Research into New Strategies for Rectification of           Uncertain Data in Process Design
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
{'SignBlockName': 'Senior Program Assistant', 'PO_EMAI': None, 'PO_PHON': None}
In any design, the information upon which the design is based is                uncertain due to biases, random errors, large variances, missing data,          and other factors that cannot be controlled.  In process design, these          uncertainties are often ignored or treated deterministically.  Various          strategies have been proposed for estimating and rectifying the data.           Among these strategies are statistical techniques such as least squares         and maximum likelihood, optimization techniques such as linear                  programming and Lagrange multipliers, and filtering techniques.  All of         these techniques focus on the data itself rather than on the use of the         data within the design process.  A new approach to data reconciliation          is developed using influence methods and interval analysis to eliminate         gross and systematic errors in the data and to reconcile the remaining          data.  This new methodology will enhance the quality of the data                available to the designer.  The research will result in algorithms and          computer programs that will be applicable in a number of disciplines.
{'FirstName': 'David', 'LastName': 'Himmelblau', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David M Himmelblau', 'EmailAddress': 'himmelblau@che.utexas.edu', 'NSF_ID': '000317364', 'StartDate': '09/01/1985', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Texas at Austin', 'CityName': 'AUSTIN', 'ZipCode': '787121139', 'PhoneNumber': '5124716424', 'StreetAddress': '110 INNER CAMPUS DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'V6AFQPN18437', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT AUSTIN', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '146400', 'Text': 'ESD-Eng & Systems Design'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1985&All=true', 'xml': '8517115.xml'}