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Cost Model and Cost Estimating Software
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
This chapter discusses a formalized methodology is basically a cost model, which forms the basis for estimating software.
Updating MIT's cost estimation model for shipbuilding
Smith, Matthew B., Lieutenant, junior grade
This thesis project will update the MIT ship cost estimation model by combining the two existing models (the Basic Military Training School (BMTS) Cost Model and the MIT Math Model) in order to develop a program that can ...
Towards the EDGE: Early diagenetic global explanation. A model depicting the early diagenesis of organic matter, O sub 2 , NO sub 3 , Mn, and PO sub 4
Rabouille, C.; Gaillard, J.F. (Univ. Paris 7 (France) Inst. de Physique du Globe de Paris (France))
The ultimate fate of particles in aquatic environments is their burial and transformation in surficial sediments. There is an increasing need to relate quantitatively particle fluxes in the water column to the material recycled or preserved in the sediment. For this purpose, a transport-reaction model (EDGE) that represents the early diagenetic processes occurring in surficial sediments has been designed. This model uses the incoming flux of particulate matter and the overlying water composition in order to obtain simulated concentration profiles of chemical species in the bulk sediment and interstitial waters. It consists of a set of coupled nonlinear differential equations representing the oxidation of Particulate Organic Matter (POM) by a continuous sequence of electron acceptors (i.e., O{sub 2}, NO{sub 3}{sup {minus}}, MnO{sub 2}; in its preset state). The distribution of the concentrations of six components: POM, O{sub 2}, NO{sub 3}{sup {minus}}, MnO{sub 2}, Mn{sup 2+}, and {Sigma}PO{sub 4} are currently calculated. The Monod rate law has been used for representing the mineralization of POM coupled with the consumption of oxidants, and the sequence of oxidation of organic matter is represented using an inhibition function. The distributions with depth of the concentrations of the six chemical compounds are presented for different fluxes of POM at steady-state. These calculations show that the preservation of organic carbon and the extent of the mineralization processes are very sensitive to the organic carbon rain rate. For constant fluxes of POM and MnO{sub 2} arriving at the sediment water interface, the effect of an increasing sedimentation rate, as it might be produced by an augmentation of the detrital flux, is assessed on carbon preservation.
Syllabus Information Depiction System (SIDS) user's guide
Waterman, D.K.; Skinner, N.L.
The Syllabus Information Depiction System (SIDS) is an automated tool designed to track the aircrew training syllabi of the Marine Corps. This report is the User's Manual for this data base system, providing users with instructions to help them use the system more efficiently. This document contains printed screen layouts that will guide the user step-by-step through the written instructions.
Improved diagnostic model for estimating wind energy
Endlich, R.M.; Lee, J.D.
Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.
Language model parameter estimation using user transcriptions
Hsu, Bo-June
In limited data domains, many effective language modeling techniques construct models with parameters to be estimated on an in-domain development set. However, in some domains, no such data exist beyond the unlabeled test ...
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Robust estimation procedure in panel data model
Shariff, Nurul Sima Mohamad [Faculty of Science of Technology, Universiti Sains Islam Malaysia (USIM), 71800, Nilai, Negeri Sembilan (Malaysia); Hamzah, Nor Aishah [Institute of Mathematical Sciences, Universiti Malaya, 50630, Kuala Lumpur (Malaysia)
The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectional dependence and outliers. Even though there are few methods that take into consideration the presence of cross sectional dependence in the panel, the methods may provide inconsistent parameter estimates and inferences when outliers occur in the panel. As such, an alternative method that is robust to outliers and cross sectional dependence is introduced in this paper. The properties and construction of the confidence interval for the parameter estimates are also considered in this paper. The robustness of the procedure is investigated and comparisons are made to the existing method via simulation studies. Our results have shown that robust approach is able to produce an accurate and reliable parameter estimates under the condition considered.
Ewing, Richard E.
PARAMETER ESTIMATION IN PETROLEUM AND GROUNDWATER MODELING R.E. Ewing, M.S. Pilant, J.G. Wade the location and subsequent remediation of contaminants in groundwater to the optimization of production on grand challenge problems. In today's petroleum industry, reservoir simulators are routinely used
Modeling and Parameter Estimation of Interpenetrating
Grossmann, Ignacio E.
Modeling and Parameter Estimation of Interpenetrating Polymer Network ProcessPolymer Network, PA 15213 #12;Interpenetrating Polymer Network Processp g y Monomer Initiator P l i ti tPolymerization reactor Seed particle Monomer droplet Aqueous mediaq Seed Polymer A Monomer B Seed Polymer A 2Fig 1. Seed
Byzantine Icons The Art and Science of Depiction
Durand, Frédo
. #12;Project Focus Art&Science of Depiction Software Engineering Byzantine Icons Software #12;Where of iconography is that the 'art' of writing icons is at its core a spiritual discipline." (Olga Milenback
Byzantine Icons The Art and Science of Depiction
Durand, Frédo
to write an icon. Project Focus Art&Science of Depiction Software Engineering Byzantine Icons Software' of writing icons is at its core a spiritual discipline." (Olga Milenback, Instructor) Technique "Before
Estimating Wireless Network Properties with Spatial Statistics and Models
Paris-Sud XI, Universit� de
Estimating Wireless Network Properties with Spatial Statistics and Models Janne Riihij statistics and models for different estimation problems related to wireless networks. We focus specifically wireless networks. We provide a concise survey of existing techniques from the spatial statistics
Parameter estimation for energy balance models with memory
Parameter estimation for energy balance models with memory By Lionel Roques1,*, Micka¨el D parameter estimation for one-dimensional energy balance models with mem- ory (EBMMs) given localized estimate is still possible in certain cases. Keywords: age dating; Bayesian inference; energy balance model
Nonmarket Valuation under Preference Uncertainty: Econometric Models and Estimation
Hanemann, W. Michael; Kristrom, Bengt; Li, Chuan-Zhong
3 The EconometricUNCERTAINTY: ECONOMETRIC MODELS AND ESTIMATION bY W. MichaelSection 3 introduces ihe econometric model. Section 4
Estimation of Two Popular Econometric Models: Random Effects Panel Data Model and Simultaneous Equations Model
Liu, Yue
1994. [9] Greene, W. B. , Econometric Analysis, Pearson /and Semiparametric Panel Econometric Models: Estimation andDEPendent models. This econometric software package was
Dynamic Bayesian Networks model to estimate process availability.
Paris-Sud XI, Universit� de
Dynamic Bayesian Networks model to estimate process availability. Weber P. Centre de Recherche en reported here explores a new methodology to develop Dynamic Bayesian Network-based Availability of the system availability estimation comparing DBN model with the classical Markov chain model. Keywords
Hybrid Simulation Modeling to Estimate U.S. Energy Elasticities
Hybrid Simulation Modeling to Estimate U.S. Energy Elasticities by Adam C. Baylin-Stern B.A. & Sc in the estimation of ESUBs from CIMS. Keywords: Elasticity of substitution; hybrid energy-economy model; translog-Stern Degree: Project No.: Master of Resource Management 535 Title of Thesis: Hybrid Simulation Modeling
Byzantine Icons The Art and Science of Depiction
Durand, Frédo
to write an icon. #12;2 Project Focus Art&Science of Depiction Software Engineering Byzantine Icons Software Where to Start · History · Technique · Analysis #12;3 History · Byzantium is the name given of the techniques of iconography is that the 'art' of writing icons is at its core a spiritual discipline." (Olga
The Art and Science of Depiction Fredo Durand
Durand, Fr�do
� Grass � Greener � Sky � Bluer #12;5 Color Vision 25 Plan � Color blindness � Color Opponents, Hue luminance #12;6 Color Vision 31 Blue-yellow opponent and painting � Often used to depict night � (S cones stage may reparameterize: � Brightness or Luminance or Value � Hue � Saturation Color Vision 35 Hue
The Art and Science of Depiction Fredo Durand
Durand, Fr�do
differences #12;Color Vision 24 Preferred colors � Caucasian skin � More tanned � Grass � Greener � Sky more than luminance #12;Color Vision 31 Blue-yellow opponent and painting � Often used to depict night-dark � Blue-yellow � Red-green � A later stage may reparameterize: � Brightness or Luminance or Value � Hue
The Art and Science of Depiction Fredo Durand
Durand, Fr�do
� Computational theory of vision � Invariants #12;Picture Organization & Gestalt 3 Overview � After image theory in physics � Holistic philosophy of vision � "spontaneous" organization � Opposed to unconsciousThe Art and Science of Depiction Fredo Durand MIT- Lab for Computer Science Picture Organization
Cost Model and Cost Estimating Software - DOE Directives, Delegations...
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
is basically a cost model, which forms the basis for estimating software. g4301-1chp22.pdf -- PDF Document, 190 KB Writer: John Makepeace Subjects: Administration...
Noisy Independent Factor Analysis Model for Density Estimation and Classification
Amato, U.
We consider the problem of multivariate density estimation when the unknown density is assumed to follow a particular form of dimensionality reduction, a noisy independent factor analysis (IFA) model. In this model the ...
Kambhampati, Subbarao
-circuit power and leak- age power. Models for large parametrized IP cores have been pre- sented in [6], [7]; [6] presents area models and detailed power model for fast Hadamard transform, and [7] presents area modelsACCURATE MODELS FOR ESTIMATING AREA AND POWER OF FPGA IMPLEMENTATIONS Lanping Deng, Kanwaldeep
L'Ecuyer, Pierre
1 FUNCTIONAL ESTIMATION FOR A MULTICOMPONENT AGE REPLACEMENT MODEL Pierre L'Ecuyer, Benoit Martin, controlled by a replacement rule based on age thresholds. We show how to estimate the expected cost generative simulation, maintenance models, age replacement policies. #12; 2 L'ECUYER, MARTIN, AND V ' AZQUEZ
Vázquez-Abad, Felisa J.
FUNCTIONAL ESTIMATION FOR A MULTICOMPONENT AGE REPLACEMENT MODEL Pierre L'Ecuyer, Benoit Martin, controlled by a replacement rule based on age thresholds. We show how to estimate the expected cost generative simulation, maintenance models, age replacement policies. #12; L'ECUYER, MARTIN, AND V ' AZQUEZ
Estimation of Parameters in Carbon Sequestration Models from Net Ecosystem
White, Luther
Estimation of Parameters in Carbon Sequestration Models from Net Ecosystem Exchange Data Luther in the context of a deterministic com- partmental carbon sequestration system. Sensitivity and approximation usefulness in the estimation of parameters within a compartmental carbon sequestration model. Previously we
Spatial Spectral Estimation forSpatial Spectral Estimation for Reactor Modeling and ControlReactor Modeling and Control
Scarrott, Carl
Spatial Spectral Estimation forSpatial Spectral Estimation for Reactor Modeling and ControlReactor in Magnox nuclear reactors l Establish safe operating limits l Issues: Subset of measurements Control Modeling and Control Carl Scarrott Granville Tunnicliffe-Wilson Lancaster University, UK c
Stochastic Wireless Channel Modeling, Estimation and Identification from Measurements
Olama, Mohammed M [ORNL; Djouadi, Seddik M [ORNL; Li, Yanyan [ORNL
This paper is concerned with stochastic modeling of wireless fading channels, parameter estimation, and system identification from measurement data. Wireless channels are represented by stochastic state-space form, whose parameters and state variables are estimated using the expectation maximization algorithm and Kalman filtering, respectively. The latter are carried out solely from received signal measurements. These algorithms estimate the channel inphase and quadrature components and identify the channel parameters recursively. The proposed algorithm is tested using measurement data, and the results are presented.
Battery Calendar Life Estimator Manual Modeling and Simulation
Jon P. Christophersen; Ira Bloom; Ed Thomas; Vince Battaglia
The Battery Life Estimator (BLE) Manual has been prepared to assist developers in their efforts to estimate the calendar life of advanced batteries for automotive applications. Testing requirements and procedures are defined by the various manuals previously published under the United States Advanced Battery Consortium (USABC). The purpose of this manual is to describe and standardize a method for estimating calendar life based on statistical models and degradation data acquired from typical USABC battery testing.
Estimation and prediction in spatial models with block composite likelihoods
Reich, Brian J.
Estimation and prediction in spatial models with block composite likelihoods Jo Eidsvik1 , Benjamin, IA 50011, U.S.A. (email@example.com) 1 #12;Abstract A block composite likelihood is developed for estimation and prediction in large spatial datasets. The composite likelihood is constructed from the joint
Estimating Emissions in Latin America: An Alternative to Traffic Models
Richner, Heinz
Estimating Emissions in Latin America: An Alternative to Traffic Models Margarita Oss�s de Eicker; Hans Hurni, Centre for Development and Environment (CDE), University of Bern, Switzerland Emissions allow precise estimations of these emissions but are too expensive for a broad application. A simplifed
Efficient Estimation in a Regression Model with Missing Responses
Crawford, Scott
This article examines methods to efficiently estimate the mean response in a linear model with an unknown error distribution under the assumption that the responses are missing at random. We show how the asymptotic variance is affected...
Panel data models with nonadditive unobserved heterogeneity : estimation and inference
Lee, Joonhwan
This paper considers fixed effects estimation and inference in linear and nonlinear panel data models with random coefficients and endogenous regressors. The quantities of interest - means, variances, and other moments of ...
Estimation of Random-Coefficient Demand Models: Two Empiricists' Perspective
Metaxoglou, Konstantinos
We document the numerical challenges we experienced estimating random-coefficient demand models as in Berry, Levinsohn, and Pakes (1995) using two well-known data sets and a thorough optimization design. The optimization ...
On Parameter Estimation of Urban Storm-Water Runoff Model
On Parameter Estimation of Urban Storm-Water Runoff Model Pedro Avellaneda1 ; Thomas P. Ballestero2 of these parameters are provided for modeling purposes and other urban storm-water quality applications. A normal runoff models are commonly used for urban storm-water quality applications DeCoursey 1985; Tsi- hrintzis
Logit Models for Estimating Urban Area Through Travel
Talbot, Eric
LOGIT MODELS FOR ESTIMATING URBAN AREA THROUGH TRAVEL A Thesis by ERIC TALBOT Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree... of MASTER OF SCIENCE August 2010 Major Subject: Civil Engineering LOGIT MODELS FOR ESTIMATING URBAN AREA THROUGH TRAVEL A Thesis by ERIC TALBOT Submitted to the Office of Graduate Studies of Texas A...
Sequential estimation of intramuscular EMG model parameters for prosthesis control
Paris-Sud XI, Universit� de
Sequential estimation of intramuscular EMG model parameters for prosthesis control Jonathan parameters which can lead to an active drive of an upper limb prosthesis. A system model will be presented an upper limb prosthesis using signals that express motoneuron activity. Therefore, the com- mand signals
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty
Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Cantrell, Kirk J.
The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates based on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four projections, and associated kriging variances, were averaged using the posterior model probabilities as weights. Finally, cross-validation was conducted by eliminating from consideration all data from one borehole at a time, repeating the above process, and comparing the predictive capability of the model-averaged result with that of each individual model. Using two quantitative measures of comparison, the model-averaged result was superior to any individual geostatistical model of log permeability considered.
Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling
Locatelli, R.
A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model ...
The Lithium-Ion Cell: Model, State Of Charge Estimation
Schenato, Luca
The Lithium-Ion Cell: Model, State Of Charge Estimation and Battery Management System Tutor degradation mechanisms of a Li-ion cell based on LiCoO2", Journal of Power Sources #12;Lithium ions and e and Y. Fuentes. Computer simulations of a lithium-ion polymer battery and implications for higher
Spectral jitter modeling and estimation Miltiadis Vasilakis a,b,
Stylianou, Yannis
Spectral jitter modeling and estimation Miltiadis Vasilakis a,b, *, Yannis Stylianou a modulation is referred to as jitter. During sustained vowel phonation, both modulations can be defined amplitude and the glottal pitch period, for shimmer and jitter, respectively.1 Since an unperturbed quasi
A Hierarchical Model for Estimating the Reliability of Complex Systems
Reese, Shane
an approximation to the joint posterior distribution on the total system reliability was obtained. Many reliability or bounding moments of the system reliability posterior distribution (Cole (1975), Mastran (1976), DostalA Hierarchical Model for Estimating the Reliability of Complex Systems Valen E. Johnson, Todd L
Emulating maize yields from global gridded crop models using statistical estimates
Blanc, E.
This study estimates statistical models emulating maize yield responses to changes in temperature and
Models for estimation of car fuel consumption in urban traffic
Biggs, D.C.; Akcelik
This article describes four fuel-consumption models. The models are interrelated and form part of the same modeling framework. A simpler model is derived from a more complicated model keeping the vehicle characteristic such as mass, drag function, and energy efficiency as explicit parameters at all model levels. Because vehicle characteristics are likely to change over time and from country to country, this is a particularly useful model property. For simplicity here, only the instantaneous fuel-consumption model is described in any detail. However, because of the derivation procedure, many of the features and properties of this model are present in the more aggregate models. Easy-to-use functions and graphs are given for the more aggregate models based on a ''default car'' in urban driving conditions. All parameters related to the speed profile and driving environment were calibrated using on-road data collected in Sydney, Australia. Use of the models is illustrated by estimating the fuel consumption for the microtrip.
Time-to-Compromise Model for Cyber Risk Reduction Estimation
Miles A. McQueen; Wayne F. Boyer; Mark A. Flynn; George A. Beitel
We propose a new model for estimating the time to compromise a system component that is visible to an attacker. The model provides an estimate of the expected value of the time-to-compromise as a function of known and visible vulnerabilities, and attacker skill level. The time-to-compromise random process model is a composite of three subprocesses associated with attacker actions aimed at the exploitation of vulnerabilities. In a case study, the model was used to aid in a risk reduction estimate between a baseline Supervisory Control and Data Acquisition (SCADA) system and the baseline system enhanced through a specific set of control system security remedial actions. For our case study, the total number of system vulnerabilities was reduced by 86% but the dominant attack path was through a component where the number of vulnerabilities was reduced by only 42% and the time-to-compromise of that component was increased by only 13% to 30% depending on attacker skill level.
Example: the Mediterranean basin Statistical Model Estimation Hypothesis testing Estimation and joint testing of temporal and spatial
and joint testing of temporal and spatial patterns in Climate Change Jean-Marc Azaïs, Aurélien Ribes, Journées climat, Orsay 28 et 29 Janvier 2010 #12;Example: the Mediterranean basin Statistical ModelExample: the Mediterranean basin Statistical Model Estimation Hypothesis testing Estimation
Test models for improving filtering with model errors through stochastic parameter estimation
Gershgorin, B. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States); Harlim, J. [Department of Mathematics, North Carolina State University, NC 27695 (United States)], E-mail: email@example.com; Majda, A.J. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States)
The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.
RSMASS: A simple model for estimating reactor and shield masses
Marshall, A.C.; Aragon, J.; Gallup, D.
A simple mathematical model (RSMASS) has been developed to provide rapid estimates of reactor and shield masses for space-based reactor power systems. Approximations are used rather than correlations or detailed calculations to estimate the reactor fuel mass and the masses of the moderator, structure, reflector, pressure vessel, miscellaneous components, and the reactor shield. The fuel mass is determined either by neutronics limits, thermal/hydraulic limits, or fuel damage limits, whichever yields the largest mass. RSMASS requires the reactor power and energy, 24 reactor parameters, and 20 shield parameters to be specified. This parametric approach should be applicable to a very broad range of reactor types. Reactor and shield masses calculated by RSMASS were found to be in good agreement with the masses obtained from detailed calculations.
Asymptotics for the maximum likelihood estimators of diffusion models
Jeong, Minsoo
: : : : : : 24 3 First Order Distribution and the Histogram of t(^fi2) { CEV : : : : : 25 4 First Order Distributions of t(^fi1) and t(^fi2) : : : : : : : : : : : : : : 33 1 CHAPTER I INTRODUCTION The difiusion model was originally designed and has long been used... of the estimator. Wooldridge (1994) shows that AD3 together with AD1 and AD2 implies1 AD4: S(^ ) = 0 with probability approaching to one as T !1 and ? ! 0. AD5: w?1?H(~ )?H( 0)?w?10= op(1) and w0(^ ? 0) = Op(1). Thus, with these conditions, we have w?1S(^ ) = w?1S...
Estimation of landfill emission lifespan using process oriented modeling
Ustohalova, Veronika [Institute of Waste Management, University of Duisburg-Essen, Universitaetsstrasse 15, 45141 Essen (Germany)]. E-mail: firstname.lastname@example.com; Ricken, Tim [Institute of Mechanics, University of Duisburg-Essen, Universitaetsstrasse 15, 45141 Essen (Germany); Widmann, Renatus [Institute of Waste Management, University of Duisburg-Essen, Universitaetsstrasse 15, 45141 Essen (Germany)
Depending on the particular pollutants emitted, landfills may require service activities lasting from hundreds to thousands of years. Flexible tools allowing long-term predictions of emissions are of key importance to determine the nature and expected duration of maintenance and post-closure activities. A highly capable option represents predictions based on models and verified by experiments that are fast, flexible and allow for the comparison of various possible operation scenarios in order to find the most appropriate one. The intention of the presented work was to develop a experimentally verified multi-dimensional predictive model capable of quantifying and estimating processes taking place in landfill sites where coupled process description allows precise time and space resolution. This constitutive 2-dimensional model is based on the macromechanical theory of porous media (TPM) for a saturated thermo-elastic porous body. The model was used to simulate simultaneously occurring processes: organic phase transition, gas emissions, heat transport, and settlement behavior on a long time scale for municipal solid waste deposited in a landfill. The relationships between the properties (composition, pore structure) of a landfill and the conversion and multi-phase transport phenomena inside it were experimentally determined. In this paper, we present both the theoretical background of the model and the results of the simulations at one single point as well as in a vertical landfill cross section.
Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors
Paris-Sud XI, Universit� de
Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors Fabienne Comte, Tabea of nonparametric density estimation in the pile-up model. Adaptive nonparametric estimators are proposed for the pile-up model in its simple form as well as in the case of additional measurement errors. Furthermore
Techno-Economic Models for Carbon Dioxide Compression, Transport, and Storage & Correlations for Estimating Carbon Dioxide Density and Viscosity
McCollum, David L; Ogden, Joan M
Ogden models use capital cost estimates from Skovholt�s 1993are below average but estimate capital costs that are abovediameter, it estimates capital cost below the average.
Multi-rate Modeling, Model Inference, and Estimation for Statistical Classifiers
Washington at Seattle, University of
Multi-rate Modeling, Model Inference, and Estimation for Statistical Classifiers �Ozg�ur C University of Washington 2004 Program Authorized to Offer Degree: Electrical Engineering #12;#12;University: Mari Ostendorf Reading Committee: Mari Ostendorf Jeffrey A. Bilmes Maya R. Gupta Date: #12;#12;In
Cosmological parameter estimation and Bayesian model comparison using VSA data
Anze Slosar; Pedro Carreira; Kieran Cleary; Rod D. Davies; Richard J. Davis; Clive Dickinson; Ricardo Genova-Santos; Keith Grainge; Carlos M. Gutierrez; Yaser A. Hafez; Michael P. Hobson; Michael E. Jones; Rudiger Kneissl; Katy Lancaster; Anthony Lasenby; J. P. Leahy; Klaus Maisinger; Phil J. Marshall; Guy G. Pooley; Rafael Rebolo; Jose Alberto Rubino-Martin; Ben Rusholme; Richard D. E. Saunders; Richard Savage; Paul F. Scott; Pedro J. Sosa Molina; Angela C. Taylor; David Titterington; Elizabeth Waldram; Robert A. Watson; Althea Wilkinson
We constrain the basic comological parameters using the first observations by the Very Small Array (VSA) in its extended configuration, together with existing cosmic microwave background data and other cosmological observations. We estimate cosmological parameters for four different models of increasing complexity. In each case, careful consideration is given to implied priors and the Bayesian evidence is calculated in order to perform model selection. We find that the data are most convincingly explained by a simple flat Lambda-CDM cosmology without tensor modes. In this case, combining just the VSA and COBE data sets yields the 68 per cent confidence intervals Omega_b h^2=0.034 (+0.007, -0.007), Omega_dm h^2 = 0.18 (+0.06, -0.04), h=0.72 (+0.15,-0.13), n_s=1.07 (+0.06,-0.06) and sigma_8=1.17 (+0.25, -0.20). The most general model considered includes spatial curvature, tensor modes, massive neutrinos and a parameterised equation of state for the dark energy. In this case, by combining all recent cosmological data, we find, in particular, 95 percent limit on the tensor-to-scalar ratio R < 0.63 and on the fraction of massive neutrinos f_nu < 0.11; we also obtain the 68 per cent confidence interval w=-1.06 (+0.20, -0.25) on the equation of state of dark energy.
Mass Flow Estimation with Model Bias Correction for a Turbocharged Diesel Engine
Johansen, Tor Arne
Mass Flow Estimation with Model Bias Correction for a Turbocharged Diesel Engine Tom�s Pol�ni. Based on an augmented observable Mean Value En- gine Model (MVEM) of a turbocharged Diesel engine in the intake duct. Keywords: Diesel engine, Mass flow estimation, Bias estimation, Kalman filtering, Mean value
Accuracy of Contemporary Parametric Software Estimation Models: A Comparative Analysis
Tomkins, Andrew
with delays and being costly and error- prone. Inaccurate estimation of project resources is considered as one the costs, schedule and the resources for IT projects. Software estimation is the process of predicting the effort, duration and cost required to develop a software system [2]. Estimators often rely on one or more
On the empirical statistics of parameter estimates in parametric modeling
Zhu, Yao
. The PARCOR parametrization has received considerable attention because of its attractive features. One of these features shows that the magnitudes of the k?'s obtained from the autocorrelation method are guaranteed to be less than one (6]. 10 2. 1. 2... are asymptotically unbiased estimates with covsriance matrix CA, because A are the maximum likelihood estimates. Similarly, the asymptotic probability density function of the PARCOR coeffi- cient estimates K = (kq, ks, ~ ~ ~, k&) is Gaussian and given by f(K...
Model Test Setup and Program for Experimental Estimation of Surface Loads of the SSG Kvitsy
Model Test Setup and Program for Experimental Estimation of Surface Loads of the SSG Kvits�y Pilot Engineering No. 32 ISSN: 1603-9874 Model Test Setup and Program for Experimental Estimation of Surface Loads University October, 2005 #12;#12;Preface This report presents the preparations done prior to model tests
Can a more realistic model error structure improve the parameter estimation in modelling the dynamics of sh populations?
Chen, Yong
or applying an estimation method that is robust to the error structure assumption in modelling the dynamicsCan a more realistic model error structure improve the parameter estimation in modelling the dynamics of �sh populations? Y. Chena,* , J.E. Paloheimob a Fisheries Conservation Chair Program, Fisheries
Speech enhancement using super-Gaussian speech models and noncausal a priori SNR estimation
Cohen, Israel
Speech enhancement using super-Gaussian speech models and noncausal a priori SNR estimation Israel that the performance of noncausal estimation, when applied to the problem of speech enhancement, is better under has a smaller effect on the enhanced speech signal when using the noncausal a priori SNR estimator
Comparing Local and Global Software Effort Estimation Models Reflections on a Systematic Review
protocols. Keywords: D.2.9.b Cost estimation, project effort prediction, systematic review, empirical of practice in the form of benchmarking, assessment of current activities, estimation of future tasksComparing Local and Global Software Effort Estimation Models � Reflections on a Systematic Review
Los Alamos Waste Management Cost Estimation Model; Final report: Documentation of waste management process, development of Cost Estimation Model, and model reference manual
Matysiak, L.M.; Burns, M.L.
This final report completes the Los Alamos Waste Management Cost Estimation Project, and includes the documentation of the waste management processes at Los Alamos National Laboratory (LANL) for hazardous, mixed, low-level radioactive solid and transuranic waste, development of the cost estimation model and a user reference manual. The ultimate goal of this effort was to develop an estimate of the life cycle costs for the aforementioned waste types. The Cost Estimation Model is a tool that can be used to calculate the costs of waste management at LANL for the aforementioned waste types, under several different scenarios. Each waste category at LANL is managed in a separate fashion, according to Department of Energy requirements and state and federal regulations. The cost of the waste management process for each waste category has not previously been well documented. In particular, the costs associated with the handling, treatment and storage of the waste have not been well understood. It is anticipated that greater knowledge of these costs will encourage waste generators at the Laboratory to apply waste minimization techniques to current operations. Expected benefits of waste minimization are a reduction in waste volume, decrease in liability and lower waste management costs.
Chauhan, Sanjay S.
of dam failure for use in Dam Safety Risk Assessments. For the emergency preparedness applications inundation characteristics. The scale of estimated consequences associated with dam failure, and especially making up the dam, and the reservoir head and volume at the time of failure. Defining breach parameters
......................................................................................................... 4 2.1. Heat Pump and Chiller Models
Estimation of system reliability using a semiparametric model
Wu, Leon
An important problem in reliability engineering is to predict the failure rate, that is, the frequency with which an engineered system or component fails. This paper presents a new method of estimating failure rate using ...
Modeling, estimation, and control of robot-soil interactions
Hong, Won, 1971-
This thesis presents the development of hardware, theory, and experimental methods to enable a robotic manipulator arm to interact with soils and estimate soil properties from interaction forces. Unlike the majority of ...
A Comparative Study of Estimation Models for Satellite Relative Motion�
Desai, Uri
The problem of relative spacecraft motion estimation is considered with application to various reference and relative orbits. Mean circular and elliptic orbits are analyzed, with relative orbits ranging in size from 1 km ...
Estimation of linear autoregressive models with Markov-switching, the E.M. algorithm revisited
Rynkiewicz, Joseph
This work concerns estimation of linear autoregressive models with Markov-switching using expectation maximisation (E.M.) algorithm. Our method generalise the method introduced by Elliot for general hidden Markov models and avoid to use backward recursion.
A quantitative framework For large-scale model estimation and discrimination In systems biology
Eydgahi, Hoda
Using models to simulate and analyze biological networks requires principled approaches to parameter estimation and model discrimination. We use Bayesian and Monte Carlo methods to recover the full probability distributions ...
Experimental Setup Measurements were made with the experimental configuration depicted in Figure 1. Tissue
Arthur, R. Martin
of the transducer was 7.5 MHz. Temperature in the tank was set by a heater that circulated the water in the tank depicted in Figure 1. Tissue samples were heated in an insulated tank that was filled with deionized water, which had been degassed by vacuum pumping in an appropriate vessel. Tissue was placed
Development of Property-Transfer Models for Estimating the Hydraulic Properties of Deep
Development of Property-Transfer Models for Estimating the Hydraulic Properties of Deep Sediments. #12;Development of Property-Transfer Models for Estimating the Hydraulic Properties of Deep Sediments-USGS World Wide Web: http://www.usgs.gov/ Any use of trade, product, or firm names in this publication
Run-time Modeling and Estimation of Operating System Power Consumption
John, Lizy Kurian
Run-time Modeling and Estimation of Operating System Power Consumption Tao Li Department computing systems point to the need for power modeling and estimation for all components of a system software power evaluation, as well as power management (e.g. dynamic thermal control and equal energy
Estimating suspended sediment concentrations in areas with limited hydrological data using a mixed-effects model
Venditti, Jeremy G.
Estimating suspended sediment concentrations in areas with limited hydrological data using a mixed-effects. In this study, we used a mixed-effects linear model to estimate an average SSC�Q relation for different periods the performance of the mixed-effects model against the standard rating curve, represented by a generalized least
Integrated Estimation and Tracking of Performance Model Parameters with Autoregressive Trends
Woodside, C. Murray
1 Integrated Estimation and Tracking of Performance Model Parameters with Autoregressive Trends Tao the model parameters can be tracked by an estimator such as a Kalman Filter, so that decisions can excessive cost (as is usually the case for the CPU time of a service). Because there may be significant
Data-driven Techniques to Estimate Parameters in the Homogenized Energy Model for Shape Memory Alloys
Data-driven Techniques to Estimate Parameters in the Homogenized Energy Model for Shape Memory. In this paper, we focus on the homogenized energy model for shape memory alloys (SMA). Specifically, we develop parameters are compared to the initial estimates. 1 Introduction Shape memory alloys (SMA) are novel
Hierarchical models for estimating state and demographic trends in U.S. death penalty public opinion
Gelman, Andrew
Hierarchical models for estimating state and demographic trends in U.S. death penalty public?" Because the death penalty is governed by state laws rather than federal laws, it is of special interest logistic regression model to estimate support for the death penalty as a function of the year, the state
A climate sensitivity estimate using Bayesian fusion of instrumental observations and an Earth System model
sensitivity estimate using Bayesian fusion of instrumental observations and an Earth System model, J. Geophys System model Roman Olson,1 Ryan Sriver,1 Marlos Goes,2,3 Nathan M. Urban,4,5 H. Damon Matthews,6 MuraliA climate sensitivity estimate using Bayesian fusion of instrumental observations and an Earth
Online Center of Gravity Estimation in Automotive Vehicles using Multiple Models and Switching
Duffy, Ken
Online Center of Gravity Estimation in Automotive Vehicles using Multiple Models and Switching and switching for realtime estimation of center of gravity (CG) position in automotive vehicles. The method utilizes simple linear vehicle models and assumes availability of standard stock automotive sensors. We
Parameter Estimation in Groundwater Flow Models with Distributed and Pointwise Observations*
Parameter Estimation in Groundwater Flow Models with Distributed and Pointwise Observations* Ben G concerning the least sqaures estimation of parameters in a groundwater flow model. As is typically the case9310153. #12; 1 Introduction Understanding the flow of groundwater is an important scientific and engineering
Modeling of PM Synchronous Motors for Control and Estimation Tasks
Stankoviæ, Aleksandar
is to introduce and explain gen- eral, detailed PMSM models that are used in electric drives community commonly used transformations of original PMSM model. Finally, in Section 4 we present three applications sensor. 2 A Complete PMSM Model in the abc Frame The model presented in this section includes nonsinu
Bilinear estimation of pollution source profiles in receptor models
Washington at Seattle, University of
the pollution sources based on air pollution data. This article is concerned with estimation of the source and assess the contribution of each source based on this data. There have been two traditional approaches. Los Angeles, CA 90089-2531 + Address for correspondence: NRCSE, University of Washington, Box 351720
Wavelet Based Density Estimators for Modeling Multidimensional Data Sets
Shahabi, Cyrus
the distribution of this random variable. We exhibit an estimator for the wavelet coe�?cients of this density and ionospheric data. After three levels of o#11;-line pre-processing, observations of temperature, water vapor agreement nr. F30602-99-1-0524, and unrestricted cash/equipment gifts from NCR, IBM, Intel and SUN. #12; 1
Coupling Quantitative Precipitation Estimate and Great Lakes Hydrologic Models
Rationale The ability to provide accurate runoff estimates not only impacts forecasting of the water levels of the Seaway, but can help business such as commercial shippers, marinas, and hydropower and nuclear plants environment, the Great Lakes basin, and GLERL will improve its LBRM to hourly computations and its AHPS
Statistical Simulation to Estimate Uncertain Behavioral Parameters of Hybrid Energy-Economy Models
Statistical Simulation to Estimate Uncertain Behavioral Parameters of Hybrid Energy-Economy Models 2011 # Springer Science+Business Media B.V. 2011 Abstract In energy-economy modeling, new hybrid models) backcasting a hybrid energy- economy model over a historical time period; and (3) the application of Markov
Enhanced Direction of Arrival Estimation through Electromagnetic Modeling
Cordill, Brian
Engineering is a high art that balances modeling the physical world and designing meaningful solutions based on those models. Array signal processing is no exception, and many innovative and creative solutions have come ...
Plan-view Trajectory Estimation with Dense Stereo Background Models
Darrell, T.
In a known environment, objects may be tracked in multiple views using a set of back-ground models. Stereo-based models can be illumination-invariant, but often have undefined values which inevitably lead to foreground ...
A model for estimating the potential of flexible carpool matching
Ringrose, Michael R
Savings Destination Site Area. . . . . Idle Time per Passenger Average Detour Speed Detour Coefficient Automobile Use Factor . Participant Adjustment Factor 88 90 92 94 94 96 98 . . 100 Findings . . 102 Model Demonstration Comprehensive... response to changes in the line-haul HOV savings 18 Model response to changes in the destination site area 19 Model response to changes in the idle time per passenger 91 93 95 20 Model response to changes in the average detour speed 97 LIST...
Modeling, Estimation, and Control of Waste Heat Recovery Systems
Luong, David
Steam Turbine . . . . . .and A. Ghaffari. �Steam Turbine Model. � SimulationTurbine Blade Damage from Wet Steam (Source: PTG Advisers,
An evaluation of risk simulation models for reserve estimates
Judah, Janeen Sue
in estimating reserves for petroleum economic evaluations is an 1mportant everyday problem encountered by practicing petroleum engineers. This study addresses the problem of est1mating reserves for petroleum evaluations with little available data. The risk... to reserve est1mates. Latin Hypercube sampling is a relatively recent statistical development and has never before been applied to petroleum economic evaluations or petroleum risk simulators. The results show that simple random sampling is adequate...
General model selection estimation of a periodic regression with a Gaussian noise
Konev, Victor; 10.1007/s10463-008-0193-1
This paper considers the problem of estimating a periodic function in a continuous time regression model with an additive stationary gaussian noise having unknown correlation function. A general model selection procedure on the basis of arbitrary projective estimates, which does not need the knowledge of the noise correlation function, is proposed. A non-asymptotic upper bound for quadratic risk (oracle inequality) has been derived under mild conditions on the noise. For the Ornstein-Uhlenbeck noise the risk upper bound is shown to be uniform in the nuisance parameter. In the case of gaussian white noise the constructed procedure has some advantages as compared with the procedure based on the least squares estimates (LSE). The asymptotic minimaxity of the estimates has been proved. The proposed model selection scheme is extended also to the estimation problem based on the discrete data applicably to the situation when high frequency sampling can not be provided.
Estimating sandstone permeability using network models with pore size distributions
Mathews, Alan Ronald
the effects of each parameter on the response of the network lattice. A FoR+RAv source code was written to generate and analyze the response of the network model (see Appendix G for source code description and flow chart). The controlling parameters used... in appearance to empirical data. A network model is developed to simulate the pore geometry of a clean, well-sorted sandstone. Pores were modeled as straight capillaries connected in various lattice configurations. Complex lattice configurations produce more...
Modeling, Estimation, and Control of Waste Heat Recovery Systems
Luong, David
Steam Turbine . . . . . .and A. Ghaffari. �Steam Turbine Model. � Simulation= m ? v (h in ? h out ) Steam Turbine As with the pump, the
INVENTORY OF SOLAR RADIATION/SOLAR ENERGY SYSTEMS ESTIMATORS, MODELS, SITE-SPECIFIC DATA, and Buildings Systems Integration Center National Renewable Energy Laboratory 8 July 2009 SOLAR SYSTEM POTENTIAL/calculators/PVWATTS/version1/ http://rredc.nrel.gov/solar/calculators/PVWATTS/version2/ Estimates the electrical energy
Model selection and estimation of a component in additive regression
Paris-Sud XI, Universit� de
on s and is based on non-asymptotic model selection methods. Given some linear spaces collection {Sm, m M}, we proposed and, among them, a widely used is the linear regression Z = � + k i=1 iX(i) + (2) where �;drawback of linear regression is its lack of flexibility for modeling more complex dependencies between Z
A categorical model for traffic incident likelihood estimation
Kuchangi, Shamanth
In this thesis an incident prediction model is formulated and calibrated. The primary idea of the model developed is to correlate the expected number of crashes on any section of a freeway to a set of traffic stream characteristics, so that a...
Numerically Estimating Internal Models of Dynamic Virtual Objects
Sekuler, Robert
human subjects to manipulate a computer-animated virtual object. This virtual object (vO) was a high, human cognition, human information processing, ideal performer, internal model, virtual object, virtual, specifically how humans acquire an internal model of a dynamic virtual object. Our methodology minimizes
Estimating Heat and Mass Transfer Processes in Green Roof Systems: Current Modeling Capabilities and Limitations (Presentation)
Tabares Velasco, P. C.
This presentation discusses estimating heat and mass transfer processes in green roof systems: current modeling capabilities and limitations. Green roofs are 'specialized roofing systems that support vegetation growth on rooftops.'
New methods for estimation, modeling and validation of dynamical systems using automatic differentiation�
Griffith, Daniel Todd
The main objective of this work is to demonstrate some new computational methods for estimation, optimization and modeling of dynamical systems that use automatic differentiation. Particular focus will be upon dynamical ...
Impact of aerothermal modeling on the estimation of turbine blade life
Collin, Jean E., 1978-
The impact of aerothermal modeling on estimates of turbine blade heat transfer and life was assessed for three high pressure turbine blades. The work was conducted as part of a project aimed at the evaluation of the effect ...
Estimation of OTEC Global Resources with an Ocean General Circulation Model
Frandsen, Jannette B.
Ocean Thermal Energy Conversion (OTEC) relies on the availability of temperature differencesEstimation of OTEC Global Resources with an Ocean General Circulation Model Krishnakumar Rajagopalan Postdoctoral Fellow Department of Ocean and Resources Engineering University of Hawai'i Abstract
Estimating the Market Penetration of Residential Cool Storage Technology Using Economic Cost Modeling�
Weijo, R. O.; and Brown, D. R.
This study estimated the market penetration for residential cool storage technology using economic cost modeling. Residential cool storage units produce and store chill during off-peak periods of the day to be used during times of peak electric...
Comparative Analysis of the Cost Models Used for Estimating Renovation Costs of Universities in Texas
Faquih, Yaquta Fakhruddin
Facility managers use various cost models and techniques to estimate the cost of renovating a building and to secure the required funds needed for building renovation. A literature search indicates that these techniques offer both advantages...
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using Reformulated Models
Subramanian, Venkat
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using Reformulated Models and characterize capacity fade in lithium-ion batteries. As a comple- ment to approaches to mathematically model been made in developing lithium-ion battery models that incor- porate transport phenomena
Load estimation and control using learned dynamics models Georgios Petkos and Sethu Vijayakumar
Vijayakumar, Sethu
Load estimation and control using learned dynamics models Georgios Petkos and Sethu Vijayakumar with their robustness in light of imperfect, intermediate dynamic models. I. INTRODUCTION Adaptive control the learned dynamics for control. In Section IV, we see how from a set of learned models with known inertial
Abstract--Using a bioenergetics model, we estimated daily ration and
332 Abstract--Using a bioenergetics model, we estimated daily ration and seasonal prey consumption sandbar sharks (Carcharhinus plumbeus) in Chesapeake Bay, Virginia, using a bioenergetics model* W. Wesley used in error analyses of the sandbar shark (Carcharhinus plumbeus) bioenergetics model. See text
Estimating home energy decision parameters for a hybrid energyYeconomy policy model
Estimating home energy decision parameters for a hybrid energyYeconomy policy model Mark Jaccard, Canada E-mail: email@example.com Hybrid energyYeconomy models combine the advantages of a technologically parameters translate into the behavioral parameters of a hybrid model. We then simulate household energy
Modeling, Estimation, and Control of Waste Heat Recovery Systems
Luong, David
Kan08] for flow through vertical and horizontal tubes. TheFlow Boiling Heat Transfer Inside Horizontal and Vertical Tubes. �and thin horizontal tube. 2. Working fluid flow modeled as a
Paris-Sud XI, Universit� de
and voltage, and a thermal model, which outputs are the stator and rotor temperatures. The parameter slight variations of high fre- quency resonances in the winding of a working machine fed by an industrial
Hybrid Model of Existing Buildings for Transient Thermal Performance Estimation
Xu, X.; Wang, S.
Building level energy models are important to provide accurate prediction of energy consumption for building performance diagnosis and energy efficiency assessment of retrofitting alternatives for building performance upgrading. Simplified...
Estimations of baryon asymmetry for different neutrino mass models
Amal Kr. Sarma; Hijam Zeen Devi; N. Nimai Singh
We present a comparison of the numerical prediction on baryon asymmetry of the Universe in different neutrino mass models. We start with a very brief review on the main formalism of baryogenesis via leptogenesis through decay of heavy right-handed Majorana neutrinos, and then calculate the baryon asymmetry of the universe for known six neutrino mass models viz., three quasi-degenerate, two inverted and one normal hierarchical models, which are derived from canonical seesaw formula. The corresponding mass matrices for the right-handed Majorana neutrino as well as the Dirac neutrino, which are fixed at the seesaw stage for generating correct light neutrino mass matrices, are again employed in the calculation of baryogenesis. This procedure removes possible ambiguity on the choices of Dirac neutrino and right-handed Majorana mass matrices, and fixes input parameters at the seesaw stage. We find that the ranges of predictions from both normal hierarchical model and degenerate model (DegT1A) are almost consistent with the observed baryon asymmetry of the universe. Combining the present result with other predictions such as light neutrino masses and mixing angles, and stability under radiative corrections in MSSM, the normal hierarchical model appears to be the most favourable choice of nature.
State Estimation for Force-Controlled Humanoid Balance using Simple Models in the Presence of Modeling Error
State Estimation for Force-Controlled Humanoid Balance using Simple Models in the Presence-based control frameworks, such as model predictive control (MPC), use the expected dynamics to generate that requires active balance control in the presence of modeling error. Primus humanoid shown in Figure 1
Markov models and the ensemble Kalman filter for estimation of sorption rates.
Vugrin, Eric D.; McKenna, Sean Andrew (Sandia National Laboratories, Albuquerque, NM); Vugrin, Kay White
Non-equilibrium sorption of contaminants in ground water systems is examined from the perspective of sorption rate estimation. A previously developed Markov transition probability model for solute transport is used in conjunction with a new conditional probability-based model of the sorption and desorption rates based on breakthrough curve data. Two models for prediction of spatially varying sorption and desorption rates along a one-dimensional streamline are developed. These models are a Markov model that utilizes conditional probabilities to determine the rates and an ensemble Kalman filter (EnKF) applied to the conditional probability method. Both approaches rely on a previously developed Markov-model of mass transfer, and both models assimilate the observed concentration data into the rate estimation at each observation time. Initial values of the rates are perturbed from the true values to form ensembles of rates and the ability of both estimation approaches to recover the true rates is examined over three different sets of perturbations. The models accurately estimate the rates when the mean of the perturbations are zero, the unbiased case. For the cases containing some bias, addition of the ensemble Kalman filter is shown to improve accuracy of the rate estimation by as much as an order of magnitude.
Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates
Sengupta, M.; Gotseff, P.
This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear sky model performance.
On the estimation of galaxy structural parameters: the Sersic Model
Ignacio Trujillo; Alister W. Graham; Nicola Caon
This paper addresses some questions which have arisen from the use of the S\\'ersic r^{1/n} law in modelling the luminosity profiles of early type galaxies. The first issue deals with the trend between the half-light radius and the structural parameter n. We show that the correlation between these two parameters is not only real, but is a natural consequence from the previous relations found to exist between the model-independent parameters: total luminosity, effective radius and effective surface brightness. We also define a new galaxy concentration index which is largely independent of the image exposure depth, and monotonically related with n. The second question concerns the curious coincidence between the form of the Fundamental Plane and the coupling between _e and r_e when modelling a light profile. We explain, through a mathematical analysis of the S\\'ersic law, why the quantity r_e_e^{0.7} appears almost constant for an individual galaxy, regardless of the value of n (over a large range) adopted in the fit to the light profile. Consequently, Fundamental Planes of the form r_e_e^{0.7} propto sigma_0^x (for any x, and where sigma_0 is the central galaxy velocity dispersion) are insensitive to galaxy structure. Finally, we address the problematic issue of the use of model-dependent galaxy light profile parameters versus model-independent quantities for the half-light radii, mean surface brightness and total galaxy magnitude. The former implicitly assume that the light profile model can be extrapolated to infinity, while the latter quantities, in general, are derived from a signal-to-noise truncated profile. We quantify (mathematically) how these parameters change as one reduces the outer radius of an r^{1/n} profile, and reveal how these can vary substantially when n>4.
Model independent foreground power spectrum estimation using WMAP 5-year data
Ghosh, Tuhin; Souradeep, Tarun [IUCAA, Post Bag 4, Ganeshkhind, Pune-411007 (India); Saha, Rajib [IUCAA, Post Bag 4, Ganeshkhind, Pune-411007 (India); Jet Propulsion Laboratory, M/S 169-327, 4800 Oak Grove Drive, Pasadena, California 91109 (United States); California Institute of Technology, Pasadena, California 91125 (United States); Department of Physics, Indian Institute of Technology, Kanpur, U.P, 208016 (India); Jain, Pankaj [Department of Physics, Indian Institute of Technology, Kanpur, U.P, 208016 (India)
In this paper, we propose and implement on WMAP 5 yr data a model independent approach of foreground power spectrum estimation for multifrequency observations of the CMB experiments. Recently, a model independent approach of CMB power spectrum estimation was proposed by Saha et al. 2006. This methodology demonstrates that the CMB power spectrum can be reliably estimated solely from WMAP data without assuming any template models for the foreground components. In the current paper, we extend this work to estimate the galactic foreground power spectrum using the WMAP 5 yr maps following a self-contained analysis. We apply the model independent method in harmonic basis to estimate the foreground power spectrum and frequency dependence of combined foregrounds. We also study the behavior of synchrotron spectral index variation over different regions of the sky. We use the full sky Haslam map as an external template to increase the degrees of freedom, while computing the synchrotron spectral index over the frequency range from 408 MHz to 94 GHz. We compare our results with those obtained from maximum entropy method foreground maps, which are formed in pixel space. We find that relative to our model independent estimates maximum entropy method maps overestimate the foreground power close to galactic plane and underestimates it at high latitudes.
Distributed state estimation and model predictive control of linear interconnected system
Boyer, Edmond
requirements, modern control systems are becoming more and more complex. For these processes, different controlDistributed state estimation and model predictive control of linear interconnected system: In this paper, a distributed and networked control system architecture based on independent Model Predictive
Comparison of model estimates of the effects of aviation emissions on atmospheric ozone and methane
Jacobson, Mark
Comparison of model estimates of the effects of aviation emissions on atmospheric ozone and methane is the effects of aviation emissions on ozone and atmospheric chemistry. In this study the effects of aviation emissions on atmospheric ozone for 2006 and two projections for 2050 are compared among seven models
Exact Maximum Likelihood estimator for the BL-GARCH model under elliptical distributed
Paris-Sud XI, Universit� de
Exact Maximum Likelihood estimator for the BL-GARCH model under elliptical distributed innovations, Brisbane QLD 4001, Australia Abstract We are interested in the parametric class of Bilinear GARCH (BL-GARCH examine, in this paper, the BL-GARCH model in a general setting under some non-normal distributions. We
Modeling and Bayesian parameter estimation for shape memory alloy bending actuators
Modeling and Bayesian parameter estimation for shape memory alloy bending actuators John H. Crewsa energy model (HEM) for shape memory alloy (SMA) bending actuators. Additionally, we utilize a Bayesian. Keywords: shape memory alloys, uncertainty quantificiation, markov chain monte carlo 1. INTRODUCTION Shape
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model
Adler, Joan
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model Zaher Abstract We have analysed low and high temperature series expansions for the three�dimensional Ising model on the simple cubic lattice. Our analysis of Butera and Comi's new 32 term high temperature series yields K c
On the Parameter Estimation of Linear Models of Aggregate Power System Loads
Ca�izares, Claudio A.
1 On the Parameter Estimation of Linear Models of Aggregate Power System Loads Valery Knyazkin-- This paper addressed some theoretical and practical issues relevant to the problem of power system load, and the corresponding results are used to validate a commonly used linear model of aggre- gate power system load
ACCEPTED TO IEEE TRANSACTIONS ON POWER SYSTEMS 1 On the Parameter Estimation and Modeling of
Ca�izares, Claudio A.
ACCEPTED TO IEEE TRANSACTIONS ON POWER SYSTEMS 1 On the Parameter Estimation and Modeling of Aggregate Power System Loads Valery Knyazkin, Student Member, IEEE, Claudio Ca~nizares, Senior Member, IEEE relevant to the problem of power system load modeling and identification. Two identification techniques
Irizarry, Rafael A.
ASYMPTOTIC DISTRIBUTION OF ESTIMATES FOR A TIME-VARYING PARAMETER IN A HARMONIC MODEL WITH MULTIPLE harmonic regression models are useful for cases where harmonic parameters appear to be time-varying. Least, harmonic regression, signal processing, sound analysis, time-varying parameters, weighted least squares
Coastal DEMs integrate seafloor bathymetry and land topography to depict Earth's solid surface, and help us better understand a variety of ocean processes.
Coastal DEMs integrate seafloor bathymetry and land topography to depict Earth's solid surface Sheet What is a coastal DEM? A coastal DEM depicts Earth's land surface and ocean bottom. It is made
Optimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model Predictive Control
Mittelmann, Hans D.
is shown by applying it to a case study involving composition control of a binary distillation column. I is demonstrated in a binary high-purity distillation column case study by Weischedel and McAvoy [7], a demandingOptimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model
A Monte Carlo study of the distribution of parameter estimators in a dual exponential decay model
Garcia, Raul
of an estimate of the reliability of the parameter estimates calculated. In 1965, Bell and Garcia [2] developed a computer program which permits a solution of the parameters without the time-consuming effort of manual calcu- lations. The same year, Rossing [3...A MONTE CARLO STUDY OF THE DISTRIBUTION OF PARAMETER ESTIMATORS IN A DUAL EXPONENTIAL DECAY MODEL A Thesis by SAUL GARCIA Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirements for the degree...
Parameter estimation from flowing fluid temperature logging data in unsaturated fractured rock using multiphase inverse modeling
Mukhopadhyay, S.; Tsang, Y.; Finsterle, S.
A simple conceptual model has been recently developed for analyzing pressure and temperature data from flowing fluid temperature logging (FFTL) in unsaturated fractured rock. Using this conceptual model, we developed an analytical solution for FFTL pressure response, and a semianalytical solution for FFTL temperature response. We also proposed a method for estimating fracture permeability from FFTL temperature data. The conceptual model was based on some simplifying assumptions, particularly that a single-phase airflow model was used. In this paper, we develop a more comprehensive numerical model of multiphase flow and heat transfer associated with FFTL. Using this numerical model, we perform a number of forward simulations to determine the parameters that have the strongest influence on the pressure and temperature response from FFTL. We then use the iTOUGH2 optimization code to estimate these most sensitive parameters through inverse modeling and to quantify the uncertainties associated with these estimated parameters. We conclude that FFTL can be utilized to determine permeability, porosity, and thermal conductivity of the fracture rock. Two other parameters, which are not properties of the fractured rock, have strong influence on FFTL response. These are pressure and temperature in the borehole that were at equilibrium with the fractured rock formation at the beginning of FFTL. We illustrate how these parameters can also be estimated from FFTL data.
Analyticity, Convergence and Convergence Rate of Recursive Maximum Likelihood Estimation in Hidden Markov Models
Tadi?, Vladislav B
This paper considers the asymptotic properties of the recursive maximum likelihood estimation in hidden Markov models. The paper is focused on the asymptotic behavior of the log-likelihood function and on the point-convergence and convergence rate of the recursive maximum likelihood estimator. Using the principle of analytical continuation, the analyticity of the asymptotic log-likelihood function is shown for analytically parameterized hidden Markov models. Relying on this fact and some results from differential geometry (Lojasiewicz inequality), the almost sure point-convergence of the recursive maximum likelihood algorithm is demonstrated, and relatively tight bounds on the convergence rate are derived. As opposed to the existing result on the asymptotic behavior of maximum likelihood estimation in hidden Markov models, the results of this paper are obtained without assuming that the log-likelihood function has an isolated maximum at which the Hessian is strictly negative definite.
A Neural Network Model for Construction Projects Site Overhead Cost Estimating in Egypt
ElSawy, Ismaail; Razek, Mohammed Abdel
Estimating of the overhead costs of building construction projects is an important task in the management of these projects. The quality of construction management depends heavily on their accurate cost estimation. Construction costs prediction is a very difficult and sophisticated task especially when using manual calculation methods. This paper uses Artificial Neural Network (ANN) approach to develop a parametric cost-estimating model for site overhead cost in Egypt. Fifty-two actual real-life cases of building projects constructed in Egypt during the seven year period 2002-2009 were used as training materials. The neural network architecture is presented for the estimation of the site overhead costs as a percentage from the total project price.
Modeling and identification of parallel nonlinear systems: Structural classification and parameter estimation methods
Chen, H.W. (Los Alamos National Lab., NM (United States). Biophysics Group M715)
Structural classification and parameter estimation (SCPE) methods are used for studying single-input single-output (SISO) parallel linear-nonlinear-linear (LNL), linear-nonlinear (LN), and nonlinear-linear (NL) system models from input-output (I-O) measurements. The uniqueness of the I-O mappings (see the definition of the I-O mapping in Section 3-A) of some model structures is discussed. The uniqueness of the I-O mappings (see the definition of the I-O mapping in Section 3-A) of some model structures is discussed. The uniqueness of I-O mappings of different models tells them in what conditions different model structures can be differentiated from one another. Parameter uniqueness of the I-O mapping of a given structural model is also discussed, which tells the authors in what conditions a given model's parameters can be uniquely estimated from I-O measurements. These methods are then generalized so that they can be used to study single-input multi-output (SIMO), multi-input single-output (MISO), as well as multi-input multi-output (MIMO) nonlinear system models. Parameter estimation of the two-input single-output nonlinear system model (denoted as the 2f-structure in 2 cited references), which was left unsolved previously, can now be obtained using the newly derived algorithms. Applications of SCPE methods for modeling visual cortical neurons, system fault detection, modeling and identification of communication networks, biological systems, and natural and artificial neural networks are also discussed. The feasibility of these methods is demonstrated using simulated examples. SCPE methods presented in this paper can be further developed to study more complicated block-structures models, and will therefore have future potential for modeling and identifying highly complex multi-input multi-output nonlinear systems.
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using First-Principles-Based Efficient Reformulated Models
Subramanian, Venkat
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using First parameters of lithium-ion batteries are estimated using a first-principles electrochemical engineering model and understanding of lithium-ion batteries using physics-based first-principles models. These models are based
Estimating Water Quality Pollution Impacts Based on Economic Loss Models in Urbanization Process
Yu, Qian
. Research has targeted the assessment toward economic loss evaluation Grossman and Alan 1995; Ofiara 2001Estimating Water Quality Pollution Impacts Based on Economic Loss Models in Urbanization Process and spatial characteristics of different water quality parameters, and simulating economic loss of water
Application of mark-recapture models to estimation of the population size of plants
Alexander, Helen M.; Slade, Norman A.; Kettle, W. Dean
observed in a particular year may greatly underestimate the true population size, just as a count of animals in traps does not adequately estimate the total number of animals in an area. Using a family of closed population models (CAPTURE), we applied mark...
Parameter Estimation and Life Modeling of Lithium-Ion Cells Shriram Santhanagopalan,*,a
Parameter Estimation and Life Modeling of Lithium-Ion Cells Shriram Santhanagopalan,*,a Qi Zhang Carolina, Columbia, South Carolina 29208, USA Lithium-ion pouch cells were cycled at five different. The lithium-ion cell is among the most popular candidates con- sidered actively as a replacement for nickel
Imperial College, London
SPACETIME BLOCK CODING : JOINT DETECTION AND CHANNEL ESTIMATION USING MULTIPLE MODEL THEORY Harini of Sheffield, Mappin Street, Sheffield S1 3JD. Email: firstname.lastname@example.com ABSTRACT A joint decoding method for spacetime block codes [1, 2] is pre sented. The spacetime coded signals can be viewed as a first
Imperial College, London
SPACE-TIME BLOCK CODING : JOINT DETECTION AND CHANNEL ESTIMATION USING MULTIPLE MODEL THEORY Harini of Sheffield, Mappin Street, Sheffield S1 3JD. Email: firstname.lastname@example.com ABSTRACT A joint decoding method for space-time block codes [1, 2] is pre- sented. The space-time coded signals can be viewed as a first
A Model for Human Interruptability: Experimental Evaluation and Automatic Estimation from Wearable Sensors
A Model for Human Interruptability: Experimental Evaluation and Automatic Estimation from Wearable Sensors Nicky Kern, Stavros Antifakos, Bernt Schiele Perceptual Computing and Computer Vision ETH Zurich sensors. It is scalable for a large number of sensors, contexts, and situations and allows for online
Boyer, Edmond
the global warming due to high concentration of CO2 in the atmosphere. However, in case of massive accidental to specific properties regarding its triple point. Then, this CO2 flakes creation may be followed1 ASSESSMENT OF THE MODELS FOR THE ESTIMATION OF THE CO2 RELEASES TOXIC EFFECTS Fr�d�ric Antoine
SO2 emissions and lifetimes: Estimates from inverse modeling using in situ and global, spacebased
Martin, Randall
SO2 emissions and lifetimes: Estimates from inverse modeling using in situ and global, spacebased 18 March 2011. [1] Topdown constraints on global sulfur dioxide (SO2) emissions are inferred through of GEOSChem for inversion of SO2 columns to emissions. The seasonal mean SO2 lifetime calculated with the GEOS
Edinburgh Research Explorer Comparison of models for estimation of long-term exposure to
Millar, Andrew J.
-term exposure to air pollution in cohort studies' Atmospheric Environment, vol 62, pp. 530-539., 10.1016/j to Air Pollution in Cohort Studies Beverland, I.J.* Department of Civil Engineering, University.L. and Agius, R.M. (2012) Comparison of models for estimation of long-term exposure to air pollution in cohort
1 COMPARISON OF SEISMIC RISK ESTIMATES USING DIFFERENT METHODS TO MODEL FRAGILITY Pierre Gehl1 , Ariane Ducellier2 , Caterina Negulescu3 , Jaime Abad4 and John Douglas5 Seismic risk evaluations play of decades hundreds of such studies have been conducted. However, the assessment of seismic risk is always
Estimation of Saturation of Permanent-Magnet Synchronous Motors Through an Energy-Based Model
Jebai, AlKassem; Martin, Philippe; Rouchon, Pierre
We propose a parametric model of the saturated Permanent-Magnet Synchronous Motor (PMSM) together with an estimation method of the magnetic parameters. The model is based on an energy function which simply encompasses the saturation effects. Injection of fast-varying pulsating voltages and measurements of the resulting current ripples then permit to identify the magnetic parameters by linear least squares. Experimental results on a surface-mounted PMSM and an interoir magnet PMSM illustrate the relevance of the approach.
An iterative stochastic ensemble method for parameter estimation of subsurface flow models
Elsheikh, Ahmed H., E-mail: email@example.com [Center for Subsurface Modeling (CSM), Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Dept. of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia); Dept. of Applied Mathematics and Computational Sciences, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia); Wheeler, Mary F. [Center for Subsurface Modeling (CSM), Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States)] [Center for Subsurface Modeling (CSM), Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Hoteit, Ibrahim [Dept. of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia) [Dept. of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia); Dept. of Applied Mathematics and Computational Sciences, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)
Parameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss�Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates.
Comparison of Fourier and model-based estimators in single mode multiaxial interferometry
E. Tatulli; J. -B. LeBouquin
There are several solutions to code the signal arising from optical long baseline multi-aperture interferometers. In this paper,we focus on the {\\bf non homothetic spatial coding scheme} (multiaxial) with the fringe pattern coded along one dimension on one detector(all-in-one). After describing the physical principles governing single mode interferometers using that sort of recombination scheme, we analyze two different existing methods that measure the source visibility. The first technique, so-called Fourier estimator, consists in integrating the high frequency peak of the power spectral density of the interferogram. The second method, so-called model-based estimator, has been specifically developed for the AMBER instrument of the VLTI and deals with directly modelling the interferogram recorded on the detector. Performances of both estimators are computed in terms of Signal to Noise Ratio (SNR) of the visibility, assuming that the interferograms are perturbed by photon and detector noises. Theoretical expressions of the visibility SNR are provided, validated through numerical computations and then compared. We show that the model-based estimator offers up to 5 times better performances than the Fourier one.
A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive Model
Dave Higdon; Jordan D. McDonnell; Nicolas Schunck; Jason Sarich; Stefan M. Wild
Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model $\\eta(\\theta)$ where $\\theta$ denotes the uncertain, best input setting. Hence the statistical model is of the form $y = \\eta(\\theta) + \\epsilon$, where $\\epsilon$ accounts for measurement, and possibly other error sources. When non-linearity is present in $\\eta(\\cdot)$, the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and non-standard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. While quite generally applicable, MCMC requires thousands, or even millions of evaluations of the physics model $\\eta(\\cdot)$. This is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory (DFT) model, using experimental mass/binding energy measurements from a collection of atomic nuclei. We also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory (ANL).
Basu, Sarbani [Department of Astronomy, Yale University, P.O. Box 208101, New Haven, CT 06520-8101 (United States); Verner, Graham A.; Chaplin, William J.; Elsworth, Yvonne, E-mail: firstname.lastname@example.com, E-mail: email@example.com, E-mail: email@example.com, E-mail: email@example.com [School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham B15 2TT (United Kingdom)
Accurate and precise values of radii and masses of stars are needed to correctly estimate properties of extrasolar planets. We examine the effect of uncertainties in stellar model parameters on estimates of the masses, radii, and average densities of solar-type stars. We find that in the absence of seismic data on solar-like oscillations, stellar masses can be determined to a greater accuracy than either stellar radii or densities; but to get reasonably accurate results the effective temperature, log g, and metallicity must be measured to high precision. When seismic data are available, stellar density is the most well-determined property, followed by radius, with mass the least well-determined property. Uncertainties in stellar convection, quantified in terms of uncertainties in the value of the mixing length parameter, cause the most significant errors in the estimates of stellar properties.
Review of uncertainty estimates associated with models for assessing the impact of breeder reactor radioactivity releases
Miller, C.; Little, C.A.
The purpose is to summarize estimates based on currently available data of the uncertainty associated with radiological assessment models. The models being examined herein are those recommended previously for use in breeder reactor assessments. Uncertainty estimates are presented for models of atmospheric and hydrologic transport, terrestrial and aquatic food-chain bioaccumulation, and internal and external dosimetry. Both long-term and short-term release conditions are discussed. The uncertainty estimates presented in this report indicate that, for many sites, generic models and representative parameter values may be used to calculate doses from annual average radionuclide releases when these calculated doses are on the order of one-tenth or less of a relevant dose limit. For short-term, accidental releases, especially those from breeder reactors located in sites dominated by complex terrain and/or coastal meteorology, the uncertainty in the dose calculations may be much larger than an order of magnitude. As a result, it may be necessary to incorporate site-specific information into the dose calculation under these circumstances to reduce this uncertainty. However, even using site-specific information, natural variability and the uncertainties in the dose conversion factor will likely result in an overall uncertainty of greater than an order of magnitude for predictions of dose or concentration in environmental media following shortterm releases.
Estimating Loss-of-Coolant Accident Frequencies for the Standardized Plant Analysis Risk Models
S. A. Eide; D. M. Rasmuson; C. L. Atwood
The U.S. Nuclear Regulatory Commission maintains a set of risk models covering the U.S. commercial nuclear power plants. These standardized plant analysis risk (SPAR) models include several loss-of-coolant accident (LOCA) initiating events such as small (SLOCA), medium (MLOCA), and large (LLOCA). All of these events involve a loss of coolant inventory from the reactor coolant system. In order to maintain a level of consistency across these models, initiating event frequencies generally are based on plant-type average performance, where the plant types are boiling water reactors and pressurized water reactors. For certain risk analyses, these plant-type initiating event frequencies may be replaced by plant-specific estimates. Frequencies for SPAR LOCA initiating events previously were based on results presented in NUREG/CR-5750, but the newest models use results documented in NUREG/CR-6928. The estimates in NUREG/CR-6928 are based on historical data from the initiating events database for pressurized water reactor SLOCA or an interpretation of results presented in the draft version of NUREG-1829. The information in NUREG-1829 can be used several ways, resulting in different estimates for the various LOCA frequencies. Various ways NUREG-1829 information can be used to estimate LOCA frequencies were investigated and this paper presents two methods for the SPAR model standard inputs, which differ from the method used in NUREG/CR-6928. In addition, results obtained from NUREG-1829 are compared with actual operating experience as contained in the initiating events database.
An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models
Harlim, John, E-mail: email@example.com [Department of Mathematics and Department of Meteorology, the Pennsylvania State University, University Park, PA 16802, Unites States (United States)] [Department of Mathematics and Department of Meteorology, the Pennsylvania State University, University Park, PA 16802, Unites States (United States); Mahdi, Adam, E-mail: email@example.com [Department of Mathematics, North Carolina State University, Raleigh, NC 27695 (United States)] [Department of Mathematics, North Carolina State University, Raleigh, NC 27695 (United States); Majda, Andrew J., E-mail: email@example.com [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, New York, NY 10012 (United States)
A central issue in contemporary science is the development of nonlinear data driven statistical�dynamical models for time series of noisy partial observations from nature or a complex model. It has been established recently that ad-hoc quadratic multi-level regression models can have finite-time blow-up of statistical solutions and/or pathological behavior of their invariant measure. Recently, a new class of physics constrained nonlinear regression models were developed to ameliorate this pathological behavior. Here a new finite ensemble Kalman filtering algorithm is developed for estimating the state, the linear and nonlinear model coefficients, the model and the observation noise covariances from available partial noisy observations of the state. Several stringent tests and applications of the method are developed here. In the most complex application, the perfect model has 57 degrees of freedom involving a zonal (east�west) jet, two topographic Rossby waves, and 54 nonlinearly interacting Rossby waves; the perfect model has significant non-Gaussian statistics in the zonal jet with blocked and unblocked regimes and a non-Gaussian skewed distribution due to interaction with the other 56 modes. We only observe the zonal jet contaminated by noise and apply the ensemble filter algorithm for estimation. Numerically, we find that a three dimensional nonlinear stochastic model with one level of memory mimics the statistical effect of the other 56 modes on the zonal jet in an accurate fashion, including the skew non-Gaussian distribution and autocorrelation decay. On the other hand, a similar stochastic model with zero memory levels fails to capture the crucial non-Gaussian behavior of the zonal jet from the perfect 57-mode model.
Glass Property Data and Models for Estimating High-Level Waste Glass Volume
Vienna, John D.; Fluegel, Alexander; Kim, Dong-Sang; Hrma, Pavel R.
This report describes recent efforts to develop glass property models that can be used to help estimate the volume of high-level waste (HLW) glass that will result from vitrification of Hanford tank waste. The compositions of acceptable and processable HLW glasses need to be optimized to minimize the waste-form volume and, hence, to save cost. A database of properties and associated compositions for simulated waste glasses was collected for developing property-composition models. This database, although not comprehensive, represents a large fraction of data on waste-glass compositions and properties that were available at the time of this report. Glass property-composition models were fit to subsets of the database for several key glass properties. These models apply to a significantly broader composition space than those previously publised. These models should be considered for interim use in calculating properties of Hanford waste glasses.
Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels
Olama, Mohammed M [ORNL] [ORNL; Djouadi, Seddik M [ORNL] [ORNL; Li, Yanyan [ORNL] [ORNL; Fathy, Aly [University of Tennessee (UT)] [University of Tennessee (UT)
In this paper, stochastic differential equations (SDEs) are used to model ultrawideband (UWB) indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and non-resolvable multipath received signals are considered and represented as small-scaled Nakagami fading. The proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method s viability and the results are presented.
Enhance accuracy in Software cost and schedule estimation by using "Uncertainty Analysis and Assessment" in the system modeling process
Vasantrao, Kardile Vilas
Accurate software cost and schedule estimation are essential for software project success. Often it referred to as the "black art" because of its complexity and uncertainty, software estimation is not as difficult or puzzling as people think. In fact, generating accurate estimates is straightforward-once you understand the intensity of uncertainty and framework for the modeling process. The mystery to successful software estimation-distilling academic information and real-world experience into a practical guide for working software professionals. Instead of arcane treatises and rigid modeling techniques, this will guide highlights a proven set of procedures, understandable formulas, and heuristics that individuals and development teams can apply to their projects to help achieve estimation proficiency with choose appropriate development approaches In the early stage of software life cycle project manager are inefficient to estimate the effort, schedule, cost estimation and its development approach .This in tu...
Essays on Regression Spline Structural Nonparametric Stochastic Production Frontier Estimation and Inefficiency Analysis Models
Li, Ke
of the requirements for the degree of DOCTOR OF PHILOSOPHY December 2010 Major Subject: Agricultural Economics Essays on Regression Spline Structural Nonparametric Stochastic Production Frontier Estimation and Ine ciency Analysis Models Copyright 2010 Ke Li... of the requirements for the degree of DOCTOR OF PHILOSOPHY Approved by: Chair of Committee, Ximing Wu Committee Members, David Bessler H. Alan Love Qi Li Head of Department, John P. Nichols December 2010 Major Subject: Agricultural Economics iii ABSTRACT...
New methods for estimation, modeling and validation of dynamical systems using automatic differentiation
Griffith, Daniel Todd
computation and evaluation of partial derivatives with minimal user coding. The key results in this dissertation details the use of OCEA through a number of computational studies in estimation and dynamical modeling. Several prototype problems are studied... Embedding Method), has been recently developed which shows promise for efficient computation and evaluation of partial derivatives. For a rather arbitrary sequentially substituted set of functions, coded in FORTRAN 90, OCEA invokes operator overloading...
Modeling and estimation in Gaussian graphical models : maximum-entropy methods and walk-sum analysis
Chandrasekaran, Venkat
Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fields such as computer vision, image processing, ...
Stochastic Differential Equations for Modeling, Estimation and Identification of Mobile-to-Mobile Communication Channels
Olama, Mohammed M [ORNL; Djouadi, Seddik M [ORNL; Charalambous, Prof. Charalambos [University of Cyprus
Mobile-to-mobile networks are characterized by node mobility that makes the propagation environment time varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) which varies from one observation instant to the next. The current models do not capture and track the time varying characteristics. This paper is concerned with dynamical modelling of mobile-to-mobile channels, parameter estimation and identification from received signal measurements. The evolution of the propagation environment is described by stochastic differential equations. In particular, it is shown that the parameters of the models can be determined by approximating the band-limited DPSD using the Gauss-Newton method. However, since the DPSD is not available online, we propose to use a filter-based expectation maximization algorithm and Kalman filter to estimate the channel parameters and states, respectively. The scheme results in a finite dimensional filter which only uses the first and second order statistics. The algorithm is recursive allowing the inphase and quadrature components and parameters to be estimated online from received signal measurements. The algorithms are tested using experimental data collected from moving sensor nodes in indoor and outdoor environments demonstrating the method s viability.
Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation
Gershgorin, B. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States); Harlim, J. [Department of Mathematics, North Carolina State University, NC 27695 (United States)], E-mail: firstname.lastname@example.com; Majda, A.J. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States)
The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates high predictive skill, comparable with the skill of the perfect model for a duration of many eddy turnover times especially in the unstable regime.
RADTRAD: A simplified model for RADionuclide Transport and Removal And Dose estimation
Humphreys, S.L.; Miller, L.A.; Monroe, D.K. [Sandia National Labs., Albuquerque, NM (United States); Heames, T.J. [ITSC, Albuquerque, NM (United States)
This report documents the RADTRAD computer code developed for the U.S. Nuclear Regulatory Commission (NRC) Office of Nuclear Reactor Regulation (NRR) to estimate transport and removal of radionuclides and dose at selected receptors. The document includes a users` guide to the code, a description of the technical basis for the code, the quality assurance and code acceptance testing documentation, and a programmers` guide. The RADTRAD code can be used to estimate the containment release using either the NRC TID-14844 or NUREG-1465 source terms and assumptions, or a user-specified table. In addition, the code can account for a reduction in the quantity of radioactive material due to containment sprays, natural deposition, filters, and other natural and engineered safety features. The RADTRAD code uses a combination of tables and/or numerical models of source term reduction phenomena to determine the time-dependent dose at user-specified locations for a given accident scenario. The code system also provides the inventory, decay chain, and dose conversion factor tables needed for the dose calculation. The RADTRAD code can be used to assess occupational radiation exposures, typically in the control room; to estimate site boundary doses; and to estimate dose attenuation due to modification of a facility or accident sequence.
Modeling Estimated Personnel Needs for a Potential Foot and Mouth Disease Outbreak
Simmons, K; Hullinger, P
Foot and Mouth disease (FMD) is a highly infectious and contagious viral disease affecting cloven-hoofed livestock that was last detected in the United States (US) in 1929. The prevalence of FMD in other countries, as well as the current potential for this virus to be used as a form of agroterrorism, has made preparations for a potential FMD outbreak a national priority. To assist in the evaluation of national preparedness, all 50 states were surveyed via e-mail, telephone and web search to obtain emergency response plans for FMD or for foreign animal diseases in general. Information from 33 states was obtained and analyzed for estimates of personnel resources needed to respond to an outbreak. These estimates were consolidated and enhanced to create a tool that could be used by individual states to better understand the personnel that would be needed to complete various tasks over time during an outbreak response. The estimates were then coupled, post-processing, to the output from FMD outbreaks simulated in California using the Multiscale Epidemiological/Economic Simulation and Analysis (MESA) model at Lawrence Livermore National Laboratory to estimate the personnel resource demands, by task, over the course of an outbreak response.
A Biomass-based Model to Estimate the Plausibility of Exoplanet Biosignature Gases
Seager, S; Hu, R
Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry and biological thermodynamics. The new framework is intended to liberate predictive atmosphere models from requiring fixed, Earth-like biosignature gas source fluxes. New biosignature gases can be considered with a check that the biomass estimate is physically plausible. We have validated the models on terrestrial production of NO, H2S, CH4, CH3Cl, and DMS. We have applied the models to propose NH3 as a biosignature gas on a "cold Haber World," a planet with a N2-H2 atmosphere, and to demonstrate why gases such as CH3Cl must have too large of a biomass to be a plausible biosignature gas on planets with Earth or early-Earth-like atmospheres orbiting a Sun-like star. To construct the biomass models, we developed a functional classification of biosignature gases, and found that gases (such...
Using Pre-Modeled Scenarios to Estimate Groundwater VOC Concentrations Resulting from Vadose Zone Sources
Oostrom, Martinus; Truex, Michael J.; Rice, Amy K.; Johnson, Christian D.; Carroll, Kenneth C.; Becker, Dave; Simon, Michelle A.
Soil vapor extraction (SVE) is a prevalent remediation approach for volatile contaminants in the vadose zone. To support selection of an appropriate endpoint for the SVE remedy, an evaluation is needed to determine whether vadose zone contamination has been diminished sufficiently to protect groundwater. When vapor-phase transport is an important component of the overall contaminant fate and transport from a vadose zone source, the contaminant concentration expected in groundwater is controlled by a limited set of parameters, including specific site dimensions, vadose zone properties, and source characteristics. An approach was developed for estimating the contaminant concentration in groundwater resulting from a contaminant source in the vadose zone based on pre-modeling contaminant transport for a matrix of parameter value combinations covering a range of potential site conditions. An interpolation and scaling process are then applied to estimate groundwater impact for site-specific conditions.
Off-Highway Gasoline Consuption Estimation Models Used in the Federal Highway Administration Attribution Process: 2008 Updates
Hwang, Ho-Ling [ORNL; Davis, Stacy Cagle [ORNL
This report is designed to document the analysis process and estimation models currently used by the Federal Highway Administration (FHWA) to estimate the off-highway gasoline consumption and public sector fuel consumption. An overview of the entire FHWA attribution process is provided along with specifics related to the latest update (2008) on the Off-Highway Gasoline Use Model and the Public Use of Gasoline Model. The Off-Highway Gasoline Use Model is made up of five individual modules, one for each of the off-highway categories: agricultural, industrial and commercial, construction, aviation, and marine. This 2008 update of the off-highway models was the second major update (the first model update was conducted during 2002-2003) after they were originally developed in mid-1990. The agricultural model methodology, specifically, underwent a significant revision because of changes in data availability since 2003. Some revision to the model was necessary due to removal of certain data elements used in the original estimation method. The revised agricultural model also made use of some newly available information, published by the data source agency in recent years. The other model methodologies were not drastically changed, though many data elements were updated to improve the accuracy of these models. Note that components in the Public Use of Gasoline Model were not updated in 2008. A major challenge in updating estimation methods applied by the public-use model is that they would have to rely on significant new data collection efforts. In addition, due to resource limitation, several components of the models (both off-highway and public-us models) that utilized regression modeling approaches were not recalibrated under the 2008 study. An investigation of the Environmental Protection Agency's NONROAD2005 model was also carried out under the 2008 model update. Results generated from the NONROAD2005 model were analyzed, examined, and compared, to the extent that is possible on the overall totals, to the current FHWA estimates. Because NONROAD2005 model was designed for emission estimation purposes (i.e., not for measuring fuel consumption), it covers different equipment populations from those the FHWA models were based on. Thus, a direct comparison generally was not possible in most sectors. As a result, NONROAD2005 data were not used in the 2008 update of the FHWA off-highway models. The quality of fuel use estimates directly affect the data quality in many tables published in the Highway Statistics. Although updates have been made to the Off-Highway Gasoline Use Model and the Public Use Gasoline Model, some challenges remain due to aging model equations and discontinuation of data sources.
Wind Bias from Sub-optimal Estimation Due to Geophysical Modeling Error Paul E. Johnson and David G . Long
Long, David G.
Wind Bias from Sub-optimal Estimation Due to Geophysical Modeling Error -Wind I Paul E. Johnson (which relates the wind to the normalized radar cross section, NRCS, of the ocean surface) is uncertainty in the NRCS for given wind conditions. When the estimated variability is in- cluded in the maximum likelihood
Small-Area Estimation based on Survey Data from a Left-Censored Fay-Herriot Model
Maryland at College Park, University of
Administration's monthly crude oil report is based on a survey (EIA-813, http://www.eiaSmall-Area Estimation based on Survey Data from a Left-Censored Fay-Herriot Model Eric V. Slud, survey estimation. This paper describes research and analysis of its authors, and is released to in- form
Simultaneous state and unknown inputs estimation with PI and PMI observers for Takagi Sugeno model with unmeasurable premise
Paris-Sud XI, Universit� de
Simultaneous state and unknown inputs estimation with PI and PMI observers for Takagi Sugeno model-- In this paper, a proportional integral (PI) and a proportional multiple integral observer (PMI) are proposed and PMI observers developed for linear systems. The state estimation error is written as a perturbed
Evolution of Meteorological Base Models for Estimating Hourly Global Solar Radiation in Texas
Kim, H.; Baltazar, J.C.; Haberl, J.S
ESL-PA-13-11-01 Available online at www.sciencedirect.com Energy Procedia 00 (2013) 000�000 www.elsevier.com/locate/procedia 2013 ISES Solar World Congress Evaluation of Meteorological Base Models... for Estimating Hourly Global Solar Radiation in Texas Kee Han Kima,b*, Juan-Carlos Baltazarb, and Jeff S. Haberla,b aDepartment of Architecture, Texas A&M University, 3137 TAMU, College Station, TX 77843-3137, U.S.A. bEnergy Systems Laboratory, Texas A...
Techno-Economic Models for Carbon Dioxide Compression, Transport, and Storage & Correlations for Estimating Carbon Dioxide Density and Viscosity
McCollum, David L; Ogden, Joan M
Costs to Estimate Hydrogen Pipeline Costs,� UCD-ITS-RR-04-predict the costs of hydrogen pipelines, all of the modelspredict the costs of hydrogen pipelines, all of the models
Information bounds and MCMC parameter estimation for the pile-up model Tabea Rebafkaa,b$, Franois Roueffa, Antoine Souloumiacb
Paris-Sud XI, Universit� de
Information bounds and MCMC parameter estimation for the pile-up model Tabea Rebafkaa,b$, Fran�ois Abstract This paper is concerned with the pile-up model defined as a nonlinear transformation of a distribution of interest. An observation of the pile-up model is the minimum of a random number of independent
686 IEEE TRANSACTIONS ON MAGNETICS, VOL. 44, NO. 6, JUNE 2008 Estimating the Eddy-Current Modeling Error
Rauhut, Holger
686 IEEE TRANSACTIONS ON MAGNETICS, VOL. 44, NO. 6, JUNE 2008 Estimating the Eddy-Current Modeling Zurich, CH-8092 Zürich, Switzerland The eddy-current model is an approximation of the full Maxwell delivers a mathematical basis for assessing the scope of the eddy-current model. Index Terms--Eddy current
Development of a weighted-average estimator from a maximum-likelihood estimator and an instrumental-variable estimator in a structural model
Gruben, David Christopher
, is written as mx y Ab Sou 1hl zz mx x ? Ab?' S?? (3. 2) and we will now spend some time explaining its form. Write a = (1, ? P&) and assume an independent estimator of Z, S?, is avail- able. Fuller (1981) shows that maximizing the likelihood equations... ? z, + u? t = 1, 2, . . . , a?s' = 1, 2, 3, . . . , b? (2. 1c) The total number of observations, n, is equal to a?b?. The experimenter has available an instrumental variable for the unobservable ze =&a+sr&W, +re, t=1, 2, . . . , a?. (2. 1d...
A mathematical model for the estimation of flue temperature in a coke oven
Choi, K.I.; Kim, S.Y.; Suo, J.S.; Hur, N.S.; Kang, I.S.; Lee, W.J.
The coke plants at the Kwangyang works has adopted an Automatic Battery Control (ABC) system which consists of four main parts, battery heating control, underfiring heat and waste gas oxygen control, pushing and charging schedule and Autotherm-S that measures heating wall temperature during pushing. The measured heating wall temperature is used for calculating Mean Battery Temperature (MBT) which is average temperature of flues for a battery, but the Autotherm-S system can not provide the flue temperatures of an oven. This work attempted to develop mathematical models for the estimation of the flue temperature using the measured heating wall temperature and to examine fitness of the mathematical model for the coke plant operation by analysis of raw gas temperature at the stand pipe. Through this work it is possible to reflect heating wall temperature in calculating MBT for battery heating control without the interruption caused by a maintenance break.
Estimating Reaction Rate Coefficients Within a Travel-Time Modeling Framework
Gong, R [Georgia Institute of Technology; Lu, C [Georgia Institute of Technology; Luo, Jian [Georgia Institute of Technology; Wu, Wei-min [Stanford University; Cheng, H. [Stanford University; Criddle, Craig [Stanford University; Kitanidis, Peter K. [Stanford University; Gu, Baohua [ORNL; Watson, David B [ORNL; Jardine, Philip M [ORNL; Brooks, Scott C [ORNL
A generalized, efficient, and practical approach based on the travel-time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel-time distribution from the injection point to the observation point. For advection-dominant reactive transport with well-mixed reactive species and a constant travel-time distribution, the reactive BTC is obtained by integrating the solutions to advective-reactive transport over the entire travel-time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero-, first-, nth-order, and Michaelis-Menten reactions. The proposed approach is validated by a reactive transport case in a two-dimensional synthetic heterogeneous aquifer and a field-scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)-bioremediation is better approximated by zero-order reaction kinetics than first-order reaction kinetics.
Novel Method for Incorporating Model Uncertainties into Gravitational Wave Parameter Estimates
Christopher J. Moore; Jonathan R. Gair
Posterior distributions on parameters computed from experimental data using Bayesian techniques are only as accurate as the models used to construct them. In many applications these models are incomplete, which both reduces the prospects of detection and leads to a systematic error in the parameter estimates. In the analysis of data from gravitational wave detectors, for example, accurate waveform templates can be computed using numerical methods, but the prohibitive cost of these simulations means this can only be done for a small handful of parameters. In this work a novel method to fold model uncertainties into data analysis is proposed; the waveform uncertainty is analytically marginalised over using with a prior distribution constructed by using Gaussian process regression to interpolate the waveform difference from a small training set of accurate templates. The method is well motivated, easy to implement, and no more computationally expensive than standard techniques. The new method is shown to perform extremely well when applied to a toy problem. While we use the application to gravitational wave data analysis to motivate and illustrate the technique, it can be applied in any context where model uncertainties exist.
Efficient Semiparametric Estimators for Nonlinear Regressions and Models under Sample Selection Bias
Kim, Mi Jeong
. Overview of Semiparametric Theory . . . . . . . . . . . . . 2 B. The Second-order Least Squares Estimator . . . . . . . . . 3 C. Sample Selection Bias . . . . . . . . . . . . . . . . . . . . . 4 II THE EFFICIENCY OF THE SECOND-ORDER NONLIN- EAR LEAST... . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1. Semiparametric Derivation . . . . . . . . . . . . . . . 24 2. Robust Estimation Family . . . . . . . . . . . . . . . 25 3. E cient Estimation . . . . . . . . . . . . . . . . . . . 29 4. Population Density Estimation...
CLEAR (Calculates Logical Evacuation And Response): A Generic Transportation Network Model for the Calculation of Evacuation Time Estimates
Moeller, M. P.; Urbanik, II, T.; Desrosiers, A. E.
This paper describes the methodology and application of the computer model CLEAR (Calculates Logical Evacuation And Response) which estimates the time required for a specific population density and distribution to evacuate an area using a specific transportation network. The CLEAR model simulates vehicle departure and movement on a transportation network according to the conditions and consequences of traffic flow. These include handling vehicles at intersecting road segments, calculating the velocity of travel on a road segment as a function of its vehicle density, and accounting for the delay of vehicles in traffic queues. The program also models the distribution of times required by individuals to prepare for an evacuation. In order to test its accuracy, the CLEAR model was used to estimate evacuatlon tlmes for the emergency planning zone surrounding the Beaver Valley Nuclear Power Plant. The Beaver Valley site was selected because evacuation time estimates had previously been prepared by the licensee, Duquesne Light, as well as by the Federal Emergency Management Agency and the Pennsylvania Emergency Management Agency. A lack of documentation prevented a detailed comparison of the estimates based on the CLEAR model and those obtained by Duquesne Light. However, the CLEAR model results compared favorably with the estimates prepared by the other two agencies.
An image-based four-source surface energy balance model to estimate crop evapotranspiration from solar
Boyer, Edmond
An image-based four-source surface energy balance model to estimate crop evapotranspiration from solar reflectance/thermal emission data (SEB-4S) Olivier Merlin,a , Jonas Chirouzea , Albert Oliosob, 84000 Avignon, France Abstract A remote sensing-based surface energy balance model is developed
Variation in Estimated Ozone-Related Health Impacts of Climate Change due to Modeling Choices and Assumptions
Post, Ellen S.; Grambsch, A.; Weaver, C. P.; Morefield, Philip; Huang, Jin; Leung, Lai-Yung R.; Nolte, Christopher G.; Adams, P. J.; Liang, Xin-Zhong; Zhu, J.; Mahoney, Hardee
Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices.
RSMASS-D models: An improved method for estimating reactor and shield mass for space reactor applications
Marshall, A.C.
Three relatively simple mathematical models have been developed to estimate minimum reactor and radiation shield masses for liquid-metal-cooled reactors (LMRs), in-core thermionic fuel element (TFE) reactors, and out-of-core thermionic reactors (OTRs). The approach was based on much of the methodology developed for the Reactor/Shield Mass (RSMASS) model. Like the original RSMASS models, the new RSMASS-derivative (RSMASS-D) models use a combination of simple equations derived from reactor physics and other fundamental considerations, along with tabulations of data from more detailed neutron and gamma transport theory computations. All three models vary basic design parameters within a range specified by the user to achieve a parameter choice that yields a minimum mass for the power level and operational time of interest. The impact of critical mass, fuel damage, and thermal limitations are accounted for to determine the required fuel mass. The effect of thermionic limitations are also taken into account for the thermionic reactor models. All major reactor component masses are estimated, as well as instrumentation and control (I&C), boom, and safety system masses. A new shield model was developed and incorporated into all three reactor concept models. The new shield model is more accurate and simpler to use than the approach used in the original RSMASS model. The estimated reactor and shield masses agree with the mass predictions from separate detailed calculations within 15 percent for all three models.
Adaptive nonparametric estimation in heteroscedastic regression models. Part 1: Sharp non-asymptotic Oracle inequalities
Galtchouk, Leonid
An adaptive nonparametric estimation procedure is constructed for the estimation problem of heteroscedastic regression when the noise variance depends on the unknown regression. A non-asymptotic upper bound for a quadratic risk (an oracle inequality) is constructed.
Complexity penalized hydraulic fracture localization and moment tensor estimation under limited model information
Ely, Gregory
In this paper we present a novel technique for micro-seismic localization using a group sparse penalization that is robust to the focal mechanism of the source and requires only a velocity model of the stratigraphy rather than a full Green's function model of the earth's response. In this technique we construct a set of perfect delta detector responses, one for each detector in the array, to a seismic event at a given location and impose a group sparsity across the array. This scheme is independent of the moment tensor and exploits the time compactness of the incident seismic signal. Furthermore we present a method for improving the inversion of the moment tensor and Green's function when the geometry of seismic array is limited. In particular we demonstrate that both Tikhonov regularization and truncated SVD can improve the recovery of the moment tensor and be robust to noise. We evaluate our algorithm on synthetic data and present error bounds for both estimation of the moment tensor as well as localization...
ARM Climate Modeling Best Estimate Data, A New Data Product for Climate Studies
Xie, Shaocheng [Lawrence Livermore National Laboratory (LLNL); McCoy, Renata B. [Lawrence Livermore National Laboratory (LLNL); Klein, Stephen A. [Lawrence Livermore National Laboratory (LLNL); Cederwall, Richard T. [Lawrence Livermore National Laboratory (LLNL); Wiscombe, Warren J. [Brookhaven National Laboratory (BNL); Clothiaux, Eugene E. [Pennsylvania State University, University Park, PA; Gaustad, Krista L. [Pacific Northwest National Laboratory (PNNL); Golaz, Jean-Christophe [NOAA Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ; Shamblin, Stefanie H [ORNL; Jensen, Michael P. [Brookhaven National Laboratory (BNL); Johnson, Karen L. [Brookhaven National Laboratory (BNL); Lin, Yanluan [NOAA Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ; Long, Charles N. [Pacific Northwest National Laboratory (PNNL); Mather, James H. [Pacific Northwest National Laboratory (PNNL); McCord, Raymond A [ORNL; McFarlane, Sally A. [Pacific Northwest National Laboratory (PNNL); Palanisamy, Giri [ORNL; Shi, Yan [Pacific Northwest National Laboratory (PNNL); Turner, David D. [University of Wisconsin, Madison
The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation in the atmosphere. A central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement. Since 1992, ARM has established six permanent ARM Climate Research Facility (ACRF) sites and deployed an ARM Mobile Facility (AMF) in diverse climate regimes around the world (Fig. 1) to perform long-term continuous field measurements. The time record of ACRF data now exceeds a decade at most ACRF fixed sites and ranges from several months to one year for AMF deployments. Billions of measurements are currently stored in millions of data files in the ACRF Data Archive. The long-term continuous ACRF data provide invaluable information to improve our understanding of the interaction between clouds and radiation, and an observational basis for model validation and improvement and climate studies. Given the huge number of data files and current diversity of archived ACRF data structures, however, it can be difficult for an outside user such as a climate modeler to quickly find the ACRF data product(s) that best meets their research needs. The required geophysical quantities may exist in multiple data streams, and over the history of ACRF operations, the measurements could be obtained by a variety of instruments, reviewed with different levels of data quality assurance, or derived using different algorithms. In addition, most ACRF data are stored in daily-based files with a temporal resolution that ranges from a few seconds to a few minutes, which is much finer than that sought by some users. Therefore, it is not as convenient for data users to perform quick comparisons over large spans of data, and this can hamper the use of ACRF data by the climate community. To make ACRF data better serve the needs of climate studies and model development, ARM has developed a data product specifically tailored for use by the climate community. The new data product, named the Climate Modeling Best Estimate (CMBE) dataset, assembles those quantities that are both well observed by ACRF over many years and are often used in model evaluation into one single dataset. The CMBE product consists of hourly averages and thus has temporal resolution comparable to a typical resolution used in climate model output. It also includes standard deviations within the averaged hour and quality control flags for the selected quantities to indicate the temporal variability and data quality. Since its initial release in February 2008, the new data product has quickly drawn the attention of the climate modeling community. It is being used for model evaluation by two major U.S. climate modeling centers, the National Center for Atmospheric Research (NCAR) and the Geophysical Fluid Dynamics Laboratory (GFDL). The purpose of this paper is to provide an overview of CMBE data and a few examples that demonstrate the potential value of CMBE data for climate modeling and in studies of cloud processes and climate variability and change.
Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States
Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, N.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen
Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469�687 g C m?2 yr?1 and total NPP in the range of 318�490 Tg C yr?1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m?2 yr?1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m?2 yr?1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species�specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.
A simplified model for estimating population-scale energy impacts of building envelope air-tightening and mechanical ventilation retrofits
Logue, J. M.; Turner, W. J.N.; Walker, I. S.; Singer, B. C.
Changing the air exchange rate of a home (the sum of the infiltration and mechanical ventilation airflow rates) affects the annual thermal conditioning energy. Large-scale changes to air exchange rates of the housing stock can significantly alter the residential sector's energy consumption. However, the complexity of existing residential energy models is a barrier to the accurate quantification of the impact of policy changes on a state or national level. The Incremental Ventilation Energy (IVE) model developed in this study combines the output of simple air exchange models with a limited set of housing characteristics to estimate the associated change in energy demand of homes. The IVE model was designed specifically to enable modellers to use existing databases of housing characteristics to determine the impact of ventilation policy change on a population scale. The IVE model estimates of energy change when applied to US homes with limited parameterisation are shown to be comparable to the estimates of a well-validated, complex residential energy model.
Estimating present climate in a warming world: a model-based approach
Raeisaenen, J.; Ruokolainen, L. [University of Helsinki (Finland). Division of Atmospheric Sciences and Geophysics
Weather services base their operational definitions of 'present' climate on past observations, using a 30-year normal period such as 1961-1990 or 1971-2000. In a world with ongoing global warming, however, past data give a biased estimate of the actual present-day climate. Here we propose to correct this bias with a 'delta change' method, in which model-simulated climate changes and observed global mean temperature changes are used to extrapolate past observations forward in time, to make them representative of present or future climate conditions. In a hindcast test for the years 1991-2002, the method works well for temperature, with a clear improvement in verification statistics compared to the case in which the hindcast is formed directly from the observations for 1961-1990. However, no improvement is found for precipitation, for which the signal-to-noise ratio between expected anthropogenic changes and interannual variability is much lower than for temperature. An application of the method to the present (around the year 2007) climate suggests that, as a geographical average over land areas excluding Antarctica, 8-9 months per year and 8-9 years per decade can be expected to be warmer than the median for 1971-2000. Along with the overall warming, a substantial increase in the frequency of warm extremes at the expense of cold extremes of monthly-to-annual temperature is expected.
Unbiased Estimation of Reliability in StressStrength Model and Similar Problems
Petersburg, Russia VASSILY G. VOINOV Kazakhstan Institute of Management, Economics and Strategic Research, Almaty, Kazakhstan Abstract: Some problems related to an application of the unbiased estimators
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. ???, XXXX, DOI:10.1029/, Efficient stochastic estimation of the model resolution1
Borchers, Brian
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. ???, XXXX, DOI:10.1029/, Efficient stochastic estimation of the model resolution1 matrix diagonal and generalized crossvalidation for2 large geophysical inverse and Environmental Science and Geophysical Research Cen- ter, New Mexico Institute of Mining and Technology, 801
Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model
Martin, Timothy
using Advanced Very High Res- olution Radiometer Lai data, Climate Research Unit climate dataGlobal estimation of evapotranspiration using a leaf area index-based surface energy and water-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balance
Lithium-Ion battery State of Charge estimation with a Kalman Filter based on a electrochemical model
Stefanopoulou, Anna
Lithium-Ion battery State of Charge estimation with a Kalman Filter based on a electrochemical model Domenico Di Domenico, Giovanni Fiengo and Anna Stefanopoulou Abstract-- Lithium-ion battery hybrid electric vehicles (HEV). In most cases the lithium-ion battery performance plays an important role
Speech Enhancement of Spectral Magnitude Bin Trajectories using Gaussian Mixture-Model based Minimum Mean-Square Error Estimators
Speech Enhancement of Spectral Magnitude Bin Trajectories using Gaussian Mixture-Model based mean-square error es- timators have been applied to speech enhancement in the tem- poral, transform (e estimator for 8 kHz telephone-quality speech. Index Terms: Speech enhancement, minimum mean-square er- ror
Stefanopoulou, Anna
ESTIMATION OF ETHANOL CONTENT IN FLEX-FUEL VEHICLES USING AN EXHAUST GAS OXYGEN SENSOR: MODEL periods of intense interest in using ethanol as an alternative fuel to petroleum-based gasoline and diesel derivatives. Currently available flexible fuel vehicles (FFVs) can operate on a blend of gasoline and ethanol
Modelling downstream change in river flood power: a novel approach based on the UK Flood Estimation Handbook
Birmingham, University of
Modelling downstream change in river flood power: a novel approach based on the UK Flood Estimation" (McEwen, 1994: 359). Lawler (1992) recognised that little was known about the downstream change. It is suggested that downstream change in discharge is best represented as a power function in terms of channel
Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration
Hollinger, D. [USDA Forest Service; Ollinger, S. V. [University of Hew Hampshire; Richardson, A. D. [University of Hew Hampshire; Martin, M. E. [University of New Hampshire; Meyers, T. P. [NOAA ATDD; Dail, D. B. [University of Maine; Scott, N. A. [Queens University, Kingston, ON, Canada; Arkebauer, T. J. [University of Nebraska, Lincoln; Baldocchi, D. D. [University of California, Berkeley; Clark, K. L. [USDA Forest Service; Curtis, Peter [Ohio State University, The, Columbus; Davis, K. J. [Pennsylvania State University; Desai, Desai Ankur R. [University of Wisconsin, Madison; Dragoni, Danilo [Indiana University; Goulden, M. L. [University of California, Irvine; Gu, Lianhong [ORNL; Katul, G. G. [Duke University; Pallardy, Stephen G. [University of Missouri; Pawu, K. T. [University of California, Davis; Schmid, H. P. [IFU, FZK IMK, Institute of Meteorology & Climate, Garmisch Partenkirchen, Germany; Stoy, P. C. [University of Edinburgh; Suyker, A. E. [University of Nebraska, Lincoln; Verma, Shashi [University of Nebraska
Vegetation albedo is a critical component of the Earth s climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site-years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climatemodels that rely on a common two-stream albedo submodel provided accurate predictions of boreal needle-leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two-stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration (for forest vegetation: albedo 50.0110.071%N, r250.91; forests, grassland, and maize: albedo50.0210.067%N, r250.80). However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two-stream albedo model and foliage nitrogen concentration. These nitrogen-based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes.
Biometrics 000, 124 DOI: 000 A Bayesian localised conditional autoregressive model for estimating the health
Sahu, Sujit K
for estimating the health effects of air pollution Duncan Lee1, , Alastair Rushworth1 and Sujit K. Sahu2 . email@example.com Summary: Estimation of the long-term health effects of air pollution is a challenging task, especially effects confound the effects of air pollution, which are also globally smooth. To avoid this collinearity
Convolution particle filtering for parameter estimation in general state-space models
Paris-Sud XI, Université de
of these aspects [6] [4]. The second approach takes place in a classical Bayesian framework, a prior probability suited, given the context of parameter estimation. Firstly the usual non Bayesian statistical estimates results in practice but suffer from an absence of theoretical backing. The particle filters propose a good
Melanoma costs: A dynamic model comparing estimated overall costs of various clinical stages
Alexandrescu, Doru Traian
AL. Trends in treatment costs for localized prostate cancer:R, Elkin EP, et al. Cumulative cost pattern comparison ofAn estimate of the annual direct cost of treating cutaneous
Seager, Sara
Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry ...
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC3)
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-ATM SGPC1)
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4)
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC3)
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC2)
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Manus Island, PNG (ARMBE-ATM TWPC1)
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-ATM SGPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Manus Island, PNG (ARMBE-ATM TWPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC3)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC2)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Nauru (ARMBE-ATM TWPC2)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
Efficient Hydraulic State Estimation Technique Using Reduced Models of Urban Water Networks
Preis, Ami
This paper describes and demonstrates an efficient method for online hydraulic state estimation in urban water networks. The proposed method employs an online predictor-corrector (PC) procedure for forecasting future water ...
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC2 V2.1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-CLDRAD SGPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC3)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC2)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-CLDRAD NSAC1 V2.1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-CLDRAD SGPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-CLDRAD [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected cloud and radiation relevant quantities from ACRF observations
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-CLDRAD NSAC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
Load Modeling and State Estimation Methods for Power Distribution Systems: Final Report
Tom McDermott
The project objective was to provide robust state estimation for distribution systems, comparable to what has been available on transmission systems for decades. This project used an algorithm called Branch Current State Estimation (BCSE), which is more effective than classical methods because it decouples the three phases of a distribution system, and uses branch current instead of node voltage as a state variable, which is a better match to current measurement.
A Probabilistic Deformation Demand Model and Fragility Estimates for Asymmetric Offshore Jacket Platforms
Fallon, Michael Brooks
to assess the deformation demand on asymmetric offshore jacket platforms subject to wave and current loadings. The probabilistic model is constructed by adding correction terms and a model error to an existing deterministic deformation demand model...
WAXS fat subtraction model to estimate differential linear scattering coefficients of fatless breast tissue: Phantom materials evaluation
Tang, Robert Y., E-mail: firstname.lastname@example.com [Biomolecular Sciences Program, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada); Laamanen, Curtis, E-mail: firstname.lastname@example.com; McDonald, Nancy, E-mail: email@example.com [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada)] [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada); LeClair, Robert J., E-mail: email@example.com [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6, Canada and Biomolecular Sciences Program, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada)
Purpose: Develop a method to subtract fat tissue contributions to wide-angle x-ray scatter (WAXS) signals of breast biopsies in order to estimate the differential linear scattering coefficients ?{sub s} of fatless tissue. Cancerous and fibroglandular tissue can then be compared independent of fat content. In this work phantom materials with known compositions were used to test the efficacy of the WAXS subtraction model. Methods: Each sample 5 mm in diameter and 5 mm thick was interrogated by a 50 kV 2.7 mm diameter beam for 3 min. A 25 mm{sup 2} by 1 mm thick CdTe detector allowed measurements of a portion of the ? = 6� scattered field. A scatter technique provided means to estimate the incident spectrum N{sub 0}(E) needed in the calculations of ?{sub s}[x(E, ?)] where x is the momentum transfer argument. Values of ?{sup �}{sub s} for composite phantoms consisting of three plastic layers were estimated and compared to the values obtained via the sum ?{sup �}{sub s}{sup ?}(x)=?{sub 1}?{sub s1}(x)+?{sub 2}?{sub s2}(x)+?{sub 3}?{sub s3}(x), where ?{sub i} is the fractional volume of the ith plastic component. Water, polystyrene, and a volume mixture of 0.6 water + 0.4 polystyrene labelled as fibphan were chosen to mimic cancer, fat, and fibroglandular tissue, respectively. A WAXS subtraction model was used to remove the polystyrene signal from tissue composite phantoms so that the ?{sub s} of water and fibphan could be estimated. Although the composite samples were layered, simulations were performed to test the models under nonlayered conditions. Results: The well known ?{sub s} signal of water was reproduced effectively between 0.5 < x < 1.6 nm{sup ?1}. The ?{sup �}{sub s} obtained for the heterogeneous samples agreed with ?{sup �}{sub s}{sup ?}. Polystyrene signals were subtracted successfully from composite phantoms. The simulations validated the usefulness of the WAXS models for nonlayered biopsies. Conclusions: The methodology to measure ?{sub s} of homogeneous samples was quantitatively accurate. Simple WAXS models predicted the probabilities for specific x-ray scattering to occur from heterogeneous biopsies. The fat subtraction model can allow ?{sub s} signals of breast cancer and fibroglandular tissue to be compared without the effects of fat provided there is an independent measurement of the fat volume fraction ?{sub f}. Future work will consist of devising a quantitative x-ray digital imaging method to estimate ?{sub f} in ex vivo breast samples.
~ is illustrated by developing a model that makes monthly forecasts of skipjack tuna, Katsuwonus pelamis, catches
OptIC project: An intercomparison of optimization techniques for parameter estimation in terrestrial biogeochemical models
Richardson, Andrew D.
and earth system models, especially for long-term (multian- nual and greater) simulations. Data assimilation
A depth-derived Pleistocene age model: Uncertainty estimates, sedimentation variability, and nonlinear climate change
Huybers, Peter
Geology and Geophysics: Geomagnetism (1550); 3220 Mathematical Geophysics: Nonlinear dynamics; 4267 of ages to measurements and events recorded in marine and ice cores as well as to a variety of isolated. [3] The currently favored method for estimating Pleisto- cene age is orbital tuning [e.g., Imbrie et
A Robust Nonparametric Estimation Framework for Implicit Image Models Himanshu Arora Maneesh Singh Narendra Ahuja
Ahuja, Narendra
Narendra Ahuja University of Illinois Siemens Corporate Research University of Illinois Urbana, IL61801, USA Princeton, NJ08540, USA Urbana, IL61801, USA email@example.com email@example.com n- clidian, affine, or projective transformations; surface normal and curvature estimation for 3D structure
Global oceanic rainfall estimation from AMSR-E data based on a radiative transfer model
Jin, Kyoung-Wook
retrieval uncertainties. The algorithm uses six channels (dual polarizations at 36.5, 18.7 and 10.65GHz) and retrieves rain rates on a pixel-by-pixel basis. Monthly rain totals are estimated by summing average rain rates computed by merging six rain rates...
Estimating the Partition Function of Graphical Models Using Langevin Importance Sampling
Xu, Jinbo
equation and estimates the partition function using all the samples generated during the random walk at all long time for MCMC sampling to reach the detailed balance equilib- rium. Further, no simple methods, inspired by the obser- vation that if a liquid material cools very quickly, the material will solidify
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model
Adler, Joan
High and Low Temperature Series Estimates for the Critical Temperature Abstract We have analysed low and high temperature series expansions for the three high temperature series yields Kc = 0.221659 +0.000002-0.000005and from the 32 term low
PEAS: A toolbox to assess the accuracy of estimated parameters in environmental models
Checchi, Elisabetta Giusti, Stefano Marsili-Libelli* Department of Systems and Computers, University, in addition to parameter estimation, such as error function plotting, trajectory sensitivity, Monte Carlo regions are computed and a confidence test is pro- duced. The Monte Carlo analysis is available
Improving parameter estimation and water table depth simulation in a land surface model using GRACE water storage and estimated base flow data
Lo, Min-Hui; Famiglietti, James S; Yeh, P. J.-F.; Syed, T. H
2007), Estimating ground water storage changes in thestorage (i.e. , all of the snow, ice, surface water, soil moisture, and ground-
Estimates of Radioxenon Released from Southern Hemisphere Medical isotope Production Facilities Using Measured Air Concentrations and Atmospheric Transport Modeling
Eslinger, Paul W.; Friese, Judah I.; Lowrey, Justin D.; McIntyre, Justin I.; Miley, Harry S.; Schrom, Brian T.
Abstract The International Monitoring System (IMS) of the Comprehensive-Nuclear-Test-Ban-Treaty monitors the atmosphere for radioactive xenon leaking from underground nuclear explosions. Emissions from medical isotope production represent a challenging background signal when determining whether measured radioxenon in the atmosphere is associated with a nuclear explosion prohibited by the treaty. The Australian Nuclear Science and Technology Organisation (ANSTO) operates a reactor and medical isotope production facility in Lucas Heights, Australia. This study uses two years of release data from the ANSTO medical isotope production facility and Xe-133 data from three IMS sampling locations to estimate the annual releases of Xe-133 from medical isotope production facilities in Argentina, South Africa, and Indonesia. Atmospheric dilution factors derived from a global atmospheric transport model were used in an optimization scheme to estimate annual release values by facility. The annual releases of about 6.8�1014 Bq from the ANSTO medical isotope production facility are in good agreement with the sampled concentrations at these three IMS sampling locations. Annual release estimates for the facility in South Africa vary from 1.2�1016 to 2.5�1016 Bq and estimates for the facility in Indonesia vary from 6.1�1013 to 3.6�1014 Bq. Although some releases from the facility in Argentina may reach these IMS sampling locations, the solution to the objective function is insensitive to the magnitude of those releases.
Developing a Cost Model and Methodology to Estimate Capital Costs for Thermal Energy Storage
Glatzmaier, G.
This report provides an update on the previous cost model for thermal energy storage (TES) systems. The update allows NREL to estimate the costs of such systems that are compatible with the higher operating temperatures associated with advanced power cycles. The goal of the Department of Energy (DOE) Solar Energy Technology Program is to develop solar technologies that can make a significant contribution to the United States domestic energy supply. The recent DOE SunShot Initiative sets a very aggressive cost goal to reach a Levelized Cost of Energy (LCOE) of 6 cents/kWh by 2020 with no incentives or credits for all solar-to-electricity technologies.1 As this goal is reached, the share of utility power generation that is provided by renewable energy sources is expected to increase dramatically. Because Concentrating Solar Power (CSP) is currently the only renewable technology that is capable of integrating cost-effective energy storage, it is positioned to play a key role in providing renewable, dispatchable power to utilities as the share of power generation from renewable sources increases. Because of this role, future CSP plants will likely have as much as 15 hours of Thermal Energy Storage (TES) included in their design and operation. As such, the cost and performance of the TES system is critical to meeting the SunShot goal for solar technologies. The cost of electricity from a CSP plant depends strongly on its overall efficiency, which is a product of two components - the collection and conversion efficiencies. The collection efficiency determines the portion of incident solar energy that is captured as high-temperature thermal energy. The conversion efficiency determines the portion of thermal energy that is converted to electricity. The operating temperature at which the overall efficiency reaches its maximum depends on many factors, including material properties of the CSP plant components. Increasing the operating temperature of the power generation system leads to higher thermal-to-electric conversion efficiency. However, in a CSP system, higher operating temperature also leads to greater thermal losses. These two effects combine to give an optimal system-level operating temperature that may be less than the upper operating temperature limit of system components. The overall efficiency may be improved by developing materials, power cycles, and system-integration strategies that enable operation at elevated temperature while limiting thermal losses. This is particularly true for the TES system and its components. Meeting the SunShot cost target will require cost and performance improvements in all systems and components within a CSP plant. Solar collector field hardware will need to decrease significantly in cost with no loss in performance and possibly with performance improvements. As higher temperatures are considered for the power block, new working fluids, heat-transfer fluids (HTFs), and storage fluids will all need to be identified to meet these new operating conditions. Figure 1 shows thermodynamic conversion efficiency as a function of temperature for the ideal Carnot cycle and 75% Carnot, which is considered to be the practical efficiency attainable by current power cycles. Current conversion efficiencies for the parabolic trough steam cycle, power tower steam cycle, parabolic dish/Stirling, Ericsson, and air-Brayton/steam Rankine combined cycles are shown at their corresponding operating temperatures. Efficiencies for supercritical steam and carbon dioxide (CO{sub 2}) are also shown for their operating temperature ranges.
Evaluation of the Effective Moisture Penetration Depth Model for Estimating Moisture Buffering in Buildings
Woods, J.; Winkler, J.; Christensen, D.
This study examines the effective moisture penetration depth (EMPD) model, and its suitability for building simulations. The EMPD model is a compromise between the simple, inaccurate effective capacitance approach and the complex, yet accurate, finite-difference approach. Two formulations of the EMPD model were examined, including the model used in the EnergyPlus building simulation software. An error in the EMPD model we uncovered was fixed with the release of EnergyPlus version 7.2, and the EMPD model in earlier versions of EnergyPlus should not be used.
Enterprise Lead Input and Tracking Environment This tool solves the problem of tracking sales leads in a closed loop fashion, as depicted
Fisher, Kathleen
ELITE Enterprise Lead Input and Tracking Environment This tool solves the problem of tracking sales leads in a closed loop fashion, as depicted in the figure below, in a simple and novel fashion, in a web handles a variety of tasks, such as lead evaluation, lead scoring, lead distribution, alerting, reporting
Bayesian Estimation of a Continuous-Time Model for Discretely-Observed Panel Data
Boulton, Aaron Jacob
Continuous-time models are used in many areas of science. However, in psychology and related fields, continuous-time models are often difficult to apply because only a small number of repeated observations are typically ...
Global oceanic rainfall estimation from AMSR-E data based on a radiative transfer model�
Jin, Kyoung-Wook
An improved physically-based rainfall algorithm was developed using AMSR-E data based on a radiative transfer model. In addition, error models were designed and embedded in the algorithm to assess retrieval errors ...
CITPUFF: a gaussian puff model for estimating pollutant concentration in complex terrain. Forest Service research paper
Ross, D.G.; Fox, D.G.; Dietrich, D.L.; Childs, J.E.; Marlatt, W.E.
CITPUFF, is a puff-type dispersion model that uses a wind field calculated from a complex-terrain wind model. It accommodates a variety of source types including point, area, and line sources; calculates plume rise where applicable; and outputs a graphic display of puff trajectories and concentrations. The model is compared against models currently used for assessing air quality impacts in complex topography.
Fracture Density Estimation Using Spectral Analysis of Reservoir Reflections: A Numerical Modeling Approach
Pearce, Fred
We use a 3-D finite difference numerical model to generate synthetic seismograms from a simple fractured reservoir
Atmospheric Environment 39 (2005) 13731382 A hierarchical Bayesian model to estimate and forecast ozone
Irwin, Mark E.
reserved. Keywords: Statistical model; Space�time models; Air pollution; Ozone; Meteorology 1. Introduction describing the spatial�temporal behavior of ambient air pollutants such as ozone (O3) and particulate matter. Statistical space�time models are useful for illuminating relationships between different air pollutants
Parameter Estimation and Model Discrimination for a Lithium-Ion Cell
interest in the modeling of the lithium-ion battery ever since this battery was first com- mercialized.1-18 This interest has been fueled by the combination of the fast growing lithium-ion battery market and the desire of a lithium- ion battery measured over a wide range of rates. Single-Particle Model This single-particle model
Accurate Online Power Estimation and Automatic Battery Behavior Based Power Model Generation for Smartphones
Tomkins, Andrew
of Systems]: Modeling techniques General Terms Measurement, Design Keywords Power modeling, mobile phones systems. Combined, PowerBooter and PowerTutor have the goal of opening power modeling and analysis of determining the impact of software design decisions on system energy consumption, but that barrier can
Estimates for temperature in projectile like fragment in geometric and transport models
Mallik, S; Chaudhuri, G
Projectile like fragments emerging from heavy ion collision have an excitation energy which is often labeled by a temperature. This temperature was recently calculated using a geometric model. We expand the geometric model to include also dynamic effects using a transport model. The temperatures so deduced agree quite well with values of temperature needed to fit experimental data.
Fractal model for estimating fracture toughness of carbon nanotube reinforced aluminum oxide
Rishabh, Abhishek; Joshi, Milind R.; Balani, Kantesh [Department of Materials and Metallurgical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India)
The current work focuses on predicting the fracture toughness of Al{sub 2}O{sub 3} ceramic matrix composites using a modified Mandelbrot's fractal approach. The first step confirms that the experimental fracture toughness values fluctuate within the fracture toughness range predicted as per the modified fractal approach. Additionally, the secondary reinforcements [such as carbon nanotubes (CNTs)] have shown to enhance the fracture toughness of Al{sub 2}O{sub 3}. Conventional fractural toughness evaluation via fractal approach underestimates the fracture toughness by considering the shortest crack path. Hence, the modified Mandelbrot's fractal approach considers the crack propagation along the CNT semicircumferential surface (three-dimensional crack path propagation) for achieving an improved fracture toughness estimation of Al{sub 2}O{sub 3}-CNT composite. The estimations obtained in the current approach range within 4% error regime of the experimentally measured fracture toughness values of the Al{sub 2}O{sub 3}-CNT composite.
Development of a mass balance model for estimating PCB export from the lower Fox River to Green Bay
Velleux, M.; Endicott, D.
A mass balance approach was used to model contaminant cycling in the lower Fox River from the DePere Dam to Green Bay. The objectives of this research were (1) to estimate present contaminant export from the Fox River to Green Bay, and (2) to quantify contaminant transport and fate pathways in the lower river for the study period. Specifically, a model describing the transport, fate, and export of chlorides, total suspended solids, total PCBs, and six PCB congeners for the lower Fox River was developed. Field data collected as part of the U.S. Environmental Protection Agency's Green Bay Mass Balance Study were used to calibrate the model. Model results suggest that the transport of inplace pollutants significantly contributed to the cumulative export of total PCBs over this period. Estimated total PCB transport in the Fox River during 1989 increased 60% between the dam and river mouth due to the resuspension of lower river sediments. Total suspended solids and PCB predictions are most sensitive to particle transport parameters, particularly the settling and resuspension velocities. The significant components of the total PCB mass balance are import (loading over the DePere Dam), settling, resuspension, and export to Green Bay. Volatilization, porewater transport, and point source input were not significant to the mass balance. Present point source discharges to the river are not significant total PCB sources, collectively contributing less than 6 kg of PCB to the river during the mass balance period.
Estimating market power in homogeneous product markets using a composed error model
Orea, Luis; Steinbuks, Jevgenijs
(frequent). In other markets all firms might be involved in perfect cartel scheme. In such a cartel-equilibrium, firms usually agree to sell �target� quantities, and the resulting market price is the monopoly price, which is associated with the maximum... ) and Clay and Troesken (2003) for applications to the sugar and whiskey industries respectively. EPRG WP 1210 7 correlation between Lerner indices and estimated conduct parameters for 3 out of 4 firms during the first period of our sample (before entry...
Bi-factor Multidimensional Item Response Theory Modeling for Subscores Estimation, Reliability, and Classification
Md Desa, Zairul Nor Deana
, test linking, equating and scaling (Kolen & Brennan, 2004), item banking, computer-based testing and computerized adaptive testing (Dras- gow & Olson-Buchanan, 1999; Mills et al., 2002; Parshall et al., 2001; van der Linden & Glas, 2000; Wainer & Dorans... decisions at student and school-level decisions (Sinharay et al., 2007; Haberman, 2008; Haberman et al., 2009; Puhan et al., 2010). The application of Bayesian approach has shown improved reliability of the overall score or subscores estimates (Kolen & Tong...
Estimation of Inflation parameters for Perturbed Power Law model using recent CMB measurements
Suvodip Mukherjee; Santanu Das; Minu Joy; Tarun Souradeep
Cosmic Microwave Background (CMB) is an important probe for understanding the inflationary era of the Universe. We consider the Perturbed Power Law (PPL) model of inflation which is a soft deviation from Power Law (PL) inflationary model. This model captures the effect of higher order derivative of Hubble parameter during inflation, which in turn leads to a non-zero effective mass $m_{\\rm eff}$ for the inflaton field. The higher order derivatives of Hubble parameter at leading order sources constant difference in the spectral index for scalar and tensor perturbation going beyond PL model of inflation. PPL model have two observable independent parameters, namely spectral index for tensor perturbation $\
Estimation of Inflation parameters for Perturbed Power Law model using recent CMB measurements
Mukherjee, Suvodip; Joy, Minu; Souradeep, Tarun
Cosmic Microwave Background (CMB) is an important probe for understanding the inflationary era of the Universe. We consider the Perturbed Power Law (PPL) model of inflation which is a soft deviation from Power Law (PL) inflationary model. This model captures the effect of higher order derivative of Hubble parameter during inflation, which in turn leads to a non-zero effective mass $m_{\\rm eff}$ for the inflaton field. The higher order derivatives of Hubble parameter at leading order sources constant difference in the spectral index for scalar and tensor perturbation going beyond PL model of inflation. PPL model have two observable independent parameters, namely spectral index for tensor perturbation $\
Evaluation of Blade-Strike Models for Estimating the Biological Performance of Kaplan Turbines
Deng, Zhiqun; Carlson, Thomas J.; Ploskey, Gene R.; Richmond, Marshall C.; Dauble, Dennis D.
Bio-indexing of hydroturbines is an important means to optimize passage conditions for fish by identifying operations for existing and new design turbines that minimize the probability of injury. Cost-effective implementation of bio-indexing requires the use of tools such as numerical and physical turbine models to generate hypotheses for turbine operations that can be tested at prototype scales using live fish. Numerical deterministic and stochastic blade strike models were developed for a 1:25-scale physical turbine model built by the U.S. Army Corps of Engineers for the original design turbine at McNary Dam and for prototype-scale original design and replacement minimum gap runner (MGR) turbines at Bonneville Dam's first powerhouse. Blade strike probabilities predicted by both models were comparable with the overall trends in blade strike probability observed in both prototype-scale live fish survival studies and physical turbine model using neutrally buoyant beads. The predictions from the stochastic model were closer to the experimental data than the predictions from the deterministic model because the stochastic model included more realistic consideration of the aspect of fish approaching to the leading edges of turbine runner blades. Therefore, the stochastic model should be the preferred method for the prediction of blade strike and injury probability for juvenile salmon and steelhead using numerical blade-strike models.
A Simple Model for Estimating Water Balance and Salinity of Reservoirs and Outflow
Miyamoto, S; Yuan, F; Anand, Shilpa
on flow and salinity of the stream and the floodplains. The first part deals with water and salt balance in reservoirs. The primary purpose of the model is to predict outflow salinity from the reservoir storage and inflow information in advance... management strategy, yet the method to predict outflow salinity has not been adequately examined. The study reported here examined the water and salt balance in a reservoir using a two-layer model. This model assumes that inflow blends with the storage...
Estimating food consumption rates of fish using a mercury mass balance model
Rasmussen, Joseph
on stomach contents. Simple models based on the mass balance of persistent contaminants such as radioactive cesium (137 Cs), poly- chlorinated bipheny
Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation
Logue, Jennifer M.
weather files for representative cities within each climatewas modeled in the representative city for each of the sevenclimate zones and representative cities were used: 2A hot/
Precise estimation of shell model energy by second order extrapolation method
Takahiro Mizusaki; Masatoshi Imada
A second order extrapolation method is presented for shell model calculations, where shell model energies of truncated spaces are well described as a function of energy variance by quadratic curves and exact shell model energies can be obtained by the extrapolation. This new extrapolation can give more precise energy than those of first order extrapolation method. It is also clarified that first order extrapolation gives a lower limit of shell model energy. In addition to the energy, we derive the second order extrapolation formula for expectation values of other observables.
Model error estimation in composite impact response prediction using hierarchical Bayes networks
Salas Mendez, Pablo Antonio
in Progressive Failure Analysis . . . 4.0.2 ModelingPuck and H. Schurmann, �Failure analysis of frp laminates byComposite laminate failure analysis using multi- continuum
Evolution of Meteorological Base Models for Estimating Hourly Global Solar Radiation in Texas�
Kim, H.; Baltazar, J.C.; Haberl, J.S
for Estimating Hourly Global Solar Radiation in Texas Kee Han Kima,b*, Juan-Carlos Baltazarb, and Jeff S. Haberla,b aDepartment of Architecture, Texas A&M University, 3137 TAMU, College Station, TX 77843-3137, U.S.A. bEnergy Systems Laboratory, Texas A... for measured solar radiation data and, as a result, rely on the values from typical meteorological years. Texas, in a similar fashion as other states in the US, does not have an active network for solar radiation data and has a variety of weather conditions...
Does Beta React to Market Conditions?: Estimates of Bull and Bear Betas using a Nonlinear Market Model with Endogenous Threshold Parameter
Kearns, Michael
Does Beta React to Market Conditions?: Estimates of Bull and Bear Betas using a Nonlinear Market Model with Endogenous Threshold Parameter by George Woodward and Heather Anderson Department transition between bull and bear states and allows the data to determine the threshold value. The estimated
Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models, atmospheric inversions and a new approach for estimating net ecosystem exchange from inventory-based data
Hayes, Daniel J [ORNL; Turner, David P [Oregon State University, Corvallis; Stinson, Graham [Pacific Forestry Centre, Canadian Forest Service; Mcguire, David [University of Alaska; Wei, Yaxing [ORNL; West, Tristram O. [Joint Global Change Research Institute, PNNL; Heath, Linda S. [USDA Forest Service; De Jong, Bernardus [ECOSUR; McConkey, Brian G. [Agriculture and Agri-Food Canada; Birdsey, Richard A. [U.S. Department of Agriculture Forest Service; Kurz, Werner [Canadian Forest Service; Jacobson, Andrew [NOAA ESRL and CIRES; Huntzinger, Deborah [University of Michigan; Pan, Yude [U.S. Department of Agriculture Forest Service; Post, Wilfred M [ORNL; Cook, Robert B [ORNL
We develop an approach for estimating net ecosystem exchange (NEE) using inventory-based information over North America (NA) for a recent 7-year period (ca. 2000 2006). The approach notably retains information on the spatial distribution of NEE, or the vertical exchange between land and atmosphere of all non-fossil fuel sources and sinks of CO2, while accounting for lateral transfers of forest and crop products as well as their eventual emissions. The total NEE estimate of a 327 252 TgC yr1 sink for NA was driven primarily by CO2 uptake in the Forest Lands sector (248 TgC yr1), largely in the Northwest and Southeast regions of the US, and in the Crop Lands sector (297 TgC yr1), predominantly in the Midwest US states. These sinks are counteracted by the carbon source estimated for the Other Lands sector (+218 TgC yr1), where much of the forest and crop products are assumed to be returned to the atmosphere (through livestock and human consumption). The ecosystems of Mexico are estimated tobe a small net source (+18 TgC yr1) due to land use change between 1993 and 2002. We compare these inventorybased estimates with results from a suite of terrestrial biosphere and atmospheric inversion models, where the mean continental-scale NEE estimate for each ensemble is 511 TgC yr1 and 931 TgC yr1, respectively. In the modeling approaches, all sectors, including Other Lands, were generally estimated to be a carbon sink, driven in part by assumed CO2 fertilization and/or lack of consideration of carbon sources from disturbances and product emissions. Additional fluxes not measured by the inventories, although highly uncertain, could add an additional 239 TgC yr1 to the inventory-based NA sink estimate, thus suggesting some convergence with the modeling approaches.
Agricultural Water Management xxx (2003) xxxxxx A GIS-based model to estimate the regionally
and landscape features that affect patterns in water available to plants, soil drainage, and aeration (Jaynes. Recent advances in GIS technology fa- cilitate the seamless integration of GIS and computer-based modeling. Multiple approaches exist to integrate GIS and hydrological models (Maidment, 1993; Abel et al
An estimation-free, robust CVaR portfolio allocation model
Mar 27, 2007 ... of these models have produced great theoretical impact, their practical ... the riskfree interest rate, and the asset returns, for dynamic portfolio models (cf. [12]). ...... Therefore, all the analysis and results presented through out the paper will ... [8] J. ?Cerb�kov�, Worst-case Var and CVaR, Operations Research�...
Approximate Conditional Least Squares Estimation of a Nonlinear State-Space Model via Unscented Kalman
Chan, Kung-Sik
Kalman Filter Kwang Woo Ahn Division of Biostatistics Medical College of Wisconsin, Milwaukee, WI 53226 function computed approximately via unscented Kalman filter (UKF). We derive conditions 1 #12;under which. ---------------------------- Keywords: Nonlinear time series; State-space model; Unscented Kalman filter; SIR model. 1. INTRODUCTION
Importance Sampling Methods for Estimating Convex Risk Measures in Portfolio Credit Risk Models
Gr�bel, Rudolf
obligors. Owing to the complexity of realistic models, quantitative risk analysis typically requires Monte the shortcomings of the industry standard Value-at-Risk (VaR). Our analysis demonstrates that standard Monte risk analysis to realistic credit portfolio models. During the past decade an intense effort has been
Estimation of net primary productivity using a process-based model in Gansu Province, Northwest China
Wang, Peijuan; Xie, Donghui; Zhou, Yuyu; E, Youhao; Zhu, Qijiang
The ecological structure in the arid and semi-arid region of Northwest China with forest, grassland, agriculture, Gobi, and desert, is complex, vulnerable, and unstable. It is a challenging and sustaining job to keep the ecological structure and improve its ecological function. Net primary productivity (NPP) modeling can help to improve the understanding of the ecosystem, and therefore, improve ecological efficiency. The boreal ecosystem productivity simulator (BEPS) model provides the possibility of NPP modeling in terrestrial ecosystem, but it has some limitations for application in arid and semi-arid regions. In this paper we improve the BEPS model, in terms of its water cycle by adding the processes of infiltration and surface runoff, to be applicable in arid and semi-arid regions. We model the NPP of forest, grass, and crop in Gansu Province as an experimental area in Northwest China in 2003 using the improved BEPS model, parameterized with moderate resolution remote sensing imageries and meteorological data. The modeled NPP using improved BEPS agrees better with the ground measurements in Qilian Mountain than that with original BEPS, with a higher R2 of 0.746 and lower root mean square error (RMSE) of 46.53 gC/m2 compared to R2 of 0.662 and RMSE of 60.19 gC/m2 from original BEPS. The modeled NPP of three vegetation types using improved BEPS show evident differences compared to that using original BEPS, with the highest difference ratio of 9.21% in forest and the lowest value of 4.29% in crop. The difference ratios between different vegetation types lie on the dependence on natural water sources. The modeled NPP in five geographic zones using improved BEPS are higher than those with original BEPS, with higher difference ratio in dry zones and lower value in wet zones.
Deriving a Framework for Estimating Individual Tree Measurements with Lidar for Use in the TAMBEETLE Southern Pine Beetle Infestation Growth Model
Stukey, Jared D.
The overall goal of this study was to develop a framework for using airborne lidar to derive inputs for the SPB infestation growth model TAMBEETLE. The specific objectives were (1) to estimate individual tree characteristics of XY location...
Estimation of Building Parameters Using Simplified Energy Balance Model and Metered Whole Building Energy Use
Masuda, H.; Claridge, D.
, cooling and heating and weather data using multiple linear regression models based on the simplified steady-state energy balance for a whole building. Two approaches using different response variables: the energy balance load (EBL) and the building thermal...
Modeling and parameter estimation for point-actuated continuous-facesheet
Stress focusing for controlled fracture in microelectromechanical systems Matthew A. Meitl,a Xue in microelectromechanical systems MEMSs based on the control of corner sharpness. Studies of model MEMS structures
Mode Estimation of Model-based Programs: Monitoring Systems with Complex Behavior
Williams, Brian C.
- active programming constructs with probabilistic, constraint-based modeling, and that offers a sim- ple controllers, have simple behaviors. However, the above trajectory spends most of its time wend- ing its way
Mode Estimation of Model-based Programs: Monitoring Systems with Complex Behavior
Williams, Brian C.
that combines reactive programming constructs with probabilistic, constraint-based modeling, and that offers wending its way through software functions. DS-1 is an instance of modern embedded systems whose
Probabilistic Seismic Demand Model and Fragility Estimates for Symmetric Rigid Blocks Subject to Rocking Motions
Bakhtiary, Esmaeel
This thesis presents a probability model to predict the maximum rotation of rocking bodies exposed to seismic excitations given specific earthquake intensity measures. After obtaining the nonlinear equations of motion and clarification...
k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models
Sun, Yixiao; Kim, Min Seong
MacKinnon, J. (1999). Bootstrap Testing in Nonlinear Models.J. (2002). Fast Double Bootstrap Tests of Nonnested LinearImproving the Reliability of Bootstrap Tests with the Fast
Estimation of Building Parameters Using Simplified Energy Balance Model and Metered Whole Building Energy Use�
Masuda, H.; Claridge, D.
, cooling and heating and weather data using multiple linear regression models based on the simplified steady-state energy balance for a whole building. Two approaches using different response variables: the energy balance load (EBL) and the building thermal...
Simultaneous Estimation of Reflectivity and Geologic Texture: Least-Squares Migration with a Hierarchical Bayesian Model
Zamanian, S. Ahmad
In many geophysical inverse problems, smoothness assumptions on the underlying geology are utilized to mitigate the effects of poor resolution and noise in the data and to improve the quality of the inferred model parameters. ...
Seismic scattering attributes to estimate reservoir fracture density : a numerical modeling study
Pearce, Frederick D. (Frederick Douglas), 1978-
We use a 3-D finite difference numerical model to generate synthetic seismograms from a simple fractured reservoir containing evenly-spaced, discrete, vertical fracture zones. The fracture zones are represented using a ...
Seismic Scattering Attributes to Estimate Reservoir Fracture Density: A Numerical Modeling Study
Pearce, Frederick Douglas
We use a 3-D finite difference numerical model to generate synthetic seismograms from a simple fractured reservoir containing evenly-spaced, discrete, vertical fracture zones. The fracture zones are represented using a ...
On-line Hydraulic State Estimation in Urban Water Networks Using Reduced Models
Preis, Ami
A Predictor-Corrector (PC) approach for on-line forecasting of water usage in an urban water system is presented and demonstrated. The M5 Model-Trees algorithm is used to predict water demands and Genetic Algorithms (GAs) ...
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using Reformulated Models
Braatz, Richard D.
Many researchers have worked to develop methods to analyze and characterize capacity fade in lithium-ion batteries. As a complement to approaches to mathematically model capacity fade that require detailed understanding ...
A comparative study of analytical models to estimate the LNAPL mound formation
Ahmed, Ashfaq
is constant for the duration of the spreading. Secondly, the model does not consider the organic phase which is held up as residual saturation in the unsaturated zone above the water table. Holzer [1976] used the saltwater/freshwater analogy to study... hydrocarbon. Reible et al. , [1991] developed a model to describe the one-dimensional infiltra- tion of a NAPL through an unsaturated zone initially at residual water saturation. tion of a NAPL through an unsaturated zone initially at residual water...
A comparative study of analytical models to estimate the LNAPL mound formation�
Ahmed, Ashfaq
developed. Even though these models are based on various as- sumptions, they are useful as tools in evaluating the spreading of the free oil phase during sn oil spill. The spreading depends on many factors, such as leak volume, type of petroleum product..., hydrogeological conditions, and hydraulic properties of the medium as well as the oil. Among the various modeling approaches to predict spill migration, the sharp interface approach has been widely examined due to its simplicity for homogeneous media...
Assessing Invariance of Factor Structures and Polytomous Item Response Model Parameter Estimates
Reyes, Jennifer McGee
.e., identical items, different people) for the homogenous graded response model (Samejima, 1969) and the partial credit model (Masters, 1982)? To evaluate measurement invariance using IRT methods, the item discrimination and item difficulty parameters... obtained from the GRM need to be equivalent across datasets. The YFCY02 and YFCY03 GRM item discrimination parameters (slope) correlation was 0.828. The YFCY02 and YFCY03 GRM item difficulty parameters (location) correlation was 0...
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
Based on the project's scope, the purpose of the estimate, and the availability of estimating resources, the estimator can choose one or a combination of techniques when estimating an activity or project. Estimating methods, estimating indirect and direct costs, and other estimating considerations are discussed in this chapter.
Journal of Molecular Graphics and Modelling 22 (2004) 441450 Continuous anisotropic representation of coarse-grained potentials
Straub, John E.
Journal of Molecular Graphics and Modelling 22 (2004) 441450 Continuous anisotropic representation improved performance. Novel graphical representations are developed and used to depict the orientational
Effect of One-Dimensional Field Data Assimilation on Land Surface Model Flux Estimates with Implications
Walker, Jeff
.W. Western1 1 Department of Civil and Environmental Engineering, The University of Melbourne, Victoria, Australia 2 CSIRO Marine and Atmospheric Research, Aspendale, Victoria, Australia Email: r Model (CBM) represent the exchange of energy and water between the earth's surface and lower atmosphere
Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving Horizon Estimation
Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving arising in the Airborne Wind Energy paradigm, an essential one is the control of the tethered airfoil], [3], the Airborne Wind Energy (AWE) paradigm shift proposes to get rid of the structural elements
Maximum Likelihood Estimation for Probit-Linear Mixed Models with Correlated Random Effects
Du, Jie
Jennifer S. K. Chan and Anthony Y. C. Kuk Department of Statistics, University of New South Wales, Sydney 2052, Australia The probit-normal model for binary data (McCulloch, 1994, Journal of the American function, one has to integrate out the random effects, which, except for a few special cases, cannot
Computational Methods for Estimation in the Modeling of Nonlinear Elastomers \\Lambda
vibration suppression devices. Materials such as elastomers, rubber�like composites typically filled and springs. One could imagine using active fillers, such as piezoelectric, magnetic, or conductive particles [12, 16, 19, 20]). Some of these models are based on the statistical molecular theory of polymers
Measuring and Modeling Fault Density for Plume-Fault Encounter Probability Estimation
Jordan, P.D.; Oldenburg, C.M.; Nicot, J.-P.
Emission of carbon dioxide from fossil-fueled power generation stations contributes to global climate change. Storage of this carbon dioxide within the pores of geologic strata (geologic carbon storage) is one approach to mitigating the climate change that would otherwise occur. The large storage volume needed for this mitigation requires injection into brine-filled pore space in reservoir strata overlain by cap rocks. One of the main concerns of storage in such rocks is leakage via faults. In the early stages of site selection, site-specific fault coverages are often not available. This necessitates a method for using available fault data to develop an estimate of the likelihood of injected carbon dioxide encountering and migrating up a fault, primarily due to buoyancy. Fault population statistics provide one of the main inputs to calculate the encounter probability. Previous fault population statistics work is shown to be applicable to areal fault density statistics. This result is applied to a case study in the southern portion of the San Joaquin Basin with the result that the probability of a carbon dioxide plume from a previously planned injection had a 3% chance of encountering a fully seal offsetting fault.
Evaluation of Blade-Strike Models for Estimating the Biological Performance of Large Kaplan Hydro Turbines
Deng, Zhiqun; Carlson, Thomas J.; Ploskey, Gene R.; Richmond, Marshall C.
BioIndex testing of hydro-turbines is sought as an analog to the hydraulic index testing conducted on hydro-turbines to optimize their power production efficiency. In BioIndex testing the goal is to identify those operations within the range identified by Index testing where the survival of fish passing through the turbine is maximized. BioIndex testing includes the immediate tailrace region as well as the turbine environment between a turbine's intake trashracks and the exit of its draft tube. The US Army Corps of Engineers and the Department of Energy have been evaluating a variety of means, such as numerical and physical turbine models, to investigate the quality of flow through a hydro-turbine and other aspects of the turbine environment that determine its safety for fish. The goal is to use these tools to develop hypotheses identifying turbine operations and predictions of their biological performance that can be tested at prototype scales. Acceptance of hypotheses would be the means for validation of new operating rules for the turbine tested that would be in place when fish were passing through the turbines. The overall goal of this project is to evaluate the performance of numerical blade strike models as a tool to aid development of testable hypotheses for bioIndexing. Evaluation of the performance of numerical blade strike models is accomplished by comparing predictions of fish mortality resulting from strike by turbine runner blades with observations made using live test fish at mainstem Columbia River Dams and with other predictions of blade strike made using observations of beads passing through a 1:25 scale physical turbine model.
Recurrent neural network language model training with noise contrastive estimation for speech recognition
Chen, X.; Liu, X.; Gales, M. J. F.; Woodland, P. C.
are evaluated on the CU-HTK LVCSR system for conversational telephone speech (CTS) used in the 2004 DARPA EARS evaluation. The acoustic models were trained on ap- proximately 2000 hours of Fisher conversational speech released by the LDC. A 59k recognition word... -gram LM was trained using a total of 545 million words from 2 text sources: the LDC Fisher acoustic transcriptions, Fisher, of 20 million words (weight 0.75), and the University Wash- ington conversational web data [28], UWWeb, of 525 million words...
A conceptual model to estimate cost effectiveness of the indoor environment improvements
Seppanen, Olli; Fisk, William J.
Macroeconomic analyses indicate a high cost to society of a deteriorated indoor climate. The few example calculations performed to date indicate that measures taken to improve IEQ are highly cost-effective when health and productivity benefits are considered. We believe that cost-benefit analyses of building designs and operations should routinely incorporate health and productivity impacts. As an initial step, we developed a conceptual model that shows the links between improvements in IEQ and the financial gains from reductions in medical care and sick leave, improved work performance, lower employee turn over, and reduced maintenance due to fewer complaints.
Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models with Weakly Exogenous Regressors
Pesaran, Hashem; Chudik, Alexander
; , xi` = x` + #17;i; x`, #17;i; x` #24; IIDN #0; 0; #27;2 x` #1; , gi` = g` + #17;i; g`, #17;i; g` #24; IIDN #0; 0; #27;2 g` #1; for ` = 1; 2; ::;m; and i = 1; 2; :::; N . Also, without loss of generality, the factor loadings are calibrated so that V... , are generated to be heteroskedastic and weakly cross- sectionally dependent. Speci?cally, we adopt the following spatial autoregressive model (SAR) to generate "t = ("1t; "2t; :::; "Nt)0: "t = a"S""t + e"t, (39) 19 where the elements of e"t are drawn as IIDN #0...
Application of a Rule-Based Model to Estimate Mercury Exchange for Three Background Biomes in the Continental United States
Hartman, Jelena S. [University of Nevada, Reno; Weisberg, Peter J [University of Nevada, Reno; Pillai, Rekha [University of Nevada, Reno; Ericksen, Joey A. [University of Nevada, Reno; Gustin, Mae S. [University of Nevada, Reno; Kuiken, Todd [Tennessee Technological University; Zhang, Hong [Tennessee Technological University; Lindberg, Steven Eric [ORNL; Rytuba, J. J. [U.S. Geological Survey, Menlo Park, CA
Ecosystems that have low mercury (Hg) concentrations (i.e., not enriched or impacted by geologic or anthropogenic processes) cover most of the terrestrial surface area of the earth yet their role as a net source or sink for atmospheric Hg is uncertain. Here we use empirical data to develop a rule-based model implemented within a geographic information system framework to estimate the spatial and temporal patterns of Hg flux for semiarid deserts, grasslands, and deciduous forests representing 45% of the continental United States. This exercise provides an indication of whether these ecosystems are a net source or sink for atmospheric Hg as well as a basis for recommendation of data to collect in future field sampling campaigns. Results indicated that soil alone was a small net source of atmospheric Hg and that emitted Hg could be accounted for based on Hg input by wet deposition. When foliar assimilation and wet deposition are added to the area estimate of soil Hg flux these biomes are a sink for atmospheric Hg.
Estimating Policy-Driven Greenhouse Gas Emissions Trajectories in California: The California Greenhouse Gas Inventory Spreadsheet (GHGIS) Model
Greenblatt, Jeffery B.
A California Greenhouse Gas Inventory Spreadsheet (GHGIS) model was developed to explore the impact of combinations of state policies on state greenhouse gas (GHG) and regional criteria pollutant emissions. The model included representations of all GHG- emitting sectors of the California economy (including those outside the energy sector, such as high global warming potential gases, waste treatment, agriculture and forestry) in varying degrees of detail, and was carefully calibrated using available data and projections from multiple state agencies and other sources. Starting from basic drivers such as population, numbers of households, gross state product, numbers of vehicles, etc., the model calculated energy demands by type (various types of liquid and gaseous hydrocarbon fuels, electricity and hydrogen), and finally calculated emissions of GHGs and three criteria pollutants: reactive organic gases (ROG), nitrogen oxides (NOx), and fine (2.5 ?m) particulate matter (PM2.5). Calculations were generally statewide, but in some sectors, criteria pollutants were also calculated for two regional air basins: the South Coast Air Basin (SCAB) and the San Joaquin Valley (SJV). Three scenarios were developed that attempt to model: (1) all committed policies, (2) additional, uncommitted policy targets and (3) potential technology and market futures. Each scenario received extensive input from state energy planning agencies, in particular the California Air Resources Board. Results indicate that all three scenarios are able to meet the 2020 statewide GHG targets, and by 2030, statewide GHG emissions range from between 208 and 396 MtCO2/yr. However, none of the scenarios are able to meet the 2050 GHG target of 85 MtCO2/yr, with emissions ranging from 188 to 444 MtCO2/yr, so additional policies will need to be developed for California to meet this stringent future target. A full sensitivity study of major scenario assumptions was also performed. In terms of criteria pollutants, targets were less well-defined, but while all three scenarios were able to make significant reductions in ROG, NOx and PM2.5 both statewide and in the two regional air basins, they may nonetheless fall short of what will be required by future federal standards. Specifically, in Scenario 1, regional NOx emissions are approximately three times the estimated targets for both 2023 and 2032, and in Scenarios 2 and 3, NOx emissions are approximately twice the estimated targets. Further work is required in this area, including detailed regional air quality modeling, in order to determine likely pathways for attaining these stringent targets.
LBNL-XXXXX | Logue et al., Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation
LBNL-XXXXX | Logue et al., Evaluation of an Incremental Ventilation Energy Model for Estimating. Turner, Iain S. Walker, and Brett C. Singer Environmental Energy Technologies Division June 2012 LBNL-5796E #12;LBNL-XXXXX | Logue et al., Evaluation of an Incremental Ventilation Energy Model
Discretized maximum likelihood estimates for adaptive control of ergodic Markov models
Duncan, Tyrone E.; Pasik-Duncan, B.; Stettner, L.
processes, almost optimal adaptive control AMS subject classi#12;cations. 93E35, 93C40, 60J05, 62M05 PII. S0363012996298369 1. Introduction. In many control problems the models are not completely de- scribed and there are perturbations or unmodeled dynamics....s., so by (64), (93) I1((v^n; n 2 N)) #20; lim sup n!1 1 n n?1 X i=0 Z E c(z; uiN (z))#25; #11;0 uiN (dz) + " a.s. For ! 2 ? n N it follows from (93) that (94) I1((v^n; n 2 N)) #20; lim sup n!1 1 n n?1 X i=0 1F (#22;#14;)(#11;^iN ) Z E c(z; uiN (z))#25...
Primate polonium metabolic models and their use in estimation of systemic radiation doses from bioassay data. Final report
Cohen, N. [New York Univ. Medical Center, Tuxedo, NY (United States). Dept. of Environmental Medicine
A Polonium metabolic model was derived and incorporated into a Fortran algorithm which estimates the systemic radiation dose from {sup 210}Po when applied to occupational urine bioassay data. The significance of the doses estimated are examined by defining the degree of uncertainty attached to them through comprehensive statistical testing procedures. Many parameters necessary for dosimetry calculations (such as organ partition coefficients and excretion fractions), were evaluated from metabolic studies of {sup 210}Po in non-human primates. Two tamarins and six baboons were injected intravenously with {sup 210}Po citrate. Excreta and blood samples were collected. Five of the baboons were sacrificed at times ranging from 1 day to 3 months post exposure. Complete necropsies were performed and all excreta and the majority of all skeletal and tissue samples were analyzed radiochemically for their {sup 210}Po content. The {sup 210}Po excretion rate in the baboon was more rapid than in the tamarin. The biological half-time of {sup 210}Po excretion in the baboon was approximately 15 days while in the tamarin, the {sup 210}Po excretion rate was in close agreement with the 50 day biological half-time predicted by ICRP 30. Excretion fractions of {sup 210}Po in the non-human primates were found to be markedly different from data reported elsewhere in other species, including man. A thorough review of the Po urinalysis procedure showed that significant recovery losses resulted when metabolized {sup 210}Po was deposited out of raw urine. Polonium-210 was found throughout the soft tissues of the baboon but not with the partition coefficients for liver, kidneys, and spleen that are predicted by the ICRP 30 metabolic model. A fractional distribution of 0.29 for liver, 0.07 for kidneys, and 0.006 for spleen was determined. Retention times for {sup 210}Po in tissues are described by single exponential functions with biological half-times ranging from 15 to 50 days.
Estimates of frequency-dependent compressibility from a quasistatic double-porosity model
Berryman, J. G.; Wang, H. F.
Gassmann's relationship between the drained and undrained bulk modulus of a porous medium is often used to relate the dry bulk modulus to the saturated bulk modulus for elastic waves, because the compressibility of air is considered so high that the dry rock behaves in a drained fashion and the frequency of elastic waves is considered so high that the saturated rock behaves in an undrained fashion. The bulk modulus calculated from ultrasonic velocities, however, often does not match the Gassmann prediction. Mavko and Jizba examined how local flow effects and unequilibrated pore pressures can lead to greater stiffnesses. Their conceptual model consists of a distribution of porosities obtained from the strain-versus-confining-pressure behavior. Stiff pores that close at higher confining pressures are considered to remain undrained (unrelaxed) while soft pores drain even for high-frequency stress changes. If the pore shape distribution is bimodal, then the rock approximately satisfies the assumptions of a double-porosity, poroelastic material. Berryman and Wang [1995] established linear constitutive equations and identified four different time scales of ow behavior: (1) totally drained, (2) soft pores are drained but stiff pores are undrained, (3) soft and stiff pores are locally equilibrated, but undrained beyond the grain scale, and (4) both soft and stiff pores are undrained. The relative magnitudes of the four associated bulk moduli will be examined for all four moduli and illustrated for several sandstones.
Estimating model parameters for an impact-produced shock-wave simulation: Optimal use of partial data with the extended Kalman filter
Kao, Jim [Los Alamos National Laboratory, Applied Physics Division, P.O. Box 1663, MS T086, Los Alamos, NM 87545 (United States)]. E-mail: firstname.lastname@example.com; Flicker, Dawn [Los Alamos National Laboratory, Applied Physics Division, P.O. Box 1663, MS T086, Los Alamos, NM 87545 (United States); Ide, Kayo [University of California at Los Angeles (United States); Ghil, Michael [University of California at Los Angeles (United States)
This paper builds upon our recent data assimilation work with the extended Kalman filter (EKF) method [J. Kao, D. Flicker, R. Henninger, S. Frey, M. Ghil, K. Ide, Data assimilation with an extended Kalman filter for an impact-produced shock-wave study, J. Comp. Phys. 196 (2004) 705-723.]. The purpose is to test the capability of EKF in optimizing a model's physical parameters. The problem is to simulate the evolution of a shock produced through a high-speed flyer plate. In the earlier work, we have showed that the EKF allows one to estimate the evolving state of the shock wave from a single pressure measurement, assuming that all model parameters are known. In the present paper, we show that imperfectly known model parameters can also be estimated accordingly, along with the evolving model state, from the same single measurement. The model parameter optimization using the EKF can be achieved through a simple modification of the original EKF formalism by including the model parameters into an augmented state variable vector. While the regular state variables are governed by both deterministic and stochastic forcing mechanisms, the parameters are only subject to the latter. The optimally estimated model parameters are thus obtained through a unified assimilation operation. We show that improving the accuracy of the model parameters also improves the state estimate. The time variation of the optimized model parameters results from blending the data and the corresponding values generated from the model and lies within a small range, of less than 2%, from the parameter values of the original model. The solution computed with the optimized parameters performs considerably better and has a smaller total variance than its counterpart using the original time-constant parameters. These results indicate that the model parameters play a dominant role in the performance of the shock-wave hydrodynamic code at hand.
Estimated United States Transportation Energy Use 2005
Smith, C A; Simon, A J; Belles, R D
A flow chart depicting energy flow in the transportation sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 31,000 trillion British Thermal Units (trBTUs) of energy were used throughout the United States in transportation activities. Vehicles used in these activities include automobiles, motorcycles, trucks, buses, airplanes, rail, and ships. The transportation sector is powered primarily by petroleum-derived fuels (gasoline, diesel and jet fuel). Biomass-derived fuels, electricity and natural gas-derived fuels are also used. The flow patterns represent a comprehensive systems view of energy used within the transportation sector.
Glass Property Models and Constraints for Estimating the Glass to be Produced at Hanford by Implementing Current Advanced Glass Formulation Efforts
Vienna, John D.; Kim, Dong-Sang; Skorski, Daniel C.; Matyas, Josef
Recent glass formulation and melter testing data have suggested that significant increases in waste loading in HLW and LAW glasses are possible over current system planning estimates. The data (although limited in some cases) were evaluated to determine a set of constraints and models that could be used to estimate the maximum loading of specific waste compositions in glass. It is recommended that these models and constraints be used to estimate the likely HLW and LAW glass volumes that would result if the current glass formulation studies are successfully completed. It is recognized that some of the models are preliminary in nature and will change in the coming years. Plus the models do not currently address the prediction uncertainties that would be needed before they could be used in plant operations. The models and constraints are only meant to give an indication of rough glass volumes and are not intended to be used in plant operation or waste form qualification activities. A current research program is in place to develop the data, models, and uncertainty descriptions for that purpose. A fundamental tenet underlying the research reported in this document is to try to be less conservative than previous studies when developing constraints for estimating the glass to be produced by implementing current advanced glass formulation efforts. The less conservative approach documented herein should allow for the estimate of glass masses that may be realized if the current efforts in advanced glass formulations are completed over the coming years and are as successful as early indications suggest they may be. Because of this approach there is an unquantifiable uncertainty in the ultimate glass volume projections due to model prediction uncertainties that has to be considered along with other system uncertainties such as waste compositions and amounts to be immobilized, split factors between LAW and HLW, etc.
Source Term Estimation of Radioxenon Released from the Fukushima Dai-ichi Nuclear Reactors Using Measured Air Concentrations and Atmospheric Transport Modeling
Eslinger, Paul W. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Biegalski, S. [Univ. of Texas at Austin, TX (United States); Bowyer, Ted W. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Cooper, Matthew W. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Haas, Derek A. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Hayes, James C. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Hoffman, Ian [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); Korpach, E. [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); Yi, Jing [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); Miley, Harry S. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Rishel, Jeremy P. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Ungar, R. Kurt [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); White, Brian [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); Woods, Vincent T. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Systems designed to monitor airborne radionuclides released from underground nuclear explosions detected radioactive fallout from the Fukushima Daiichi nuclear accident in March 2011. Atmospheric transport modeling (ATM) of plumes of noble gases and particulates were performed soon after the accident to determine plausible detection locations of any radioactive releases to the atmosphere. We combine sampling data from multiple International Modeling System (IMS) locations in a new way to estimate the magnitude and time sequence of the releases. Dilution factors from the modeled plume at five different detection locations were combined with 57 atmospheric concentration measurements of 133-Xe taken from March 18 to March 23 to estimate the source term. This approach estimates that 59% of the 1.24�1019 Bq of 133-Xe present in the reactors at the time of the earthquake was released to the atmosphere over a three day period. Source term estimates from combinations of detection sites have lower spread than estimates based on measurements at single detection sites. Sensitivity cases based on data from four or more detection locations bound the source term between 35% and 255% of available xenon inventory.
Carbonaceous aerosols recorded in a southeastern Tibetan glacier: analysis of temporal variations and model estimates of sources and radiative forcing
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Wang, Mo; Xu, B.; Cao, J.; Tie, X.; Wang, Hailong; Zhang, Rudong; Qian, Yun; Rasch, Philip J.; Zhao, Shuyu; Wu, Guangjian; et al
High temporal resolution measurements of black carbon (BC) and organic carbon (OC) covering the time period of 1956�2006 in an ice core over the southeastern Tibetan Plateau show a distinct seasonal dependence of BC and OC with higher respective concentrations but a lower OC / BC ratio in the non-monsoon season than during the summer monsoon. We use a global aerosol-climate model, in which BC emitted from different source regions can be explicitly tracked, to quantify BC source�receptor relationships between four Asian source regions and the southeastern Tibetan Plateau as a receptor. The model results show that South Asia hasmore��the largest contribution to the present-day (1996�2005) mean BC deposition at the ice-core drilling site during the non-monsoon season (October to May) (81%) and all year round (74%), followed by East Asia (14% to the non-monsoon mean and 21% to the annual mean). The ice-core record also indicates stable and relatively low BC and OC deposition fluxes from the late 1950s to 1980, followed by an overall increase to recent years. This trend is consistent with the BC and OC emission inventories and the fuel consumption of South Asia (as the primary contributor to annual mean BC deposition). Moreover, the increasing trend of the OC / BC ratio since the early 1990s indicates a growing contribution of coal combustion and/or biomass burning to the emissions. The estimated radiative forcing induced by BC and OC impurities in snow has increased since 1980, suggesting an increasing potential influence of carbonaceous aerosols on the Tibetan glacier melting and the availability of water resources in the surrounding regions. Our study indicates that more attention to OC is merited because of its non-negligible light absorption and the recent rapid increases evident in the ice-core record.��less
Multi-scale geospatial agroecosystem modeling: a case study on the influence of soil data resolution on carbon budget estimates
Zhang, Xuesong; Sahajpal, Ritvik; Manowitz, D.; Zhao, Kaiguang; LeDuc, Stephen D.; Xu, Min; Xiong, Wei; Zhang, Aiping; Izaurralde, Roberto C.; Thomson, Allison M.; West, Tristram O.; Post, W. M.
The development of effective measures to stabilize atmospheric CO2 concentration and mitigate negative impacts of climate change requires accurate quantification of the spatial variation and magnitude of the terrestrial carbon (C) flux. However, the spatial pattern and strength of terrestrial C sinks and sources remain uncertain. In this study, we designed a spatially-explicit agroecosystem modeling system by integrating the Environmental Policy Integrated Climate (EPIC) model with multiple sources of geospatial and surveyed datasets (including crop type map, elevation, climate forcing, fertilizer application, tillage type and distribution, and crop planting and harvesting date), and applied it to examine the sensitivity of cropland C flux simulations to two widely used soil databases (i.e. State Soil Geographic-STATSGO of a scale of 1:250,000 and Soil Survey Geographic-SSURGO of a scale of 1:24,000) in Iowa, USA. To efficiently execute numerous EPIC runs resulting from the use of high resolution spatial data (56m), we developed a parallelized version of EPIC. Both STATSGO and SSURGO led to similar simulations of crop yields and Net Ecosystem Production (NEP) estimates at the State level. However, substantial differences were observed at the county and sub-county (grid) levels. In general, the fine resolution SSURGO data outperformed the coarse resolution STATSGO data for county-scale crop-yield simulation, and within STATSGO, the area-weighted approach provided more accurate results. Further analysis showed that spatial distribution and magnitude of simulated NEP were more sensitive to the resolution difference between SSURGO and STATSGO at the county or grid scale. For over 60% of the cropland areas in Iowa, the deviations between STATSGO- and SSURGO-derived NEP were larger than 1MgCha(-1)yr(-1), or about half of the average cropland NEP, highlighting the significant uncertainty in spatial distribution and magnitude of simulated C fluxes resulting from differences in soil data resolution.
Carbonaceous Aerosols Recorded in a Southeastern Tibetan Glacier: Analysis of Temporal Variations and Model Estimates of Sources and Radiative Forcing
Wang, Mo; Xu, B.; Cao, J.; Tie, X.; Wang, Hailong; Zhang, Rudong; Qian, Yun; Rasch, Philip J.; Zhao, Shuyu; Wu, Guangjian; Zhao, Huabiao; Joswiak, Daniel R.; Li, Jiule; Xie, Ying
High temporal resolution measurements of black carbon (BC) and organic carbon (OC) covering the time period of 1956-2006 in an ice core over the southeastern Tibetan Plateau show a distinct seasonal dependence of OC/BC ratio with higher values in the non-monsoon season than during the summer monsoon. We use a global aerosol-climate model, in which BC emitted from different source regions can be explicitly tracked, to quantify BC source-receptor relationships between four Asian source regions and the southern Tibetan Plateau as a receptor. The model results show that South Asia is a primary contributor during the non-monsoon season (October to May) (81%) and on an annual basis (74%), followed by East Asia (14% and 21%, respectively). The ice-core record also indicates stable and relatively low BC and OC deposition fluxes from late 1950s to 1980, followed by an overall increase to recent years. This trend is consistent with the BC and OC emission inventories and the fuel consumption of South Asia as the primary contributor. Moreover, the increasing trend of OC/BC ratio since the early 1990s indicates a growing contribution of coal combustion and biomass burning to the emissions. The estimated radiative forcing induced by BC/OC impurities in snow has increased since 1980, suggesting an increasing influence of carbonaceous aerosols on the Tibetan glacier melting, influencing the availability of water resources in the surrounding regions. Our study indicates that the role of OC deserves more attention because of its non-negligible light absorption and the more rapid increase than BC
Estimating extinction risk under climate change: next-generation models simultaneously incorporate demography, dispersal, and biotic interactions
Kissling, W. Daniel
interactions Estimating species-level extinction risk underin predicting species-level extinction risk under climateto assess extinction risk of select species under climate
A Stochastic Unit-Commitment Model to Estimate the Costs of Changing Power Plant Operation under High Amounts of Intermittent Wind Power
A Stochastic Unit-Commitment Model to Estimate the Costs of Changing Power Plant Operation under High Amounts of Intermittent Wind Power Integration Meibom, P.1 , Brand, H.2 , Barth, R.2 and Weber, C in several European countries. The introduction of substantial amounts of wind power in a liberalized
IEEE TRANSACTIONS ON SYSTEMS, MAN AND CYBERNETICS, PART B: CYBERNETICS, VOL. ?, NO. ?, ? 1 M-estimator and D-optimality Model Construction using
Chen, Sheng
output is a linear combination of non- linear basis functions. Provided that there is a separate and linear algebra are directly applicable. Moreover by applying linear regression statistical techniques-estimator and D-optimality Model Construction using Orthogonal Forward Regression Xia Hong, Senior Member, IEEE
DEWEK Wind Energy Conference 2012 Category: 4. Simulation models BACKWARD EXTRAPOLATION OF SHORT-TIME MEASUREMENT DATA FOR A REMAINING SERVICE LIFE ESTIMATION OF WIND
Berlin,Technische Universit�t
DEWEK Wind Energy Conference 2012 Category: 4. Simulation models 1 BACKWARD EXTRAPOLATION OF SHORT-TIME MEASUREMENT DATA FOR A REMAINING SERVICE LIFE ESTIMATION OF WIND TURBINES Dipl.-Ing. Ren� Kamieth, Prof. Dr, Germany, Tel.: +49-(0)30-314-23603, Fax: +49-(0)30-314-26131 Summary Wind turbines built in the last
CONTRIBUTED to ASA/Q&P, ASA/SPES, and IMS JRC 2000 Spatial Spectral Estimation for Reactor Modelling and Control
Scarrott, Carl
and reactor control. Carl J. Scarrott, Mathematics and Statistics Dept., Lancaster University, Lancaster, LA1CONTRIBUTED to ASA/Q&P, ASA/SPES, and IMS JRC 2000 Spatial Spectral Estimation for Reactor Modelling and Control C.J. Scarrott G. Tunnicli e-Wilson Lancaster University, Lancaster, UK. Two
Recession-based hydrological models for estimating low flows in ungauged catchments in the Himalayas Hydrology and Earth System Sciences, 8(5), 891902 (2004) EGU
Paris-Sud XI, Université de
Recession-based hydrological models for estimating low flows in ungauged catchments in the Himalayas 891 Hydrology and Earth System Sciences, 8(5), 891902 (2004) © EGU Recession-based hydrological.R. Young1 and S.R. Kansakar2 1 Centre for Ecology and Hydrology,Wallingford, Oxfordshire, OX10 8BB, UK 2
A Unified Open-Circuit-Voltage Model of Lithium-ion Batteries for State-of-Charge Estimation and State-of-Health Monitoring $
Peng, Huei
A Unified Open-Circuit-Voltage Model of Lithium-ion Batteries for State-of-Charge Estimation. Keywords: Electric vehicles, Lithium-ion batteries, Open-Circuit-Voltage, State-of-Charge, State is widely used for characterizing battery properties under different conditions. It contains important
Supervised learning of a regression model based on latent process. Application to the estimation of fuel cell life time
Chamroukhi, Faicel
of fuel cell life time Ra�ssa Onanena(1) , Faicel Chamroukhi(1) , Latifa Oukhellou(1)(2) , Denis Candusso to estimate fuel cell duration time from electrochemical impedance spectroscopy measurements. It consists for the estimation of fuel cell time duration. The performances of the proposed approach are evaluated
Model Selection and Health Effect Estimation in Environmental Epidemiology Francesca Dominici, Chi Wang, Ciprian Crainiceanu, Giovanni Parmigiani
Dominici, Francesca
Abstract In air pollution epidemiology, improvements in statistical analysis tools can translate for confounding. In studies of air pollution and health, the focus should ideally be on estimating health effects estimate the association between prenatal and lifetime exposures to air pollutants and pulmonary function
Second cancer incidence risk estimates using BEIR VII models for standard and complex external beam radiotherapy for early breast cancer
Donovan, E. M.; James, H.; Bonora, M.; Yarnold, J. R.; Evans, P. M. [Joint Department of Physics, Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Sutton SM2 5PT (United Kingdom); Physics Department, Ipswich Hospital NHS Foundation Trust, Ipswich IP4 5PD (United Kingdom); Department of Academic Radiotherapy, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton SM2 5PT, United Kingdom and School of Radiotherapy, University of Milan, Milan 20122 (Italy); Department of Academic Radiotherapy, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton SM2 5PT (United Kingdom); Centre for Vision Speech and Signal Processing, University of Surrey, Guildford GU2 7XH (United Kingdom)
Purpose: To compare organ specific cancer incidence risks for standard and complex external beam radiotherapy (including cone beam CT verification) following breast conservation surgery for early breast cancer.Method: Doses from breast radiotherapy and kilovoltage cone beam CT (CBCT) exposures were obtained from thermoluminescent dosimeter measurements in an anthropomorphic phantom in which the positions of radiosensitive organs were delineated. Five treatment deliveries were investigated: (i) conventional tangential field whole breast radiotherapy (WBRT), (ii) noncoplanar conformal delivery applicable to accelerated partial beast irradiation (APBI), (iii) two-volume simultaneous integrated boost (SIB) treatment, (iv) forward planned three-volume SIB, and (v) inverse-planned three volume SIB. Conformal and intensity modulated radiotherapy methods were used to plan the complex treatments. Techniques spanned the range from simple methods appropriate for patient cohorts with a low cancer recurrence risk to complex plans relevant to cohorts with high recurrence risk. Delineated organs at risk included brain, salivary glands, thyroid, contralateral breast, left and right lung, esophagus, stomach, liver, colon, and bladder. Biological Effects of Ionizing Radiation (BEIR) VII cancer incidence models were applied to the measured mean organ doses to determine lifetime attributable risk (LAR) for ages at exposure from 35 to 80 yr according to radiotherapy techniques, and included dose from the CBCT imaging. Results: All LAR decreased with age at exposure and were lowest for brain, thyroid, liver, and bladder (<0.1%). There was little dependence of LAR on radiotherapy technique for these organs and for colon and stomach. LAR values for the lungs for the three SIB techniques were two to three times those from WBRT and APBI. Uncertainties in the LAR models outweigh any differences in lung LAR between the SIB methods. Constraints in the planning of the SIB methods ensured that contralateral breast doses and LAR were comparable to WBRT, despite their added complexity. The smaller irradiated volume of the ABPI plan contributed to a halving of LAR for contralateral breast compared with the other plan types. Daily image guided radiotherapy (IGRT) for a left breast protocol using kilovoltage CBCT contributed <10% to LAR for the majority of organs, and did not exceed 22% of total organ dose. Conclusions: Phantom measurements and calculations of LAR from the BEIR VII models predict that complex breast radiotherapy techniques do not increase the theoretical risk of second cancer incidence for organs distant from the treated breast, or the contralateral breast where appropriate plan constraints are applied. Complex SIB treatments are predicted to increase the risk of second cancer incidence in the lungs compared to standard whole breast radiotherapy; this is outweighed by the threefold reduction in 5 yr local recurrence risk for patients of high risk of recurrence, and young age, from the use of radiotherapy. APBI may have a favorable impact on risk of second cancer in the contralateral breast and lung for older patients at low risk of recurrence. Intensive use of IGRTincreased the estimated values of LAR but these are dominated by the effect of the dose from the radiotherapy, and any increase in LAR from IGRT is much lower than the models' uncertainties.
Estimation of methane and carbon dioxide surface fluxes using a 3-D global atmospheric chemical transport model
Chen, Yu-Han, 1973-
Methane (CH?) and carbon dioxide (CO?) are the two most radiatively important greenhouse gases attributable to human activity. Large uncertainties in their source and sink magnitudes currently exist. We estimate global ...
Operator-adapted finite element wavelets : theory and applications to a posteriori error estimation and adaptive computational modeling
Sudarshan, Raghunathan, 1978-
We propose a simple and unified approach for a posteriori error estimation and adaptive mesh refinement in finite element analysis using multiresolution signal processing principles. Given a sequence of nested discretizations ...
ARM Climate Modeling Best Estimate from Darwin, AU (ARMBE-CLDRAD TWPC3 V2.1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Manus Island, PNG (ARMBE-CLDRAD TWPC1 V2.1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
Modeling Mud-Filtrate Invasion Effects on Resistivity Logs to Estimate Permeability of Vuggy and Fractured Carbonate Formations
Torres-Verd�n, Carlos
measurements with conventional and non- conventional well logs to calculate static and dynamic petrophysical/or fractures in the displacement of hydrocarbons by mud filtrate. Introduction Permeability estimation is one
A combined method to estimate parameters of the thalamocortical model from a heavily noise-corrupted time series of action potential
Wang, Ruofan; Wang, Jiang; Deng, Bin, E-mail: email@example.com; Liu, Chen; Wei, Xile [Department of Electrical and Automation Engineering, Tianjin University, Tianjin (China)] [Department of Electrical and Automation Engineering, Tianjin University, Tianjin (China); Tsang, K. M.; Chan, W. L. [Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon (Hong Kong)] [Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon (Hong Kong)
A combined method composing of the unscented Kalman filter (UKF) and the synchronization-based method is proposed for estimating electrophysiological variables and parameters of a thalamocortical (TC) neuron model, which is commonly used for studying Parkinson's disease for its relay role of connecting the basal ganglia and the cortex. In this work, we take into account the condition when only the time series of action potential with heavy noise are available. Numerical results demonstrate that not only this method can estimate model parameters from the extracted time series of action potential successfully but also the effect of its estimation is much better than the only use of the UKF or synchronization-based method, with a higher accuracy and a better robustness against noise, especially under the severe noise conditions. Considering the rather important role of TC neuron in the normal and pathological brain functions, the exploration of the method to estimate the critical parameters could have important implications for the study of its nonlinear dynamics and further treatment of Parkinson's disease.
Rakha, Hesham A.
, MOBILE6, Fuel Consumption Models, Emission Models. #12;3 INTRODUCTION Numerous energy and emission models) and Environmental Protection Agency (EPA) laboratory fuel consumption and emission databases are utilized for model are consistent in trends with laboratory measurements. Furthermore, the VT-Micro and MOBILE6 models accurately
Constraining the Influence of Natural Variability to Improve Estimates of Global Aerosol Indirect Effects in a Nudged Version of the Community Atmosphere Model 5
Kooperman, G. J.; Pritchard, M. S.; Ghan, Steven J.; Wang, Minghuai; Somerville, Richard C.; Russell, Lynn
Natural modes of variability on many timescales influence aerosol particle distributions and cloud properties such that isolating statistically significant differences in cloud radiative forcing due to anthropogenic aerosol perturbations (indirect effects) typically requires integrating over long simulations. For state-of-the-art global climate models (GCM), especially those in which embedded cloud-resolving models replace conventional statistical parameterizations (i.e. multi-scale modeling framework, MMF), the required long integrations can be prohibitively expensive. Here an alternative approach is explored, which implements Newtonian relaxation (nudging) to constrain simulations with both pre-industrial and present-day aerosol emissions toward identical meteorological conditions, thus reducing differences in natural variability and dampening feedback responses in order to isolate radiative forcing. Ten-year GCM simulations with nudging provide a more stable estimate of the global-annual mean aerosol indirect radiative forcing than do conventional free-running simulations. The estimates have mean values and 95% confidence intervals of -1.54 � 0.02 W/m2 and -1.63 � 0.17 W/m2 for nudged and free-running simulations, respectively. Nudging also substantially increases the fraction of the world�s area in which a statistically significant aerosol indirect effect can be detected (68% and 25% of the Earth's surface for nudged and free-running simulations, respectively). One-year MMF simulations with and without nudging provide global-annual mean aerosol indirect radiative forcing estimates of -0.80 W/m2 and -0.56 W/m2, respectively. The one-year nudged results compare well with previous estimates from three-year free-running simulations (-0.77 W/m2), which showed the aerosol-cloud relationship to be in better agreement with observations and high-resolution models than in the results obtained with conventional parameterizations.
SU-E-I-46: Sample-Size Dependence of Model Observers for Estimating Low-Contrast Detection Performance From CT Images
Reiser, I; Lu, Z [University of Chicago, Chicago, IL (United States)
Purpose: Recently, task-based assessment of diagnostic CT systems has attracted much attention. Detection task performance can be estimated using human observers, or mathematical observer models. While most models are well established, considerable bias can be introduced when performance is estimated from a limited number of image samples. Thus, the purpose of this work was to assess the effect of sample size on bias and uncertainty of two channelized Hotelling observers and a template-matching observer. Methods: The image data used for this study consisted of 100 signal-present and 100 signal-absent regions-of-interest, which were extracted from CT slices. The experimental conditions included two signal sizes and five different x-ray beam current settings (mAs). Human observer performance for these images was determined in 2-alternative forced choice experiments. These data were provided by the Mayo clinic in Rochester, MN. Detection performance was estimated from three observer models, including channelized Hotelling observers (CHO) with Gabor or Laguerre-Gauss (LG) channels, and a template-matching observer (TM). Different sample sizes were generated by randomly selecting a subset of image pairs, (N=20,40,60,80). Observer performance was quantified as proportion of correct responses (PC). Bias was quantified as the relative difference of PC for 20 and 80 image pairs. Results: For n=100, all observer models predicted human performance across mAs and signal sizes. Bias was 23% for CHO (Gabor), 7% for CHO (LG), and 3% for TM. The relative standard deviation, ?(PC)/PC at N=20 was highest for the TM observer (11%) and lowest for the CHO (Gabor) observer (5%). Conclusion: In order to make image quality assessment feasible in the clinical practice, a statistically efficient observer model, that can predict performance from few samples, is needed. Our results identified two observer models that may be suited for this task.
Operational Evaluation of Air Quality Models Paul D. Sampson Peter Guttorp
Washington at Seattle, University of
predictions, (2) graphical depiction and comparison of spatio-temporal correlation structures determined from Standards (NAAQS) (CFR 40, Part 50). These models--or modeling systems, comprised of emissions, atmospheric
MERCHOP (Merchandising Optimizer): A dynamic programming model for estimating the harvest value of unthinned loblolly and slash pine plantations. Forest Service research paper
Busby, R.L.; Ward, K.B.
A model was devised to estimate the harvest value of unthinned loblolly and slash pine (pinus taeda L. and P. elliottii var. elliottii Englm.) plantations in the west gulf region. The model, MERCHOP, can be used to forecast product volumes and values; the output provided is partitioned into 1-inch tree d.b.h. classes. Using a dynamic programming algorithm, MERCHOP can be used to convert stand tables predicted by USLYCOWG's three-parameter Weibull function into a listing of seven products that maximizes the selling value of the stand, assuming the assumptions used in the analysis are correct.
Biophysical modelling of the effects of inhaled radon progeny on the bronchial epithelium for the estimation of the relationships applied in the two stage clonal expansion model of carcinogenesis
Madas, Bal�zs G
There is a considerable debate between research groups applying the two stage clonal expansion model for lung cancer risk estimation, whether radon exposure affects initiation and transformation or promotion. The objective of the present study is to quantify the effects of radon progeny on these stages with biophysical models. For this purpose, numerical models of mutation induction and clonal growth were applied in order to estimate how initiation, transformation and promotion rates depend on tissue dose rate. It was found that rates of initiation and transformation increase monotonically with dose rate, while effective promotion rate decreases with time, but increases in a supralinear fashion with dose rate. Despite the uncertainty of the results due to the lack of experimental data, present study suggests that effects of radon exposure on both mutational events and clonal growth are significant, and should be considered in epidemiological analyses applying mathematical models of carcinogenesis.
Continental Scale Comparisons of Terrestrial Carbon Sinks Estimated from Satellite Data and Ecosystem Modeling 1982-1998
Kumar, Vipin
ecosystem (tundra and boreal) sinks for atmospheric CO2. Key Words: carbon dioxide, ecosystems, remote "missing sink" for carbon dioxide emissions. Measured atmospheric CO2, 13 C, and O2/N2 distributionsContinental Scale Comparisons of Terrestrial Carbon Sinks Estimated from Satellite Data
654 IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 18, NO. 3, MAY 2010 Model-Based Electrochemical Estimation and
-Based Electrochemical Estimation and Constraint Management for Pulse Operation of Lithium Ion Batteries Kandler A. Smith Technologies, Graduate Automotive Technology Education Pro- gram. This work was performed at the Pennsylvania-mail: email@example.com; firstname.lastname@example.com). C. D. Rahn and C.-Y. Wang are with the Department
Estimation of Absolute Free Energies of Hydration using Continuum Methods: Accuracy of Partial Charge Models and Optimization of Nonpolar Contributions
Rizzo, Robert C.
Estimation of Absolute Free Energies of Hydration using Continuum Methods: Accuracy of Partial, and Irwin D. Kuntz Supporting Information Table S1. Experimental Free Energies of Hydration (Ghyd) in kcal,2-dimethylcyclohexane 1.58 36 trans-1,4-dimethylcyclohexane 2.11 37 ethene 1.28 38 propene 1.32 39 but-1-ene 1.38 40
Estimating Fuel Cycle Externalities: Analytical Methods and Issues, Report 2
Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.
The activities that produce electric power typically range from extracting and transporting a fuel, to its conversion into electric power, and finally to the disposition of residual by-products. This chain of activities is called a fuel cycle. A fuel cycle has emissions and other effects that result in unintended consequences. When these consequences affect third parties (i.e., those other than the producers and consumers of the fuel-cycle activity) in a way that is not reflected in the price of electricity, they are termed ''hidden'' social costs or externalities. They are the economic value of environmental, health and any other impacts, that the price of electricity does not reflect. How do you estimate the externalities of fuel cycles? Our previous report describes a methodological framework for doing so--called the damage function approach. This approach consists of five steps: (1) characterize the most important fuel cycle activities and their discharges, where importance is based on the expected magnitude of their externalities, (2) estimate the changes in pollutant concentrations or other effects of those activities, by modeling the dispersion and transformation of each pollutant, (3) calculate the impacts on ecosystems, human health, and any other resources of value (such as man-made structures), (4) translate the estimates of impacts into economic terms to estimate damages and benefits, and (5) assess the extent to which these damages and benefits are externalities, not reflected in the price of electricity. Each step requires a different set of equations, models and analysis. Analysts generally believe this to be the best approach for estimating externalities, but it has hardly been used! The reason is that it requires considerable analysis and calculation, and to this point in time, the necessary equations and models have not been assembled. Equally important, the process of identifying and estimating externalities leads to a number of complex issues that also have not been fully addressed. This document contains two types of papers that seek to fill part of this void. Some of the papers describe analytical methods that can be applied to one of the five steps of the damage function approach. The other papers discuss some of the complex issues that arise in trying to estimate externalities. This report, the second in a series of eight reports, is part of a joint study by the U.S. Department of Energy (DOE) and the Commission of the European Communities (EC)* on the externalities of fuel cycles. Most of the papers in this report were originally written as working papers during the initial phases of this study. The papers provide descriptions of the (non-radiological) atmospheric dispersion modeling that the study uses; reviews much of the relevant literature on ecological and health effects, and on the economic valuation of those impacts; contains several papers on some of the more complex and contentious issues in estimating externalities; and describes a method for depicting the quality of scientific information that a study uses. The analytical methods and issues that this report discusses generally pertain to more than one of the fuel cycles, though not necessarily to all of them. The report is divided into six parts, each one focusing on a different subject area.
Estimating consumption rates of juvenile sandbar sharks (Carcharhinus plumbeus) in Chesapeake Bay, Virginia, using a bioenergetics model
Dowd, William Wesley; Brill, R W; Bushnell, P G; Musick, J A
error analy- sis of fish bioenergetics models. Can J. Fish.importance of activity in bioenergetics models applied toA. C. Cockcroft. 1990. Bioenergetics of fishes in a high-
Individual heterogeneity in life history processes: Estimation and applications of demographic models to stage-structured arthropod populations
Scranton, Katherine
cois, 2008. Non-linear regression models for approximateparameters. They use non-linear regression of parameters on
The `Multifractal Model' of Turbulence and {\\em A Priori} Estimates in Large-Eddy Simulation, I. Subgrid Flux and Locality of Energy Transfer
Gregory L. Eyink
We establish and discuss {\\em a priori} estimates on subgrid stress and subgrid flux for filtering schemes used in the turbulence modelling method of Large-Eddy Simulation (LES). Our estimates are derived as rigorous consequences of the exact subgrid stress formulae from Navier-Stokes equations under realistic conditions for inertial-range velocity fields, those conjectured in the Parisi-Frisch ``multifractal model.'' The estimates are shown to be an expression of ``local energy cascade,'' i.e. the dominance of local wavevector triads in the energy transfer. We prove that for nearly any reasonable filter function the LES method defines an energy flux in which local triads dominate in individual realizations, due to cancellation of distant triadic contributions by detailed conservation. A somewhat similar observation of Leslie and Quarini on graded filters in the EDQNM closure is shown to be unrelated to the cancellation we establish in Navier-Stokes solutions. The sharp Fourier cutoff filter is one example which does not satisfy the modest conditions of our proof and, in fact, we show that with that filter the energy transfer in individual realizations at arbitrarily high Reynolds number will be dominated by nonlocal, convective sweeping.
Uncertainties of isoprene emissions in the MEGAN model estimated for a coniferous and broad-leaved mixed forest in Southern China
Situ, S.; Wang, Xuemei; Guenther, Alex B.; Zhang, Yanli; Wang, Xinming; Huang, Minjuan; Fan, Qi; Xiong, Zhe
Using local observed emission factor, meteorological data, vegetation 5 information and dynamic MODIS LAI, MEGANv2.1 was constrained to predict the isoprene emission from Dinghushan forest in the Pearl River Delta region during a field campaign in November 2008, and the uncertainties in isoprene emission estimates were quantified by the Monte Carlo approach. The results indicate that MEGAN can predict the isoprene emission reasonably during the campaign, and the mean value of isoprene emission is 2.35 mg m-2 h-1 in daytime. There are high uncertainties associated with the MEGAN inputs and calculated parameters, and the relative error can be as high as -89 to 111% for a 95% confidence interval. The emission factor of broadleaf trees and the activity factor accounting for light and temperature dependence are the most important contributors to the uncertainties in isoprene emission estimated for the Dinghushan forest during the campaign. The results also emphasize the importance of accurate observed PAR and temperature to reduce the uncertainties in isoprene emission estimated by model, because the MEGAN model activity factor accounting for light and temperature dependence is highly sensitive to PAR and temperature.
HYBRID SPEAKER-BASED SEGMENTATION SYSTEM USING MODEL-LEVEL Hyoung-Gook Kim, Daniel Ertelt, Thomas Sikora
Wichmann, Felix
-based and model-based segmentation. Figure 1 depicts the algorithm flow chart. The hybrid segmentation can speaker models. First, silence segments in the input audio recording are detected by the simple energy
SimHydro 2012: Hydraulic modeling and uncertainty, 12-14 September 2012, Sophia Antipolis N. Jean-Baptiste, C. Dore, P-O. Malaterre, J. Sau -Data assimilation for hydraulic state estimation of a development project
Paris-Sud XI, Universit� de
SimHydro 2012: Hydraulic modeling and uncertainty, 12-14 September 2012, Sophia Antipolis � N. Jean-Baptiste, C. Dor�e, P-O. Malaterre, J. Sau - Data assimilation for hydraulic state estimation of a development project Data assimilation for hydraulic state estimation of a development project Assimilation de donn�es
Calibration of floodplain roughness and estimation of flood discharge based on tree-ring evidence and hydraulic modelling
Stoffel, Markus
and Environmental Engineering, Universidad de Los Andes, Bogot�, Colombia d Laboratory of Dendrogeomorphology the Navaluenga flow gauge (Avila Province) as well as a 1D/2D coupled numerical hydraulic model. A total of 49 hydraulic modelling, we cannot find a statistically sig- nificant difference between water depths registered
Development and use of the GREET model to estimate fuel-cycle energy use and emissions of various transportation technologies and fuels
Wang, M.Q.
This report documents the development and use of the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The model, developed in a spreadsheet format, estimates the full fuel- cycle emissions and energy use associated with various transportation fuels for light-duty vehicles. The model calculates fuel-cycle emissions of five criteria pollutants (volatile organic compounds, carbon monoxide, nitrogen oxides, sulfur oxides, and particulate matter measuring 10 microns or less) and three greenhouse gases (carbon dioxide, methane, and nitrous oxide). The model also calculates the total fuel-cycle energy consumption, fossil fuel consumption, and petroleum consumption using various transportation fuels. The GREET model includes 17 fuel cycles: petroleum to conventional gasoline, reformulated gasoline, clean diesel, liquefied petroleum gas, and electricity via residual oil; natural gas to compressed natural gas, liquefied petroleum gas, methanol, hydrogen, and electricity; coal to electricity; uranium to electricity; renewable energy (hydrogen, solar energy, and wind) to electricity; corn, woody biomass, and herbaceous biomass to ethanol; and landfill gases to methanol. This report presents fuel-cycle energy use and emissions for a 2000 model-year car powered by each of the fuels that are produced from the primary energy sources considered in the study.
Techno-Economic Models for Carbon Dioxide Compression, Transport, and Storage & Correlations for Estimating Carbon Dioxide Density and Viscosity
McCollum, David L; Ogden, Joan M
as reported in the Oil & Gas Journal. From this data, theycost data from the Oil & Gas Journal. The Ecofys Models Theas reported in the Oil & Gas Journal. From this data, they
Concentrating Solar Deployment System (CSDS) -- A New Model for Estimating U.S. Concentrating Solar Power (CSP) Market Potential: Preprint
Blair, N.; Mehos, M.; Short, W.; Heimiller, D.
This paper presents the Concentrating Solar Deployment System Model (CSDS). CSDS is a multiregional, multitime-period, Geographic Information System (GIS), and linear programming model of capacity expansion in the electric sector of the United States. CSDS is designed to address the principal market and policy issues related to the penetration of concentrating solar power (CSP) electric-sector technologies. This paper discusses the current structure, capabilities, and assumptions of the model. Additionally, results are presented for the impact of continued research and development (R&D) spending, an extension to the investment tax credit (ITC), and use of a production tax credit (PTC). CSDS is an extension of the Wind Deployment System (WinDS) model created at the National Renewable Energy Laboratory (NREL). While WinDS examines issues related to wind, CSDS is an extension to analyze similar issues for CSP applications. Specifically, a detailed representation of parabolic trough systems with thermal storage has been developed within the existing structure.
Use of multi-sources 10-years quantitative precipitation estimation re-analyses in a lumped rainfall-runoff model.
Paris-Sud XI, Universit� de
of precipitation depths. Indeed, meteorological radar provides spatially distributed rainfall depths information (radars, hourly and daily rain gauges, satellite data, model freezing level heights, etc with rain gauge network. First, a methodology for automated identification and treatment of radar
Estimated Water Flows in 2005: United States
Smith, C A; Belles, R D; Simon, A J
Flow charts depicting water use in the United States have been constructed from publicly available data and estimates of water use patterns. Approximately 410,500 million gallons per day of water are managed throughout the United States for use in farming, power production, residential, commercial, and industrial applications. Water is obtained from four major resource classes: fresh surface-water, saline (ocean) surface-water, fresh groundwater and saline (brackish) groundwater. Water that is not consumed or evaporated during its use is returned to surface bodies of water. The flow patterns are represented in a compact 'visual atlas' of 52 state-level (all 50 states in addition to Puerto Rico and the Virgin Islands) and one national water flow chart representing a comprehensive systems view of national water resources, use, and disposition.
Two dose-estimation models CSA-N288.1 and Nureg 1.109, 1.113 - compared for chronic aquatic releases from nuclear facilities
Sheppard, S C; Peterson, S R
Both the Canadian Standards Association (CSA) and the United States Nuclear Regulatory Commission (US-NRC) have published guidelines for the calculation of doses to the public due to emissions from nuclear facilities. In the sale of CANDU reactors overseas, either of these guidelines may be used as part of the approval process in the recipient country. This study compares the aquatic exposure pathways described in the guidelines. These include direct consumption of contaminated water and food, and exposure to contaminated sediments. The CSA and US-NRC guidelines for estimating dilution of aquatic emissions are of a general nature and the choice of model used to quantify dilution is left to the user. The models prescribed for the different exposure pathways by these two regulatory guides are similar in many attributes. Many of the recommended parameter values are identical and many of the formulations are either identical, or become identical under general conditions. However, despite these similarities, there...
Local error estimates dramatically improve the utility of homology models for solving crystal structures by molecular replacement
Bunk�czi, G�bor; Wallner, Bj�rn; Read, Randy J.
calculated with MUSCLE (Edgar, 2004). ts, homology models were created using ini et al., 2014), based on the template ed as MR models. This step was required iction, since the actual sequence has to be cture and side chains have to be present. selected... , 2014 Published: January 22, 2015 REFERENCES Adams, P.D., Afonine, P.V., Bunko�czi, G., Chen, V.B., Davis, I.W., Echols, N., Headd, J.J., Hung, L.W., Kapral, G.J., Grosse-Kunstleve, R.W., et al. (2010).Nature 473, 540�543. Edgar, R.C. (2004). MUSCLE...
A general model for estimating the economic and production effects of specified pesticide withdrawals: a cotton application
Casey, James Elmer
. Hypothetical Factor-Pactor Model indicating profit maximizing conditions with limited capital and with a variab1e input limitation 24 P2 units, then other inputs would be added until their marginal value poduct was equal to their price. This would...
Cost Estimating, Analysis, and Standardization
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
To establish policy and responsibilities for: (a) developing and reviewing project cost estimates; (b) preparing independent cost estimates and analysis; (c) standardizing cost estimating procedures; and (d) improving overall cost estimating and analytical techniques, cost data bases, cost and economic escalation models, and cost estimating systems. Cancels DOE O 5700.2B, dated 8-5-1983; DOE O 5700.8, dated 5-27-1981; and HQ 1130.1A, dated 12-30-1981. Canceled by DOE O 5700.2D, dated 6-12-1992
A model for determining shelf life, estimating terminal body composition, yield grade and quality grade of feedlot cattle�
Perry, Richard Jay
4. 5 percentage units less fat (21. 64% vs 26, 1% carcass fat) than non-implanted steers of the same carcass weight and rate of gain (350 kg and ADG of 1. 0 kg/d). Fat as a percentage of gain averaged 67. 85, 52. 05 and 39. 59 for non... model which can be used for projecting changes in yield grade and quality grade with performance of cattle in the feedlot over time. The primary objectives of this research were: 1) To determine the "shelf life" of a steer in the feedlot. 2...
Exploring chaos to model the design process
Sharkawy, Ahmed
of design as a sequence of three rational processes (14) 10 Jansson's tsvo space model (15) 4 The different types of constraints within the design process The major processes occuring in Jansson's concept space. 19 6 Figure 6a depicts the skeleton upon... model and how it fits within March's depiction 9 Reduced two variable model and how it fits within Jansson's scheme . . 45 10 Map of case: 3=2. 0, /=50, d=0. 15 47 11 Map of case: %=2. 2, y=50, d=0. 15 48 12 Map of' case: 4=2. 6, @=50, d=0. 15 49...
Exploring chaos to model the design process�
Sharkawy, Ahmed
of design as a sequence of three rational processes (14) 10 Jansson's tsvo space model (15) 4 The different types of constraints within the design process The major processes occuring in Jansson's concept space. 19 6 Figure 6a depicts the skeleton upon... model and how it fits within March's depiction 9 Reduced two variable model and how it fits within Jansson's scheme . . 45 10 Map of case: 3=2. 0, /=50, d=0. 15 47 11 Map of case: %=2. 2, y=50, d=0. 15 48 12 Map of' case: 4=2. 6, @=50, d=0. 15 49...
Best Linear Unbiased Estimate Motivation for BLUE
Fowler, Mark
1 Chapter 6 Best Linear Unbiased Estimate (BLUE) #12;2 Motivation for BLUE Except for Linear Model to a sub-optimal estimate BLUE is one such sub-optimal estimate Idea for BLUE: 1. Restrict estimate) Advantage of BLUE:Needs only 1st and 2nd moments of PDF Mean & Covariance Disadvantages of BLUE: 1. Sub
Linear Constrained Moving Horizon Estimator With Pre-Estimating Observer
Johansen, Tor Arne
in the literature, e.g. Rao et al. (2001, 2003); Alessandri et al. (2003, 2004). The idea of MHE is to estimate of robustness in the presence of uncertainties such as noise, disturbances and modeling errors, see Alessandri in the literature, e.g. Rao et al. (2001, 2003); Alessandri et al. (2003, 2004). The pre-estimator leads
A Monte Carlo Investigation of Three Different Estimation Methods in Multilevel Structural Equation Modeling Under Conditions of Data Nonnormality and Varied Sample Sizes
Byrd, Jimmy
various sample sizes and differing estimators (maximum likelihood, generalized least squares, and weighted least squares). The finding revealed that the regression coefficients were estimated with little to no bias among the study design conditions...
Sun Sensor Model Nikolas Trawny and Stergios Roumeliotis
Roumeliotis, Stergios I.
Sun Sensor Model Nikolas Trawny and Stergios Roumeliotis Department of Computer Science://www.cs.umn.edu/~trawny #12;Sun Sensor Model Nikolas Trawny and Stergios Roumeliotis Department of Computer Science-hole Camera Model The Sun Sensor is represented mathematically by the simple pin-hole camera model, depicted
Estimation of unsaturated zone traveltimes for Rainier Mesa and Shoshone Mountain, Nevada Test Site, Nevada, using a source-responsive preferential-flow model
Brian A. Ebel; John R. Nimmo
Traveltimes for contaminant transport by water from a point in the unsaturated zone to the saturated zone are a concern at Rainier Mesa and Shoshone Mountain in the Nevada Test Site, Nevada. Where nuclear tests were conducted in the unsaturated zone, contaminants must traverse hundreds of meters of variably saturated rock before they enter the saturated zone in the carbonate rock, where the regional groundwater system has the potential to carry them substantial distances to a location of concern. The unsaturated-zone portion of the contaminant transport path may cause a significant delay, in addition to the time required to travel within the saturated zone, and thus may be important in the overall evaluation of the potential hazard from contamination. Downward contaminant transport through the unsaturated zone occurs through various processes and pathways; this can lead to a broad distribution of contaminant traveltimes, including exceedingly slow and unexpectedly fast extremes. Though the bulk of mobile contaminant arrives between the time-scale end members, the fastest contaminant transport speed, in other words the speed determined by the combination of possible processes and pathways that would bring a measureable quantity of contaminant to the aquifer in the shortest time, carries particular regulatory significance because of its relevance in formulating the most conservative hazard-prevention scenarios. Unsaturated-zone flow is usually modeled as a diffusive process responding to gravity and pressure gradients as mediated by the unsaturated hydraulic properties of the materials traversed. The mathematical formulation of the diffuse-flow concept is known as Richards' equation, which when coupled to a solute transport equation, such as the advection-dispersion equation, provides a framework to simulate contaminant migration in the unsaturated zone. In recent decades awareness has increased that much fluid flow and contaminant transport within the unsaturated zone takes place as preferential flow, faster than would be predicted by the coupled Richards' and advection-dispersion equations with hydraulic properties estimated by traditional means. At present the hydrologic community has not achieved consensus as to whether a modification of Richards' equation, or a fundamentally different formulation, would best quantify preferential flow. Where the fastest contaminant transport speed is what needs to be estimated, there is the possibility of simplification of the evaluation process. One way of doing so is by a two-step process in which the first step is to evaluate whether significant preferential flow and solute transport is possible for the media and conditions of concern. The second step is to carry out (a) a basic Richards' and advection-dispersion equation analysis if it is concluded that preferential flow is not possible or (b) an analysis that considers only the fastest possible preferential-flow processes, if preferential flow is possible. For the preferential-flow situation, a recently published model describable as a Source-Responsive Preferential-Flow (SRPF) model is an easily applied option. This report documents the application of this two-step process to flow through the thick unsaturated zones of Rainier Mesa and Shoshone Mountain in the Nevada Test Site. Application of the SRPF model involves distinguishing between continuous and intermittent water supply to preferential flow paths. At Rainier Mesa and Shoshone Mountain this issue is complicated by the fact that contaminant travel begins at a location deep in the subsurface, where there may be perched water that may or may not act like a continuous supply, depending on such features as the connectedness of fractures and the nature of impeding layers. We have treated this situation by hypothesizing both continuous and intermittent scenarios for contaminant transport to the carbonate aquifer and reporting estimation of the fastest speed for both of these end members.
Harmonizing Systems and Software Cost Estimation
Wang, Gan
The objective of this paper is to examine the gaps and overlaps between software and systems engineering cost models with intent to harmonize the estimates in engineering engineering estimation. In particular, we evaluate ...
Econometric Analysis on Efficiency of Estimator
M. Khoshnevisan; F. Kaymram; Housila P. Singh; Rajesh Singh; Florentin Smarandache
This paper investigates the efficiency of an alternative to ratio estimator under the super population model with uncorrelated errors and a gamma-distributed auxiliary variable. Comparisons with usual ratio and unbiased estimators are also made.
Bayesian estimation of resistivities from seismic velocities�
Werthm�ller, Dieter
I address the problem of finding a background model for the estimation of resistivities in the earth from controlled-source electromagnetic (CSEM) data by using seismic data and well logs as constraints. Estimation of ...
Estimating radiogenic cancer risks
This document presents a revised methodology for EPA`s estimation of cancer risks due to low-LET radiation exposures in light of information that has become available since the publication of BIER III, especially new information on the Japanese atomic bomb survivors. For most cancer sites, the risk model is one in which the age-specific relative risk coefficients are obtained by taking the geometric mean of coefficients derived from the atomic bomb survivor data employing two different methods for transporting risks from Japan to the U.S. (multiplicative and NIH projection methods). Using 1980 U.S. vital statistics, the risk models are applied to estimate organ-specific risks, per unit dose, for a stationary population.
The Role Model Estimator Revisited
Sayir, Jossy
in the constraint. Let us denote by M = [mij ] the 9�9 matrix of incoming messages into a constraint node, where mij = P (Xi = j|Y i) where Y i generically denotes the set of channel observations that led to the incoming message on the i-th branch... : http://en.wikipedia.org/wiki/Sudoku [8] �Permanent,� article in Wikipedia. [Online]. Available: http://en.wikipedia.org/wiki/Permanent [9] T. T. Nguyen and L. Lampe, �Bit-interleaved coded modulation with mismatched decoding metrics,� IEEE Trans. Commun...
Categorical missing data imputation for software cost estimation by
Bae, Doo-Hwan
the cost usually begins by building estimation model Apply estimation method to historical data setsCategorical missing data imputation for software cost estimation by multinomial logistic regression Organization type Banking, Construction, Gas, Defense, Engergy, ... bartype Business area type Accounting
A TIME ESTIMATE FOR CONSOLIDATION AND DISINTEGRATION OF AN ASTEROID RUBBLE PILE. THE SIMPLEST MODEL. A PRELIMINARY ANALYSIS. G.A. Leikin, A.N. and Sanovich, Sternberg, State
A TIME ESTIMATE FOR CONSOLIDATION AND DISINTEGRATION OF AN ASTEROID � RUBBLE PILE. THE SIMPLEST model shows that an asteroid � rubble pile evolves, depending on the parameter V2 d (where V � rubble pile to survive for a long time, and on the other hand, even without tidal effects, it prevents
Flux recovery and a posteriori error estimators
bility and the local efficiency bounds for this estimator are established provided that the ... For simple model problems, the energy norm of the true error is equal.
Estimating Temperature Distributions In Geothermal Areas Using...
an analytical model, showing that the errors in neuronet temperature estimates based on well log data derive from: (a) the neuronet "education level" (which depends on the amount...
May 4, 2007 10:5 WSPC/Trim Size: 9in x 6in for Review Volume chapter10 SURVIVAL MODEL AND ESTIMATION FOR LUNG
Hong, Don
AND ESTIMATION FOR LUNG CANCER PATIENTS Xingchen Yuana , Don Hongb , and Yu Shyrc,d a Fermilab, Batavia, IL 60510, Nashville, TN 37232, USA d Department of Statistics, National Cheng Kung University, Taiwan, ROC Lung cancer for a group of lung cancer patients for survival study, the covariates in the hazard function are estimated
Contribution to the development of DOE ARM Climate Modeling Best Estimate Data (CMBE) products: Satellite data over the ARM permanent and AMF sites: Final Report
Xie, B; Dong, X; Xie, S
To support the LLNL ARM infrastructure team Climate Modeling Best Estimate (CMBE) data development, the University of North Dakota (UND)'s group will provide the LLNL team the NASA CERES and ISCCP satellite retrieved cloud and radiative properties for the periods when they are available over the ARM permanent research sites. The current available datasets, to date, are as follows: the CERES/TERRA during 200003-200812; the CERES/AQUA during 200207-200712; and the ISCCP during 199601-200806. The detailed parameters list below: (1) CERES Shortwave radiative fluxes (net and downwelling); (2) CERES Longwave radiative fluxes (upwelling) - (items 1 & 2 include both all-sky and clear-sky fluxes); (3) CERES Layered clouds (total, high, middle, and low); (4) CERES Cloud thickness; (5) CERES Effective cloud height; (6) CERES cloud microphysical/optical properties; (7) ISCCP optical depth cloud top pressure matrix; (8) ISCCP derived cloud types (r.g., cirrus, stratus, etc.); and (9) ISCCP infrared derived cloud top pressures. (10) The UND group shall apply necessary quality checks to the original CERES and ISCCP data to remove suspicious data points. The temporal resolution for CERES data should be all available satellite overpasses over the ARM sites; for ISCCP data, it should be 3-hourly. The spatial resolution is the closest satellite field of view observations to the ARM surface sites. All the provided satellite data should be in a format that is consistent with the current ARM CMBE dataset so that the satellite data can be easily merged into the CMBE dataset.
Characterization of the Femoral Neck Region�s Reponse to the Rat Hindlimb Unloading Model through Tomographic Scanning, Mechanical Testing and Estimated Strengths�
Kupke, Joshua Scott
quantitative computed tomography (pQCT), mechanical testing in two different loading conditions, and estimated strength indices. Adult male Sprague-Dawley rats (6-mo) were grouped into baseline (BL), ambulatory cage control (CC) and hindlimb unloaded (HU); HU...
Model independent foreground power spectrum estimation using WMAP 5-year data Tuhin Ghosh,1,* Rajib Saha,1,2,3,4,
Souradeep, Tarun
Saha,1,2,3,4, Pankaj Jain,4, and Tarun Souradeep1,x 1 IUCAA, Post Bag 4, Ganeshkhind, Pune-411007 of CMB power spectrum estimation was proposed by Saha et al. 2006. This methodology demonstrates
ARM Climate Modeling Best Estimate Barrow, AK with additional satellite product (ARMBE-CLDRAD NSAC1 V2.1a)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Manus Island, PNG with additional satellite product (ARMBE-CLDRAD TWPC1 V2.1a)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Darwin, AU with additional satellite product (ARMBE-CLDRAD TWPC3 V2.1a)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru with additional satellite product (ARMBE-CLDRAD TWPC2 V2.1a)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
Estimated United States Residential Energy Use in 2005
Smith, C A; Johnson, D M; Simon, A J; Belles, R D
A flow chart depicting energy flow in the residential sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 11,000 trillion British Thermal Units (trBTUs) of electricity and fuels were used throughout the United States residential sector in lighting, electronics, air conditioning, space heating, water heating, washing appliances, cooking appliances, refrigerators, and other appliances. The residential sector is powered mainly by electricity and natural gas. Other fuels used include petroleum products (fuel oil, liquefied petroleum gas and kerosene), biomass (wood), and on-premises solar, wind, and geothermal energy. The flow patterns represent a comprehensive systems view of energy used within the residential sector.
Estimated Carbon Dioxide Emissions in 2008: United States
Smith, C A; Simon, A J; Belles, R D
Flow charts depicting carbon dioxide emissions in the United States have been constructed from publicly available data and estimates of state-level energy use patterns. Approximately 5,800 million metric tons of carbon dioxide were emitted throughout the United States for use in power production, residential, commercial, industrial, and transportation applications in 2008. Carbon dioxide is emitted from the use of three major energy resources: natural gas, coal, and petroleum. The flow patterns are represented in a compact 'visual atlas' of 52 state-level (all 50 states, the District of Columbia, and one national) carbon dioxide flow charts representing a comprehensive systems view of national CO{sub 2} emissions. Lawrence Livermore National Lab (LLNL) has published flow charts (also referred to as 'Sankey Diagrams') of important national commodities since the early 1970s. The most widely recognized of these charts is the U.S. energy flow chart (http://flowcharts.llnl.gov). LLNL has also published charts depicting carbon (or carbon dioxide potential) flow and water flow at the national level as well as energy, carbon, and water flows at the international, state, municipal, and organizational (i.e. United States Air Force) level. Flow charts are valuable as single-page references that contain quantitative data about resource, commodity, and byproduct flows in a graphical form that also convey structural information about the system that manages those flows. Data on carbon dioxide emissions from the energy sector are reported on a national level. Because carbon dioxide emissions are not reported for individual states, the carbon dioxide emissions are estimated using published energy use information. Data on energy use is compiled by the U.S. Department of Energy's Energy Information Administration (U.S. EIA) in the State Energy Data System (SEDS). SEDS is updated annually and reports data from 2 years prior to the year of the update. SEDS contains data on primary resource consumption, electricity generation, and energy consumption within each economic sector. Flow charts of state-level energy usage and explanations of the calculations and assumptions utilized can be found at: http://flowcharts.llnl.gov. This information is translated into carbon dioxide emissions using ratios of carbon dioxide emissions to energy use calculated from national carbon dioxide emissions and national energy use quantities for each particular sector. These statistics are reported annually in the U.S. EIA's Annual Energy Review. Data for 2008 (US. EIA, 2010) was updated in August of 2010. This is the first presentation of a comprehensive state-level package of flow charts depicting carbon dioxide emissions for the United States.
8th International Conference on Probability Methods Applied to Power Systems, Ames Iowa, September 2004 Estimating Failure Propagation in Models of
Reliability Technology Solutions and funding in part by the Assistant Secretary for Energy Efficiency Vickie E. Lynch Bertrand Nkei David E. Newman Abstract-- We compare and test statistical estimates and Renewable Energy, Office of Power Technologies, Transmission Reliability Program of the U.S. Department
Rating curves and estimation of average water depth at the upper Negro River based on satellite altimeter data and modeled discharges
Paris-Sud XI, Universit� de
1 Rating curves and estimation of average water depth at the upper Negro River based on satellite for 21 ``virtual gauge stations'' located at the upper Negro River (Amazon Basin, Brazil). A virtual station can be defined as any crossing of water body surface (i.e., large rivers) by radar altimeter
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
This chapter focuses on the components (or elements) of the cost estimation package and their documentation.
MODEL OF THE .MIGRATION OF ALBACORE IN THE NORTH PACIFIC OCEAN .By TAMIO OTSU and RICHARD N. UCHIDA of the migration of albacore in the North Pacific Ocean has been developed. This model is consistent with the hypothesis that there is a single population of albacore in the North Pacific Ocean. . The model depicts
Check Estimates and Independent Costs
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
Check estimates and independent cost estimates (ICEs) are tools that can be used to validate a cost estimate. Estimate validation entails an objective review of the estimate to ensure that estimate criteria and requirements have been met and well documented, defensible estimate has been developed. This chapter describes check estimates and their procedures and various types of independent cost estimates.
Kernel Density Based Linear Regression Estimate and Zhibiao Zhao
Zhao, Zhibiao
Kernel Density Based Linear Regression Estimate Weixin Yao and Zhibiao Zhao Abstract For linear regression models with non-normally distributed errors, the least squares estimate (LSE) will lose some words: EM algorithm, Kernel density estimate, Least squares estimate, Linear regression, Maximum
State energy data report 1994: Consumption estimates
This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.
Tight gas reservoirs: A visual depiction
Not Available
Future gas supplies in the US will depend on an increasing contribution from unconventional sources such as overpressured and tight gas reservoirs. Exploitation of these resources and their conversion to economically producible gas reserves represents a major challenge. Meeting this challenge will require not only the continuing development and application of new technologies, but also a detailed understanding of the complex nature of the reservoirs themselves. This report seeks to promote understanding of these reservoirs by providing examples. Examples of gas productive overpressured tight reservoirs in the Greater Green River Basin, Wyoming are presented. These examples show log data (raw and interpreted), well completion and stimulation information, and production decline curves. A sampling of wells from the Lewis and Mesaverde formations are included. Both poor and good wells have been chosen to illustrate the range of productivity that is observed. The second section of this document displays decline curves and completion details for 30 of the best wells in the Greater Green River Basin. These are included to illustrate the potential that is present when wells are fortuitously located with respect to local stratigraphy and natural fracturing, and are successfully hydraulically fractured.
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
The chapter describes the estimates required on government-managed projects for both general construction and environmental management.
A Configurable Reference Modelling Language1 M. Rosemanna
van der Aalst, Wil
, Configuration, Event-driven Process Chains 1 This research project is financially supported by SAP Corporate reference models "just" depict the possible system capabilities and cannot sufficiently guide the project, Eindhoven, The Netherlands, email@example.com Abstract Enterprise Systems (ES) are comprehensive off
Modelling a Respiratory Central Pattern Generator Neuron in Lymnaea stagnalis
Campbell, Sue Ann
Modelling a Respiratory Central Pattern Generator Neuron in Lymnaea stagnalis Sharene D. Bungay, is characterized in part by its ability to take in oxygen both cutaneously and aerially (via its rudi- mentary lung by a 3-neuron central pattern generator (CPG) as depicted in Figure 1. Syed et al. [1, 2] were able
Systems Engineering Cost Estimation
Bryson, Joanna J.
on project, human capital impact. 7 How to estimate Cost? Difficult to know what we are building early on1 Systems Engineering Lecture 3 Cost Estimation Dr. Joanna Bryson Dr. Leon Watts University of Bath: Contrast approaches for estimating software project cost, and identify the main sources of cost
Fracture compliance estimation using borehole tube waves
Bakku, Sudhish Kumar
We tested two models, one for tube-wave generation and the other for tube-wave attenuation at a fracture intersecting a borehole that can be used to estimate fracture compliance, fracture aperture, and lateral extent. In ...
Broader source: Energy.gov [DOE]
This simple spreadsheet model estimates either the flow rate required to produce a specified level of power output, or the power output that can be produced from a specified flow rate.
Application of the CALIOP Layer Product to Evaluate the Vertical Distribution of Aerosols Estimated by Global Models: AeroCom Phase I Results
Koffi, Brigitte; Schultz, Michael; Breon, Francois-Marie; Griesfeller, Jan; Winker, D.; Balkanski, Y.; Bauer, Susanne E.; Berntsen, T.; Chin, Mian; Collins, William D.; Dentener, Frank; Diehl, Thomas; Easter, Richard C.; Ghan, Steven J.; Ginoux, P.; Gong, S.; Horowitz, L.; Iversen, T.; Kirkevag, A.; Koch, Dorothy; Krol, Maarten; Myhre, G.; Stier, P.; Takemura, T.
The CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) layer product is used for a multimodel evaluation of the vertical distribution of aerosols. Annual and seasonal aerosol extinction profiles are analyzed over 13 sub-continental regions representative of industrial, dust, and biomass burning pollution, from CALIOP 2007-2009 observations and from AeroCom (Aerosol Comparisons between Observations and Models) 2000 simulations. An extinction mean height diagnostic (Z{sub a}) is defined to quantitatively assess the models performance. It is calculated over the 0-6 km and 0-10 km altitude ranges by weighting the altitude of each 100 m altitude layer by its aerosol extinction coefficient. The mean extinction profiles derived from CALIOP layer products provide consistent regional and seasonal specificities and a low inter-annual variability. While the outputs from most models are significantly correlated with the observed Z{sub a} climatologies, some do better than others, and 2 of the 12 models perform particularly well in all seasons. Over industrial and maritime regions, most models show higher Z{sub a} than observed by CALIOP, whereas over the African and Chinese dust source regions, Z{sub a} is underestimated during Northern Hemisphere Spring and Summer. The positive model bias in Z{sub a} is mainly due to an overestimate of the extinction above 6 km. Potential CALIOP and model limitations, and methodological factors that might contribute to the differences are discussed.
Statistical estimation of water distribution system pipe break risk
Yamijala, Shridhar
and maintenance decisions. A number of statistical methods have been proposed for this estimation problem. This thesis focuses on comparing these statistical models on the basis of short time histories. The goals of this research are to estimate the likelihood...
Satellite-based estimates of net radiation and modeling the role of topography and vegetation on inter-annual hydro-climatology
Bisht, Gautam
The Fourth Assessment Report of the Intergovernmental Panel on Climate Change acknowledged that the lack of relevant observations in various regions of the world is a crucial gap in understanding and modeling impacts of ...
Stretched Exponential Decline Model as a Probabilistic and Deterministic Tool for Production Forecasting and Reserve Estimation in Oil and Gas Shales
Akbarnejad Nesheli, Babak
stabilized production forecast than traditional DCA models and in this work it is shown that it produces unchanging EUR forecasts after only two-three years of production data are available in selected reservoirs, notably the Barnett Shale...
Conceptual Model Summary Report Simulation Framework for Regional Geologic CO{sub 2} Storage Along Arches Province of Midwestern United States
A conceptual model was developed for the Arches Province that integrates geologic and hydrologic information on the Eau Claire and Mt. Simon formations into a geocellular model. The conceptual model describes the geologic setting, stratigraphy, geologic structures, hydrologic features, and distribution of key hydraulic parameters. The conceptual model is focused on the Mt. Simon sandstone and Eau Claire formations. The geocellular model depicts the parameters and conditions in a numerical array that may be imported into the numerical simulations of carbon dioxide (CO{sub 2}) storage. Geophysical well logs, rock samples, drilling logs, geotechnical test results, and reservoir tests were evaluated for a 500,000 km{sup 2} study area centered on the Arches Province. The geologic and hydraulic data were integrated into a three-dimensional (3D) grid of porosity and permeability, which are key parameters regarding fluid flow and pressure buildup due to CO{sub 2} injection. Permeability data were corrected in locations where reservoir tests have been performed in Mt. Simon injection wells. The final geocellular model covers an area of 600 km by 600 km centered on the Arches Province. The geocellular model includes a total of 24,500,000 cells representing estimated porosity and permeability distribution. CO{sub 2} injection scenarios were developed for on-site and regional injection fields at rates of 70 to 140 million metric tons per year.
Models of thin discs and spheroidal haloes with masses in a linear relationship: mass estimates for NGC4389 and UGC6969
Guillermo A. Gonz�lez; J. Ib��ez; Jerson I. Reina
A family of models of thin discs and spheroidal haloes with masses in a linear relationship is presented. The models are obtained by considering the gravitational potential as the superposition of two independent components, a potential generated by the thin galactic disc and a potential generated by the spheroidal halo. The models leads to an expression for the circular velocity that can be adjusted very accurately to the observed rotation curves of some specific galaxies, in such a way that the models are stable against radial and vertical perturbations. Two particular models for galaxies NGC4389 and UGC6969 are obtained by adjusting the circular velocity with data taken from the recent paper by Verheijen & Sancici (2001). The values of the halo mass, the disc mass and the total mass for these two galaxies are computed in such a way that we obtain a very narrow interval of values for these quantities. Furthermore, the values of masses here obtained are in perfect agreement with the expected order of magnitude and with the relative order of magnitude between the halo mass and the disc mass.
PSM: Lithium-Ion Battery State of Charge (SOC) and Critical Surface Charge (CSC) Estimation using an Electrochemical Model-driven
Stefanopoulou, Anna
modeling is connected with the hybrid vehicle design, scale-up, optimization and control issues of Hybrid characteristics to be widely used in the hybrid vehicles, thanks to its best energy-to-weight ratios, no memory. INTRODUCTION Lithium-ion battery is the core of new plug-in hybrid- electrical vehicles (PHEV) as well
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
Specialty costs are those nonstandard, unusual costs that are not typically estimated. Costs for research and development (R&D) projects involving new technologies, costs associated with future regulations, and specialty equipment costs are examples of specialty costs. This chapter discusses those factors that are significant contributors to project specialty costs and methods of estimating costs for specialty projects.
Cooling load estimation methods
McFarland, R.D.
Ongoing research on quantifying the cooling loads in residential buildings, particularly buildings with passive solar heating systems, is described. Correlations are described that permit auxiliary cooling estimates from monthly average insolation and weather data. The objective of the research is to develop a simple analysis method, useful early in design, to estimate the annual cooling energy required of a given building.
Optimization Online - Sparse/Robust Estimation and Kalman ...
Aleksandr Aravkin
Feb 29, 2012 ... Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory. Aleksandr�...
Modeling plankton dynamics during a Prymnesium parvum bloom: The importance of inflows and allelopathic relationships on bloom dynamics
Hewitt, Natalie Case
further research. 8 2. METHODS 2.1 Model Design The model is constructed of ordinary differential equations, solved using MatlabTM?s fourth-order Runge-Kutta methods(The Math Works, 2009) and uses a carbon currency to depict two phytoplankton...
Estimating exposure of terrestrial wildlife to contaminants
Sample, B.E.; Suter, G.W. II
This report describes generalized models for the estimation of contaminant exposure experienced by wildlife on the Oak Ridge Reservation. The primary exposure pathway considered is oral ingestion, e.g. the consumption of contaminated food, water, or soil. Exposure through dermal absorption and inhalation are special cases and are not considered hereIN. Because wildlife mobile and generally consume diverse diets and because environmental contamination is not spatial homogeneous, factors to account for variation in diet, movement, and contaminant distribution have been incorporated into the models. To facilitate the use and application of the models, life history parameters necessary to estimate exposure are summarized for 15 common wildlife species. Finally, to display the application of the models, exposure estimates were calculated for four species using data from a source operable unit on the Oak Ridge Reservation.
Cardiovascular Signal Decomposition and Estimation with the Extended Kalman Smoother
Cardiovascular Signal Decomposition and Estimation with the Extended Kalman Smoother James Mc of cardiovascular signals that can be used with the extended Kalman filter or smoother to simultaneously estimate with the extended Kalman filter and smoother to estimate and track all the model parameters of interest including
Rank-Based Estimation for GARCH Processes Beth Andrews
Andrews, Beth
Rank-Based Estimation for GARCH Processes Beth Andrews Northwestern University September 7, 2011 Abstract We consider a rank-based technique for estimating GARCH model parameters, some of which are scale transformations of conventional GARCH parameters. The estimators are obtained by minimizing a rank-based residual
Estimation of building occupancy levels through environmental signals deconvolution
Johansson, Karl Henrik
, and ventilation actuation signals in order to identify a dynamic model. The building occupancy estimation problem Abstract We address the problem of estimating the occupancy lev- els in rooms using the information is formulated as a regularized deconvolution problem, where the estimated occupancy is the input that, when
A simple method to estimate interwell autocorrelation
Pizarro, J.O.S.; Lake, L.W. [Univ. of Texas, Austin, TX (United States)
The estimation of autocorrelation in the lateral or interwell direction is important when performing reservoir characterization studies using stochastic modeling. This paper presents a new method to estimate the interwell autocorrelation based on parameters, such as the vertical range and the variance, that can be estimated with commonly available data. We used synthetic fields that were generated from stochastic simulations to provide data to construct the estimation charts. These charts relate the ratio of areal to vertical variance and the autocorrelation range (expressed variously) in two directions. Three different semivariogram models were considered: spherical, exponential and truncated fractal. The overall procedure is demonstrated using field data. We find that the approach gives the most self-consistent results when it is applied to previously identified facies. Moreover, the autocorrelation trends follow the depositional pattern of the reservoir, which gives confidence in the validity of the approach.
Jobs and Economic Development Modeling
Broader source: Energy.gov [DOE]
Project objective: Develop models to estimate jobs and economic impacts from geothermal project development and operation.
Estimating Power System Dynamic States Using Extended Kalman Filter
Huang, Zhenyu; Schneider, Kevin P.; Nieplocha, Jaroslaw; Zhou, Ning
Abstract�The state estimation tools which are currently deployed in power system control rooms are based on a steady state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper investigates the application of Extended Kalman Filtering techniques for estimating dynamic states in the state estimation process. The new formulated �dynamic state estimation� includes true system dynamics reflected in differential equations, not like previously proposed �dynamic state estimation� which only considers the time-variant snapshots based on steady state modeling. This new dynamic state estimation using Extended Kalman Filter has been successfully tested on a multi-machine system. Sensitivity studies with respect to noise levels, sampling rates, model errors, and parameter errors are presented as well to illustrate the robust performance of the developed dynamic state estimation process.
Statistical Estimation of Quantum Tomography Protocols Quality
Yu. I. Bogdanov; G. Brida; M. Genovese; S. P. Kulik; E. V. Moreva; A. P. Shurupov
A novel operational method for estimating the efficiency of quantum state tomography protocols is suggested. It is based on a-priori estimation of the quality of an arbitrary protocol by means of universal asymptotic fidelity distribution and condition number, which takes minimal value for better protocol. We prove the adequacy of the method both with numerical modeling and through the experimental realization of several practically important protocols of quantum state tomography.
Quantum risk-sensitive estimation and robustness
Naoki Yamamoto; Luc Bouten
This paper studies a quantum risk-sensitive estimation problem and investigates robustness properties of the filter. This is a direct extension to the quantum case of analogous classical results. All investigations are based on a discrete approximation model of the quantum system under consideration. This allows us to study the problem in a simple mathematical setting. We close the paper with some examples that demonstrate the robustness of the risk-sensitive estimator.
State energy data report 1993: Consumption estimates
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public; and (2) to provide the historical series necessary for EIA`s energy models.
State energy data report 1995 - consumption estimates
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public, and (2) to provide the historical series necessary for EIA`s energy models.
State Energy Data Report, 1991: Consumption estimates
Not Available
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to the Government, policy makers, and the public; and (2) to provide the historical series necessary for EIA`s energy models.
A conceptual model and preliminary estimate of potential tritium migration from the Benham (U-20c) site, Pahute Mesa, Nevada Test Site
Brikowski, T.; Mahin, G. [Nevada Univ., Reno, NV (United States). Water Resources Center
U-20c is the site of a large below-water-table nuclear test near the Nevada Test Site boundary. A conceptual model of potential groundwater migration of tritium from U-20c is constructed and quantitatively evaluated in this report. The lower portion of the collapse chimney at Benham is expected to intersect 200 m of permeable rhyolite lava, overlain by similar thicknesses of low-permeability zeolitized bedded tuff, then permeable welded tuff. Vertical groundwater flow through the chimney is predicted to be minimal, horizontal transport should be controlled by the regional groundwater flow. Analytic solutions treating only advective transport indicate 1 to 2 km of tritium movement (95% confidence interval 0.7--2.5 km) within 5 years after test-related pressure-temperature transients have dissipated. This point lies at the axis of a potentiometric surface trough along the west edge of Area 20, Nevada Test Site. Within 25 years, movement is predicted to extend to 3 km (95% confidence interval 2--5 km) approximately to the intersection of the trough and the Nevada Test Site boundary. Considering the effects of radioactive decay, but not dispersion, plume concentration would fall below Safe Drinking Water Act standards by 204 years, at a predicted distance of 11 km (95% confidence interval 7--31 km). This point is located in the eastern portion of the Timber Mountain Caldera moat within the Nellis Air Force Range (military bombing range).
Distributed Energy Resources Market Diffusion Model
Maribu, Karl Magnus; Firestone, Ryan; Marnay, Chris; Siddiqui,Afzal S.
Distributed generation (DG) technologies, such as gas-fired reciprocating engines and microturbines, have been found to be economically beneficial in meeting commercial-sector electrical, heating, and cooling loads. Even though the electric-only efficiency of DG is lower than that offered by traditional central stations, combined heat and power (CHP) applications using recovered heat can make the overall system energy efficiency of distributed energy resources (DER) greater. From a policy perspective, however, it would be useful to have good estimates of penetration rates of DER under various economic and regulatory scenarios. In order to examine the extent to which DER systems may be adopted at a national level, we model the diffusion of DER in the US commercial building sector under different technical research and technology outreach scenarios. In this context, technology market diffusion is assumed to depend on the system's economic attractiveness and the developer's knowledge about the technology. The latter can be spread both by word-of-mouth and by public outreach programs. To account for regional differences in energy markets and climates, as well as the economic potential for different building types, optimal DER systems are found for several building types and regions. Technology diffusion is then predicted via two scenarios: a baseline scenario and a program scenario, in which more research improves DER performance and stronger technology outreach programs increase DER knowledge. The results depict a large and diverse market where both optimal installed capacity and profitability vary significantly across regions and building types. According to the technology diffusion model, the West region will take the lead in DER installations mainly due to high electricity prices, followed by a later adoption in the Northeast and Midwest regions. Since the DER market is in an early stage, both technology research and outreach programs have the potential to increase DER adoption, and thus, shift building energy consumption to a more efficient alternative.
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
This Guide provides uniform guidance and best practices that describe the methods and procedures that could be used in all programs and projects at DOE for preparing cost estimates. No cancellations.
Estimation of food consumption
Callaway, J.M. Jr.
The research reported in this document was conducted as a part of the Hanford Environmental Dose Reconstruction (HEDR) Project. The objective of the HEDR Project is to estimate the radiation doses that people could have received from operations at the Hanford Site. Information required to estimate these doses includes estimates of the amounts of potentially contaminated foods that individuals in the region consumed during the study period. In that general framework, the objective of the Food Consumption Task was to develop a capability to provide information about the parameters of the distribution(s) of daily food consumption for representative groups in the population for selected years during the study period. This report describes the methods and data used to estimate food consumption and presents the results developed for Phase I of the HEDR Project.
Operated device estimation framework
Rengarajan, Janarthanan
Protective device estimation is a challenging task because there are numerous protective devices present in a typical distribution system. Among various protective devices, auto-reclosers and fuses are the main overcurrent protection on distribution...
FY 2015 FY 2016 FY 2017 FY 2013 President's Budget Request 3,821.2 3,712.8 3,932.8 4,076.5 4,076.5 4 Estimate Budget Authority (in $ millions) FY 2011 FY 2012 FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 FY 2013EXPLORATION EXP-1 Actual Estimate Budget Authority (in $ millions) FY 2011 FY 2012 FY 2013 FY 2014
1. INTRODUCTION Geomorphic models have a wide range of capabilities in
realistic, color, 3D, and/or animated graphics, modelers may become overenthusiastic about what they can for the realism they see depicted in such graphics, make connec- tions that are not reasonable, and come to expect.g., investigations of charm- anticharm asymmetries in high energy photoproduction Prediction in Geomorphology
Seismic fragility estimates for reinforced concrete framed buildings
Ramamoorthy, Sathish Kumar
story drift given the spectral acceleration at the fundamental period of the building. The unknown parameters of the demand models are estimated using the simulated response data obtained from nonlinear time history analyses of the structural models...
Technical Report 2014-15 Lugre Tire Model for HMMWV
Negrut, Dan
. An example of an all-terrain tire that can be used on HMMWV is depicted in figure 1. Figure 1. A Goodyear tire 37/12.50R17LT (http://www.goodyear.com/). Tires can be modelled in a number of ways in computerTechnical Report 2014-15 Lugre Tire Model for HMMWV Aki Mikkola October 21, 2014 #12;2 Abstract
Local Harmonic Estimation in Musical Sound Rafael A. IRIZARRY
Irizarry, Rafael A.
Local Harmonic Estimation in Musical Sound Signals Rafael A. IRIZARRY Statistical modeling so a local harmonic model that tracks changes in pitch and in the amplitudes of the harmonics is fit estimates of the harmonic signal and of the noise signal. Different musical composition applications may
MELE: Maximum Entropy Leuven Estimators
Paris, Quirino
of the Generalized Maximum Entropy Estimator of the Generaland Douglas Miller, Maximum Entropy Econometrics, Wiley andCalifornia Davis MELE: Maximum Entropy Leuven Estimators by
Thermodynamic estimation: Ionic materials
Glasser, Leslie, E-mail: email@example.com
Thermodynamics establishes equilibrium relations among thermodynamic parameters (�properties�) and delineates the effects of variation of the thermodynamic functions (typically temperature and pressure) on those parameters. However, classical thermodynamics does not provide values for the necessary thermodynamic properties, which must be established by extra-thermodynamic means such as experiment, theoretical calculation, or empirical estimation. While many values may be found in the numerous collected tables in the literature, these are necessarily incomplete because either the experimental measurements have not been made or the materials may be hypothetical. The current paper presents a number of simple and relible estimation methods for thermodynamic properties, principally for ionic materials. The results may also be used as a check for obvious errors in published values. The estimation methods described are typically based on addition of properties of individual ions, or sums of properties of neutral ion groups (such as �double� salts, in the Simple Salt Approximation), or based upon correlations such as with formula unit volumes (Volume-Based Thermodynamics). - Graphical abstract: Thermodynamic properties of ionic materials may be readily estimated by summation of the properties of individual ions, by summation of the properties of �double salts�, and by correlation with formula volume. Such estimates may fill gaps in the literature, and may also be used as checks of published values. This simplicity arises from exploitation of the fact that repulsive energy terms are of short range and very similar across materials, while coulombic interactions provide a very large component of the attractive energy in ionic systems. Display Omitted - Highlights: � Estimation methods for thermodynamic properties of ionic materials are introduced. � Methods are based on summation of single ions, multiple salts, and correlations. � Heat capacity, entropy, lattice energy, enthalpy, Gibbs energy values are available.
Estimation of hydrologic properties of an unsaturated, fractured rock mass
Klavetter, E.A.; Peters, R.R.
In this document, two distinctly different approaches are used to develop continuum models to evaluate water movement in a fractured rock mass. Both models provide methods for estimating rock-mass hydrologic properties. Comparisons made over a range of different tuff properties show good qualitative and quantitative agreement between estimates of rock-mass hydrologic properties made by the two models. This document presents a general discussion of: (1) the hydrology of Yucca Mountain, and the conceptual hydrological model currently being used for the Yucca Mountain site, (2) the development of two models that may be used to estimate the hydrologic properties of a fractured, porous rock mass, and (3) a comparison of the hydrologic properties estimated by these two models. Although the models were developed in response to hydrologic characterization requirements at Yucca Mountain, they can be applied to water movement in any fractured rock mass that satisfies the given assumptions.
Building unbiased estimators from non-gaussian likelihoods with application to shear estimation
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Madhavacheril, Mathew S. [Stony Brook Univ., NY (United States); Slosar, Anze [Brookhaven National Lab. (BNL), Upton, NY (United States); McDonald, Patrick [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sehgal, Neelima [Stony Brook Univ., NY (United States)
We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong�s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.
Building unbiased estimators from non-gaussian likelihoods with application to shear estimation
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Madhavacheril, Mathew S.; Slosar, Anze; McDonald, Patrick; Sehgal, Neelima
We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the workmore��of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong�s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.��less
Estimating transition times for a model of
Mitchener, W. Garrett
= mean usage rate of G2 dm dt = birth q(m) - death m 0.0 0.2 0.4 0.6 0.8 1.0 0.2 0.4 0.6 0.8 1.0 Mean at a rate k K Simplify K = 1: Each agent uses G1 (state 0) or G2 (state 1) @ Ck = number youth in state kD = death rate: each time step each adult dies with prob- ability pD = rD N , replaced by sampling from
Cardiovascular parameter estimation using a computational model
Samar, Zaid
Modern intensive care units are equipped with a wide range of patient monitoring devices, each continuously recording signals produced by the human body. Currently, these signals need to be interpreted by a clinician in ...
Emission estimates for air pollution transport models.
Streets, D. G.
The results of studies of energy consumption and emission inventories in Asia are discussed. These data primarily reflect emissions from fuel combustion (both biofuels and fossil fuels) and were collected to determine emissions of acid-deposition precursors (SO{sub 2} and NO{sub x}) and greenhouse gases (CO{sub 2} CO, CH{sub 4}, and NMHC) appropriate to RAINS-Asia regions. Current work is focusing on black carbon (soot), volatile organic compounds, and ammonia.
An Estimation and Simulation Framework for Energy Efficient Design using Platform FPGAs
Prasanna, Viktor K.
An Estimation and Simulation Framework for Energy Efficient Design using Platform FPGAs Sumit modeling technique, domain specific modeling, and a methodology for energy-efficient design of application
SPACE TECHNOLOGY Actual Estimate
SPACE TECHNOLOGY TECH-1 Actual Estimate Budget Authority (in $ millions) FY 2011 FY 2012 FY 2013 FY.7 247.0 Exploration Technology Development 144.6 189.9 202.0 215.5 215.7 214.5 216.5 Notional SPACE TECHNOLOGY OVERVIEW .............................. TECH- 2 SBIR AND STTR
; - calculated separately for the most important radionuclides produced in nuclear weapons tests. Those would averages for all tests. 2. Provide a list of references regarding: (1) the history of nuclear weapons to the Population of the Continental U.S. from Nevada Weapons Tests and Estimates of Deposition Density
Use of Cost Estimating Relationships
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
Cost Estimating Relationships (CERs) are an important tool in an estimator's kit, and in many cases, they are the only tool. Thus, it is important to understand their limitations and characteristics. This chapter discusses considerations of which the estimator must be aware so the Cost Estimating Relationships can be properly used.
Status Report on the Modeling of TRISO Energy Deposition, Time-Dependent Temperature Field and Doppler Feedback
Javier Ortensi; Abderrafi M Ougouag
The Doppler feedback mechanism is a major contributor to the passive safety of gas-cooled, graphite-moderated high temperature reactors that use fuel based on Tristructural-Isotropic coated particles. It follows that the correct prediction of the magnitude and time-dependence of this feedback effect is essential to the conduct of safety analyses for these reactors. We present a fuel conduction model for obtaining better estimates of the temperature feedback during moderate and fast transients. The fuel model has been incorporated in the CYNOD-THERMIX-KONVEK suite of coupled codes as a single TRISO particle within each calculation cell. The heat generation rate is scaled down from the neutronic solution and a Dirichlet boundary condition is imposed as the bulk graphite temperature from the thermal-hydraulic solution. This simplified approach yields similar results to those obtained with more complex methods, requiring multi-TRISO calculations within one control volume, but with much less computational effort. We provide an analysis of the hypothetical total control ejection event in the PBMR-400 design that clearly depicts the improvement in the predictions of the fuel temperature.
Monotonic Local Decay Estimates
Avy Soffer
For the Hamiltonian operator H = -{\\Delta}+V(x) of the Schr\\"odinger Equation with a repulsive potential, the problem of local decay is considered. It is analyzed by a direct method, based on a new, L^2 bounded, propagation observable. The resulting decay estimate, is in certain cases monotonic in time, with no "Quantum Corrections". This method is then applied to some examples in one and higher dimensions. In particular the case of the Wave Equation on a Schwarzschild manifold is redone: Local decay, stronger than the known ones are proved (minimal loss of angular derivatives and lower order of radial derivatives of initial data). The method developed here can be an alternative in some cases to the Morawetz type estimates, with L^2-multipliers replacing the first order operators. It provides an alternative to Mourre's method, by including thresholds and high energies.
Kampa, Aleksander Edward
) December 1988 Extremal Index Estimation (December 1988) Aleksander Edward Kampa, Ecole Centrale de Paris, France Chairman of Advisory Comittee: Dr. Tailen Hsing If (X ) is a strictly stationary sequence satisfying certain n dependence restrictions (e.... g. D or A), then the relationship between the extremal properties of (X ) and its associated independent sequence (X ) n n can. under certain conditions, be summed up by a single constant Be[0. 1]. called the extremal index. Results of extreme...
Blumenthal, Jurg M.; Thompson, Wayne
can collect samples from a corn field and use this data to calculate the yield estimate. An interactive grain yield calculator is provided in the Appendix of the pdf version of this publication. The calculator is also located in the publication.... Plan and prepare for sample and data collection. 2. Collect field samples and record data. 3. Analyze the data using the interactive grain yield calculator in the Appendix. Plan and prepare for sample and data collection Predetermine sample locations...
A Flexible Method of Estimating Luminosity Functions
Brandon C. Kelly; Xiaohui Fan; Marianne Vestergaard
We describe a Bayesian approach to estimating luminosity functions. We derive the likelihood function and posterior probability distribution for the luminosity function, given the observed data, and we compare the Bayesian approach with maximum-likelihood by simulating sources from a Schechter function. For our simulations confidence intervals derived from bootstrapping the maximum-likelihood estimate can be too narrow, while confidence intervals derived from the Bayesian approach are valid. We develop our statistical approach for a flexible model where the luminosity function is modeled as a mixture of Gaussian functions. Statistical inference is performed using Markov chain Monte Carlo (MCMC) methods, and we describe a Metropolis-Hastings algorithm to perform the MCMC. The MCMC simulates random draws from the probability distribution of the luminosity function parameters, given the data, and we use a simulated data set to show how these random draws may be used to estimate the probability distribution for the luminosity function. In addition, we show how the MCMC output may be used to estimate the probability distribution of any quantities derived from the luminosity function, such as the peak in the space density of quasars. The Bayesian method we develop has the advantage that it is able to place accurate constraints on the luminosity function even beyond the survey detection limits, and that it provides a natural way of estimating the probability distribution of any quantities derived from the luminosity function, including those that rely on information beyond the survey detection limits.
Using Photogrammetry to Estimate Tank Waste Volumes from Video
Field, Jim G. [Washington River Protection Solutions, LLC, Richland, WA (United States)
Washington River Protection Solutions (WRPS) contracted with HiLine Engineering & Fabrication, Inc. to assess the accuracy of photogrammetry tools as compared to video Camera/CAD Modeling System (CCMS) estimates. This test report documents the results of using photogrammetry to estimate the volume of waste in tank 241-C-I04 from post-retrieval videos and results using photogrammetry to estimate the volume of waste piles in the CCMS test video.
Geothermal Electricity Technology Evaluation Model (GETEM) Development...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Electricity Technology Evaluation Model (GETEM) Development Geothermal Electricity Technology Evaluation Model (GETEM) Development Project objective: Provide a tool for estimating...
Topics in Microeconometrics: Estimation of a Dynamic Model of Occupational Transitions, Wage and Non-Wage Benefits Cross Validation Bandwidth Selection for Derivatives of Various Dimensional Densities Testing the Additive Separability of the Teacher Value Added Effect Semiparametrically
Baird, Matthew David
additively non-separable linear regression model. First,the additively non-separable linear regression model matchesThe additively non-separable linear regression model nests
Kalman filter data assimilation: Targeting observations and parameter estimation
Bellsky, Thomas, E-mail: email@example.com; Kostelich, Eric J.; Mahalov, Alex [School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona 85287 (United States)] [School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona 85287 (United States)
This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.
Reservoir environment of the Onuma geothermal power plant, northeast Japan, estimated by forward analysis of long-term artificial-tracer concentration change, using single-box-model simulator
Shigeno, Hiroshi; Takahashi, Masaaki; Tetsuro, Noda
A single-box-model numerical simulator for personal computer analysis was developed in order to estimate macroscopic parameter values for exploited geothermal reservoirs and essential fluids coming from the depth. The simulator was designed to compute history data concerning total production and reinjection fluids at geothermal power plants from the assumed parameter values, based on conservation laws for water mass, heat energy and masses of conservative chemical constituents of geothermal fluids. Using two kinds of forward analysis techniques, i.e. the cast-net and pursuit methods, programs containing the simulator can semiautomatically select the optimum combination of the unknown parameter values by minimizing the differences between the simulated and measured history data for specific enthalpy and chemical compositions of the production fluids. The forward analysis programs were applied to the history data from the Onuma geothermal power plant (production capacity, 10MWe) where waste hot water reinjection, chemical monitoring and artificial tracer tests have been conducted since 1970, almost the beginning of the geothermal exploitation. Using the history data, enthalpy and iodine concentrations of the total production fluids with the amounts of KI tracer injected as spikes, the macroscopic parameter values for the exploited reservoir and the essential hot water from the depth were uniquely determined as follows: mass of the hot water convecting in the exploited reservoir (M0), 3.23x109kg; recycling fraction of the reinjected waste hot water to the reservoir (R), 0.74; specific enthalpy of the essential water from the depth (H1), 385kcalkg; iodine concentration of the water (I1), 0.086mg/kg with chlorine concentration (C1), 259mg/kg. These results support the conceptual model that the exploited Onuma reservoir mainly in the Tertiary volcanics is supplied with the neutral Na-Cl type hot water of abnormally high B/CI mole ratio of around 1.0 by a large essential reservoir distributed at depth in the Paleozoic to Mesozoic detrital marine sedimentary rocks.
Image-based meteorologic visibility estimation
Graves, Nathan
the estimated luminance. . . . . . . . . . . . . . . . . .Nephelometer . . . . . . 3.4.3 Luminance Meter . . . . 4intensity and the estimated luminance. . . . . . . . . .
DAMAGE ESTIMATION USING MULTI-OBJECTIVE GENETIC ALGORITHMS Faisal Shabbir
Boyer, Edmond
DAMAGE ESTIMATION USING MULTI-OBJECTIVE GENETIC ALGORITHMS Faisal Shabbir 1 , Piotr Omenzetter 2 firstname.lastname@example.com ABSTRACT It is common to estimate structural damage severity by updating a structural model against experimental responses at different damage states. When experimental results from the healthy and damaged
Parameter Estimation from an Optimal Projection in a Local Environment
A. Bijaoui; A. Recio-Blanco; P. de Laverny
The parameter fit from a model grid is limited by our capability to reduce the number of models, taking into account the number of parameters and the non linear variation of the models with the parameters. The Local MultiLinear Regression (LMLR) algorithms allow one to fit linearly the data in a local environment. The MATISSE algorithm, developed in the context of the estimation of stellar parameters from the Gaia RVS spectra, is connected to this class of estimators. A two-steps procedure was introduced. A raw parameter estimation is first done in order to localize the parameter environment. The parameters are then estimated by projection on specific vectors computed for an optimal estimation. The MATISSE method is compared to the estimation using the objective analysis. In this framework, the kernel choice plays an important role. The environment needed for the parameter estimation can result from it. The determination of a first parameter set can be also avoided for this analysis. These procedures based on a local projection can be fruitfully applied to non linear parameter estimation if the number of data sets to be fitted is greater than the number of models.
Statistical Methods for Estimating the Minimum Thickness Along a Pipeline
along the pipeline can be used to estimate corrosion levels. The traditional parametric model method for this problem is to estimate parameters of a specified corrosion distribution and then to use these parameters companies use pipelines to transfer oil, gas and other materials from one place to another. Manufactures
State energy data report 1996: Consumption estimates
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.
Energy Expenditure Estimation DEMO Application
Lu?trek, Mitja
and against the SenseWear, a dedicated commercial product for energy expenditure estimation. Keywords: humanEnergy Expenditure Estimation DEMO Application Bozidara Cvetkovi�c1,2 , Simon Kozina1,2 , Bostjan://www.mps.si Abstract. The paper presents two prototypes for the estimation of hu- man energy expenditure during normal
Rate Estimates In order to estimate the time needed to obtain a complete data set for one combination
Appendix C Rate Estimates In order to estimate the time needed to obtain a complete data set for one combination of colliding beams at one energy the following requirements were defined to obtain the model predictions. Also, since emphasis is put on the most central collisions, a 5% trigger is employed
Variable Density Flow Modeling for Simulation Framework for Regional Geologic CO{sub 2} Storage Along Arches Province of Midwestern United States
Joel Sminchak
The Arches Province in the Midwestern U.S. has been identified as a major area for carbon dioxide (CO{sub 2}) storage applications because of the intersection of Mt. Simon sandstone reservoir thickness and permeability. To better understand large-scale CO{sub 2} storage infrastructure requirements in the Arches Province, variable density scoping level modeling was completed. Three main tasks were completed for the variable density modeling: Single-phase, variable density groundwater flow modeling; Scoping level multi-phase simulations; and Preliminary basin-scale multi-phase simulations. The variable density modeling task was successful in evaluating appropriate input data for the Arches Province numerical simulations. Data from the geocellular model developed earlier in the project were translated into preliminary numerical models. These models were calibrated to observed conditions in the Mt. Simon, suggesting a suitable geologic depiction of the system. The initial models were used to assess boundary conditions, calibrate to reservoir conditions, examine grid dimensions, evaluate upscaling items, and develop regional storage field scenarios. The task also provided practical information on items related to CO{sub 2} storage applications in the Arches Province such as pressure buildup estimates, well spacing limitations, and injection field arrangements. The Arches Simulation project is a three-year effort and part of the United States Department of Energy (U.S. DOE)/National Energy Technology Laboratory (NETL) program on innovative and advanced technologies and protocols for monitoring/verification/accounting (MVA), simulation, and risk assessment of CO{sub 2} sequestration in geologic formations. The overall objective of the project is to develop a simulation framework for regional geologic CO{sub 2} storage infrastructure along the Arches Province of the Midwestern U.S.
Varaiya, Pravin
applicable kinematic wave model to construct a link travel time estimate from 30-second flow and occupancy the kinematic wave model (with known or estimated congestion wave speed and jam density), it is straightforward
alternative factor models: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
and estimation of dynamic unobserved component models. After introducing the general model, two methods for estimating the unknown parameters are presented. Both are algorithms...
In silico estimates of cell electroporation by electrical incapacitation waveforms
Weaver, James C.
We use a system model of a cell and approximate magnitudes of electrical incapacitation (EI) device waveforms to estimate conditions that lead to responses with or without electroporation (EP) of cell membranes near ...
Nonparametric function estimation with infinite-order kernels and applications
Berg, Arthur Steven
2.5.3 GARCH Model . . . . . . . . . . . . . . . . . 2.5.4N = 2000. . . estimates on garch data for N = 200 and N =data. . Histograms based on garch data. . Histograms based
Estimating the Potential Impact of Renewable Energy on the Caribbean
Kammen, Daniel M.
Estimating the Potential Impact of Renewable Energy on the Caribbean Job Sector Rebekah Shirley renewable energy projects within the Caribbean region. We present a model scenario where together energy
Estimation of dibaryon (OO) yields at RHIC energies
Zhong-Dao Lu
The yields of dibaryon (Omega-Omega) in relativistic heavy ion collisions, especially at RHIC energies, are estimated by statistical model. The yields of hyperon Omega- and the ratio of dibaryon to Omega are also given.
An uncertainty principle, Wegner estimates and localization near fluctuation boundaries
Anne Boutet de Monvel; Daniel Lenz; Peter Stollmann
We prove a simple uncertainty principle and show that it can be applied to prove Wegner estimates near fluctuation boundaries. This gives new classes of models for which localization at low energies can be proven.
Genetic parameter estimation of mohair production traits in Angora goats
Podisi, Baitsi
analyzed included fiber diameter (FD; n = 4329), grease fleece weight (FW; n = 7073), body weight (BW; n = 4171) and fertility (FERT; n = 2118). Heritability estimates were obtained for all the traits using REML procedures with a multivariate animal model...
Identification and Estimation of a Discrete Game of Complete Information
Bajari, Patrick
We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility ...
Performance bounds on matched-field methods for source localization and estimation of ocean environmental parameters
Xu, Wen, 1967-
Matched-field methods concern estimation of source location and/or ocean environmental parameters by exploiting full wave modeling of acoustic waveguide propagation. Typical estimation performance demonstrates two fundamental ...
New Results in Stability, Control, and Estimation of Fractional Order Systems
Koh, Bong Su
of control and estimation, even for systems where fractional order models do not arise �naturally�. This dissertation is aimed at further building of the base methodology with a focus on robust feedback control and state estimation. By setting...
Robust quantum parameter estimation: Coherent magnetometry with feedback
Stockton, John K.; Geremia, J.M.; Doherty, Andrew C.; Mabuchi, Hideo [Norman Bridge Laboratory of Physics, Mail Code 12-33, California Institute of Technology, Pasadena, California 91125 (United States)
We describe the formalism for optimally estimating and controlling both the state of a spin ensemble and a scalar magnetic field with information obtained from a continuous quantum limited measurement of the spin precession due to the field. The full quantum parameter estimation model is reduced to a simplified equivalent representation to which classical estimation and control theory is applied. We consider both the tracking of static and fluctuating fields in the transient and steady-state regimes. By using feedback control, the field estimation can be made robust to uncertainty about the total spin number.
Tools and techniques that provide improved performance and reduced costs are important to government programs, particularly in current times. An opportunity for improvement was identified for preparation of cost estimates used to support the evaluation of response action alternatives. As a result, CH2M HILL Plateau Remediation Company has developed Tool for Response Action Cost Estimating (TRACE). TRACE is a multi-page Microsoft Excel{reg_sign} workbook developed to introduce efficiencies into the timely and consistent production of cost estimates for response action alternatives. This tool combines costs derived from extensive site-specific runs of commercially available remediation cost models with site-specific and estimator-researched and derived costs, providing the best estimating sources available. TRACE also provides for common quantity and key parameter links across multiple alternatives, maximizing ease of updating estimates and performing sensitivity analyses, and ensuring consistency.
Quantum-enhanced metrology for multiple phase estimation with noise
Jie-Dong Yue; Yu-Ran Zhang; Heng Fan
We present a general framework to study the simultaneous estimation of multiple phases in the presence of noise as a discretized model for phase imaging. This approach can lead to nontrivial bounds of the precision for multiphase estimation. Our results show that simultaneous estimation (SE) of multiple phases is always better than individual estimation (IE) of each phase even in noisy environment. However with $d$ being the number of phases, the $O(d)$ advantage in the variance of the estimation, with which SE outperforms IE schemes for noiseless processes, may disappear asymptotically. When noise is low, those bounds recover the Heisenberg scale with the $O(d)$ advantage. The utility of the bound of multiple phase estimation for photon loss channels is exemplified.
Estimating Energy Savings in Compressed Air Systems
Schmidt, C.; Kissock, J. K.
are frequently overestimated because the methods used to estimate savings neglect to consider important factors such as compressor control and type, storage, and multiple compressor operation. In this paper, a methodology is presented for modeling air... compressor performance and calculating projected energy savings from easily obtainable performance data such as full-load power, no-load power, rated capacity, average fraction full-load power or average fraction rated capacity. The methodology...
IDC RP2 & 3 US Industry Standard Cost Estimate Summary.
Harris, James M.; Huelskamp, Robert M.
Sandia National Laboratories has prepared a ROM cost estimate for budgetary planning for the IDC Reengineering Phase 2 & 3 effort, using a commercial software cost estimation tool calibrated to US industry performance parameters. This is not a cost estimate for Sandia to perform the project. This report provides the ROM cost estimate and describes the methodology, assumptions, and cost model details used to create the ROM cost estimate. ROM Cost Estimate Disclaimer Contained herein is a Rough Order of Magnitude (ROM) cost estimate that has been provided to enable initial planning for this proposed project. This ROM cost estimate is submitted to facilitate informal discussions in relation to this project and is NOT intended to commit Sandia National Laboratories (Sandia) or its resources. Furthermore, as a Federally Funded Research and Development Center (FFRDC), Sandia must be compliant with the Anti-Deficiency Act and operate on a full-cost recovery basis. Therefore, while Sandia, in conjunction with the Sponsor, will use best judgment to execute work and to address the highest risks and most important issues in order to effectively manage within cost constraints, this ROM estimate and any subsequent approved cost estimates are on a 'full-cost recovery' basis. Thus, work can neither commence nor continue unless adequate funding has been accepted and certified by DOE.
POINTWISE ESTIMATES AND MONOTONICITY FORMULAS WITHOUT MAXIMUM PRINCIPLE MARCELO MONTENEGRO;2 MARCELO MONTENEGRO AND ENRICO VALDINOCI In this paper, a central role will be played by the following
Trade-offs between inductive loops and GPS probe vehicles for travel time estimation
using a velocity model equivalent to the Cell Transmission Model, and a traffic state estimation equivalent to the Cell Transmission Model [1, 2], using an estimation technique known as ensemble Kalman, 11], including data generated from cell phone towers, which produces less accurate vehicle position
Frequency tracking and parameter estimation for robust quantum state estimation
Ralph, Jason F. [Department of Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ (United Kingdom); Jacobs, Kurt [Department of Physics, University of Massachusetts at Boston, 100 Morrissey Blvd, Boston, Massachusetts 02125 (United States); Hill, Charles D. [Centre for Quantum Computation and Communication Technology, School of Physics, University of Melbourne, Victoria 3010 (Australia)
In this paper we consider the problem of tracking the state of a quantum system via a continuous weak measurement. If the system Hamiltonian is known precisely, this merely requires integrating the appropriate stochastic master equation. However, even a small error in the assumed Hamiltonian can render this approach useless. The natural answer to this problem is to include the parameters of the Hamiltonian as part of the estimation problem, and the full Bayesian solution to this task provides a state estimate that is robust against uncertainties. However, this approach requires considerable computational overhead. Here we consider a single qubit in which the Hamiltonian contains a single unknown parameter. We show that classical frequency estimation techniques greatly reduce the computational overhead associated with Bayesian estimation and provide accurate estimates for the qubit frequency.
Estimate of the scatter component in SPECT
Ivanovic, M.; Weber, D.A. [Univ. of California, Sacramento, CA (United States); Loncaric, S. [Univ. of Zagreb (Croatia)
Analytical expressions that describe the dependence of slopes and amplitudes of the scatter distribution functions (SDF) on source depth and media density are used to estimate a scatter component in SPECT projection data. Since the ratio of detected scattered to total photons (S/T), SDF amplitude and slope depend strongly on line source length (SL) used to obtain SDFs, we compared estimated scattered components using SDFs, obtained for lengths of 2-21 cm. At 10 cm source depth, S/T changes from 0.19 to 0.36 when SL changes from 2 to 21 cm. Scatter amplitude`s dependence on source depth (d) in water was described by 6.38e{sup -0.186d} for a 2 cm and 16.15e{sup -0.129d} for a 21 cm SL. Slope was described by 0.292d{sup -0.601} for a cm SL and by 0.396d{sup -0.82} for a 21 cm SL. The estimated scatter components are compared with simulated SPECT projection data obtained with Monte Carlo modeling of six hot spheres placed in a cylindrical water filled phantom. The comparison of estimated with simulated total counts/projection shows very good agreement when approaching SDF for a point source (the % difference varied from 2 to 13% for 2 cm SL). Significant overestimate is seen when source length increases.
Atmospheric dispersion estimates in the vicinity of buildings
Ramsdell, J.V. Jr.; Fosmire, C.J.
A model describing atmospheric dispersion in the vicinity of buildings was developed for the U.S. Nuclear Regulatory Commission (NRC) in the late 1980s. That model has recently undergone additional peer review. The reviewers identified four areas of concern related to the model and its application. This report describes revisions to the model in response to the reviewers concerns. Model revision involved incorporation of explicit treatment of enhanced dispersion at low wind speeds in addition to explicit treatment of enhanced dispersion at high speeds resulting from building wakes. Model parameters are evaluated from turbulence data. Experimental diffusion data from seven reactor sites are used for model evaluation. Compared with models recommended in current NRC guidance to licensees, the revised model is less biased and shows more predictive skill. The revised model is also compared with two non-Gaussian models developed to estimate maximum concentrations in building wakes. The revised model concentration predictions are nearly the same as the predictions of the non-Gaussian models. On the basis of these comparisons of the revised model concentration predictions with experimental data and the predictions of other models, the revised model is found to be an appropriate model for estimating concentrations in the vicinity of buildings.
Examples of Cost Estimation Packages
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
Estimates can be performed in a variety of ways. Some of these are for projects for an undefined scope, a conventional construction project, or where there is a level of effort required to complete the work. Examples of cost estimation packages for these types of projects are described in this appendix.
Estimating the Energy Use and Efficiency Potential of U.S. Data Centers
Masanet, EricR.
Keywords: data centers; energy demand modeling; energyof U.S. data center energy demand under different efficiencyfor estimation of energy demand in different data center
Aerosol Best Estimate Value-Added Product
Flynn, C; Turner, D; Koontz, A; Chand, D; Sivaraman, C
The objective of the Aerosol Best Estimate (AEROSOLBE) value-added product (VAP) is to provide vertical profiles of aerosol extinction, single scatter albedo, asymmetry parameter, and Angstroem exponents for the atmospheric column above the Central Facility at the ARM Southern Great Plains (SGP) site. We expect that AEROSOLBE will provide nearly continuous estimates of aerosol optical properties under a range of conditions (clear, broken clouds, overcast clouds, etc.). The primary requirement of this VAP was to provide an aerosol data set as continuous as possible in both time and height for the Broadband Heating Rate Profile (BBHRP) VAP in order to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Even though BBHRP has been completed, AEROSOLBE results are very valuable for environmental, atmospheric, and climate research.
IVCNZ 2002 SUBMISSION 1 Pose Estimation by Applied Numerical Techniques
McCane, Brendan
process of how to deform the model in order to bring it into agreement with the input image. An energy. Keywords--- Numerical Optimisation, Pose Estimation, AnalysisbySynthesis, Optimisation Algorithms (HCI). Traditionally, researchers have split approaches into an appearancebased approach and a model
de Freitas, Nando
ESTIMATION AND CONTROL OF INDUSTRIAL PROCESSES WITH PARTICLE FILTERS Rub�en Morales of industrial processes. In particular, we adopt a jump Markov linear Gaussian (JMLG) model to describe an industrial heat exchanger. The parameters of this model are identi- fied with the expectation maximisation
Stump, Brian W.
COUPLING AND COHERENCE ESTIMATES FROM SINGLE-FIRED CYLINDRICAL EXPLOSIONS Implications for Using 4 5 6 7 8 test bench pit charge depth burden charge length explosive stemming #12;Single shot) Modeling - Source a) Explosion Source Mueller-Murphy model b) Vertical Spall Opening of horizontal crack
Design of Optimal Experiments for Parameter Estimation of Microalgae
Paris-Sud XI, Universit� de
. INTRODUCTION Microalgae have received a specific attention in the frame- work of renewable energy generationDesign of Optimal Experiments for Parameter Estimation of Microalgae Growth Models Rafael Mu microalgal production towards a profitable process of renewable energy generation. To render models
Nondestructive estimates of above-ground biomass using terrestrial laser scanning
Jones, Peter JS
, The Netherlands; 2 CSIRO Land and Water, Private Bag 10, Clayton South, Vic. 3169, Australia; 3 Department these estimates against destructively harvested AGB estimates and AGB derived from allometric equations. We also. Single trees are extracted from the TLS data and quantitative structure models are used to estimate
An efficient algorithm for real-time estimation and prediction of dynamic OD tables
Bierlaire, Michel
An efficient algorithm for real-time estimation and prediction of dynamic OD tables M. Bierlaire and F. Crittin February, 2002 Abstract The problem of estimating and predicting Origin-Destination (OD more intricate. We consider here a least-square modeling approach for solving the OD estimation
Submitted to the Annals of Statistics FLEXIBLE COVARIANCE ESTIMATION IN GRAPHICAL
West, Mike
models have proven to be excellent tools for the analysis of complex high-dimensional data where examples where we explore frequentist risk prop- erties and the efficacy of graphs in the estimation of these estimators give substantial risk reductions compared to the sample covariance estimator S in small sample
Switching Mode Generation and Optimal Estimation with Application to Skid-Steering
Hartmann, Mitra J. Z.
to treat the skid-steered vehicle as a switched system, the vehicle's ground interaction is modeled using; optimal estimation; optimal control; estimation algorithms 1 Introduction The skid-steered vehicle (SSVSwitching Mode Generation and Optimal Estimation with Application to Skid-Steering T. M. Caldwell
How to Estimate the Value of Service Reliability Improvements
Sullivan, Michael J.; Mercurio, Matthew G.; Schellenberg, Josh A.; Eto, Joseph H.
A robust methodology for estimating the value of service reliability improvements is presented. Although econometric models for estimating value of service (interruption costs) have been established and widely accepted, analysts often resort to applying relatively crude interruption cost estimation techniques in assessing the economic impacts of transmission and distribution investments. This paper first shows how the use of these techniques can substantially impact the estimated value of service improvements. A simple yet robust methodology that does not rely heavily on simplifying assumptions is presented. When a smart grid investment is proposed, reliability improvement is one of the most frequently cited benefits. Using the best methodology for estimating the value of this benefit is imperative. By providing directions on how to implement this methodology, this paper sends a practical, usable message to the industry.
Joint estimation of phase and phase diffusion for quantum metrology
Mihai D. Vidrighin; Gaia Donati; Marco G. Genoni; Xian-Min Jin; W. Steven Kolthammer; M. S. Kim; Animesh Datta; Marco Barbieri; Ian A. Walmsley
Phase estimation, at the heart of many quantum metrology and communication schemes, can be strongly affected by noise, whose amplitude may not be known, or might be subject to drift. Here, we investigate the joint estimation of a phase shift and the amplitude of phase diffusion, at the quantum limit. For several relevant instances, this multiparameter estimation problem can be effectively reshaped as a two-dimensional Hilbert space model, encompassing the description of an interferometer phase probed with relevant quantum states -- split single-photons, coherent states or N00N states. For these cases, we obtain a trade-off bound on the statistical variances for the joint estimation of phase and phase diffusion, as well as optimum measurement schemes. We use this bound to quantify the effectiveness of an actual experimental setup for joint parameter estimation for polarimetry. We conclude by discussing the form of the trade-off relations for more general states and measurements.
Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant
Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa
System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.
Optimized replica gas estimation of absolute integrals and partition functions.
Minh, D. (Biosciences Division)
In contrast with most Monte Carlo integration algorithms, which are used to estimate ratios, the replica gas identities recently introduced by Adib enable the estimation of absolute integrals and partition functions using multiple copies of a system and normalized transition functions. Here, an optimized form is presented. After generalizing a replica gas identity with an arbitrary weighting function, we obtain a functional form that has the minimal asymptotic variance for samples from two replicas and is provably good for a larger number. This equation is demonstrated to improve the convergence of partition function estimates in a two-dimensional Ising model.
Photogrammetry and Laser Imagery Tests for Tank Waste Volume Estimates: Summary Report
Field, Jim G. [Washington River Protection Solutions, LLC, Richland, WA (United States)
Feasibility tests were conducted using photogrammetry and laser technologies to estimate the volume of waste in a tank. These technologies were compared with video Camera/CAD Modeling System (CCMS) estimates; the current method used for post-retrieval waste volume estimates. This report summarizes test results and presents recommendations for further development and deployment of technologies to provide more accurate and faster waste volume estimates in support of tank retrieval and closure.
Cosmological parameter estimation: impact of CMB aberration
Catena, Riccardo [Institut f�r Theoretische Physik, Friedrich-Hund-Platz 1, 37077 G�ttingen (Germany); Notari, Alessio, E-mail: email@example.com, E-mail: email@example.com [Departament de F�sica Fondamental i Institut de Ci�ncies del Cosmos, Universitat de Barcelona, Mart� i Franqu�s 1, 08028 Barcelona (Spain)
The peculiar motion of an observer with respect to the CMB rest frame induces an apparent deflection of the observed CMB photons, i.e. aberration, and a shift in their frequency, i.e. Doppler effect. Both effects distort the temperature multipoles a{sub lm}'s via a mixing matrix at any l. The common lore when performing a CMB based cosmological parameter estimation is to consider that Doppler affects only the l = 1 multipole, and neglect any other corrections. In this paper we reconsider the validity of this assumption, showing that it is actually not robust when sky cuts are included to model CMB foreground contaminations. Assuming a simple fiducial cosmological model with five parameters, we simulated CMB temperature maps of the sky in a WMAP-like and in a Planck-like experiment and added aberration and Doppler effects to the maps. We then analyzed with a MCMC in a Bayesian framework the maps with and without aberration and Doppler effects in order to assess the ability of reconstructing the parameters of the fiducial model. We find that, depending on the specific realization of the simulated data, the parameters can be biased up to one standard deviation for WMAP and almost two standard deviations for Planck. Therefore we conclude that in general it is not a solid assumption to neglect aberration in a CMB based cosmological parameter estimation.
Risk Estimation Methodology for Launch Accidents.
Clayton, Daniel James; Lipinski, Ronald J.; Bechtel, Ryan D.
As compact and light weight power sources with reliable, long lives, Radioisotope Power Systems (RPSs) have made space missions to explore the solar system possible. Due to the hazardous material that can be released during a launch accident, the potential health risk of an accident must be quantified, so that appropriate launch approval decisions can be made. One part of the risk estimation involves modeling the response of the RPS to potential accident environments. Due to the complexity of modeling the full RPS response deterministically on dynamic variables, the evaluation is performed in a stochastic manner with a Monte Carlo simulation. The potential consequences can be determined by modeling the transport of the hazardous material in the environment and in human biological pathways. The consequence analysis results are summed and weighted by appropriate likelihood values to give a collection of probabilistic results for the estimation of the potential health risk. This information is used to guide RPS designs, spacecraft designs, mission architecture, or launch procedures to potentially reduce the risk, as well as to inform decision makers of the potential health risks resulting from the use of RPSs for space missions.
Economic Model For a Return on Investment Analysis of United States Government High Performance Computing (HPC) Research and Development (R & D) Investment
Joseph, Earl C.; Conway, Steve; Dekate, Chirag
This study investigated how high-performance computing (HPC) investments can improve economic success and increase scientific innovation. This research focused on the common good and provided uses for DOE, other government agencies, industry, and academia. The study created two unique economic models and an innovation index: 1 A macroeconomic model that depicts the way HPC investments result in economic advancements in the form of ROI in revenue (GDP), profits (and cost savings), and jobs. 2 A macroeconomic model that depicts the way HPC investments result in basic and applied innovations, looking at variations by sector, industry, country, and organization size. ? A new innovation index that provides a means of measuring and comparing innovation levels. Key findings of the pilot study include: IDC collected the required data across a broad set of organizations, with enough detail to create these models and the innovation index. The research also developed an expansive list of HPC success stories.
Measurement enhancement for state estimation
Chen, Jian
in the power system. A robust state estimation should have the capability of keeping the system observable during different contingencies, as well as detecting and identifying the gross errors in measurement set and network topology. However, this capability...
Estimation of resources and reserves
Massachusetts Institute of Technology. Energy Laboratory.
This report analyzes the economics of resource and reserve estimation. Current concern about energy problems has focused attention on how we measure available energy resources. One reads that we have an eight-year oil ...
Motion Estimation from Disparity Images
Demirdjian, D.
A new method for 3D rigid motion estimation from stereo is proposed in this paper. The appealing feature of this method is that it directly uses the disparity images obtained from stereo matching. We assume that the stereo ...
Estimation of soil moisture in paddy field using Artificial Neural Networks
Arif, Chusnul; Setiawan, Budi Indra; Doi, Ryoichi
In paddy field, monitoring soil moisture is required for irrigation scheduling and water resource allocation, management and planning. The current study proposes an Artificial Neural Networks (ANN) model to estimate soil moisture in paddy field with limited meteorological data. Dynamic of ANN model was adopted to estimate soil moisture with the inputs of reference evapotranspiration (ETo) and precipitation. ETo was firstly estimated using the maximum, average and minimum values of air temperature as the inputs of model. The models were performed under different weather conditions between the two paddy cultivation periods. Training process of model was carried out using the observation data in the first period, while validation process was conducted based on the observation data in the second period. Dynamic of ANN model estimated soil moisture with R2 values of 0.80 and 0.73 for training and validation processes, respectively, indicated that tight linear correlations between observed and estimated values of s...
A Bayesian Framework for Combining Valuation Estimates
Kenton K. Yee
Obtaining more accurate equity value estimates is the starting point for stock selection, value-based indexing in a noisy market, and beating benchmark indices through tactical style rotation. Unfortunately, discounted cash flow, method of comparables, and fundamental analysis typically yield discrepant valuation estimates. Moreover, the valuation estimates typically disagree with market price. Can one form a superior valuation estimate by averaging over the individual estimates, including market price? This article suggests a Bayesian framework for combining two or more estimates into a superior valuation estimate. The framework justifies the common practice of averaging over several estimates to arrive at a final point estimate.
A Bayesian Framework for Combining Valuation Estimates
Yee, Kenton K
Obtaining more accurate equity value estimates is the starting point for stock selection, value-based indexing in a noisy market, and beating benchmark indices through tactical style rotation. Unfortunately, discounted cash flow, method of comparables, and fundamental analysis typically yield discrepant valuation estimates. Moreover, the valuation estimates typically disagree with market price. Can one form a superior valuation estimate by averaging over the individual estimates, including market price? This article suggests a Bayesian framework for combining two or more estimates into a superior valuation estimate. The framework justifies the common practice of averaging over several estimates to arrive at a final point estimate.
Analysis of neutron scattering data: Visualization and parameter estimation
Beauchamp, J.J.; Fedorov, V.; Hamilton, W.A.; Yethiraj, M.
Traditionally, small-angle neutron and x-ray scattering (SANS and SAXS) data analysis requires measurements of the signal and corrections due to the empty sample container, detector efficiency and time-dependent background. These corrections are then made on a pixel-by-pixel basis and estimates of relevant parameters (e.g., the radius of gyration) are made using the corrected data. This study was carried out in order to determine whether treatment of the detector efficiency and empty sample cell in a more statistically sound way would significantly reduce the uncertainties in the parameter estimators. Elements of experiment design are shortly discussed in this paper. For instance, we studied the way the time for a measurement should be optimally divided between the counting for signal, background and detector efficiency. In Section 2 we introduce the commonly accepted models for small-angle neutron and x-scattering and confine ourselves to the Guinier and Rayleigh models and their minor generalizations. The traditional approaches of data analysis are discussed only to the extent necessary to allow their comparison with the proposed techniques. Section 3 describes the main stages of the proposed method: visual data exploration, fitting the detector sensitivity function, and fitting a compound model. This model includes three additive terms describing scattering by the sampler, scattering with an empty container and a background noise. We compare a few alternatives for the first term by applying various scatter plots and computing sums of standardized squared residuals. Possible corrections due to smearing effects and randomness of estimated parameters are also shortly discussed. In Section 4 the robustness of the estimators with respect to low and upper bounds imposed on the momentum value is discussed. We show that for the available data set the most accurate and stable estimates are generated by models containing double terms either of Guinier's or Rayleigh's type. The optimal partitioning of the total experimental time between measuring various signals is discussed in Section 5. We applied a straightforward optimization instead of some special experimental techniques because of the numerical simplicity of the corresponding problem. As a criterion of optimality we selected the variance of the gyration radius maximum likelihood estimator. The statistical background of the proposed approach is given in the appendix. The properties of the maximum likelihood estimators and the corresponding iterated estimator together with its possible numerical realization are presented in subsection A.1. In subsection A.2 we prove that the use of a compound model leads to more efficient estimators than a stage-wise analysis of different components entering that model.
The Art and Science of Depiction Fredo Durand
Durand, Fr�do
and Darkness � the Evening of the Deluge Light and Colour (Goethe's Theory) � the Morning after Deluge #12
The Art and Science of Depiction Fredo Durand
Durand, Fr�do
and Darkness � the Evening of the Deluge Light and Colour (Goethe's Theory) � the Morning after Deluge
The Art and Science of Depiction Fredo Durand
Durand, Fr�do
� Rembrandt Gaze Movement & Focal Points 26 Focus through perspective � Raphael, The School of Athens Gaze on task? � Rembrandt, The Anatomy Lesson � Different tasks: � A: Aesthetic � B: Semantic � Very similar