Computational Algorithms for Particle Transport Processes
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
{'SignBlockName': 'George K. Lea', 'PO_EMAI': None, 'PO_PHON': None}
The goal of this research is to develop accurate and efficient                  computational algorithms that will enable engineers to routinely                analyze transport phenomena without relying on methods that utilize             simplified physical models.  In particular, several methods to                  accelerate the interactive convergence of numerical transport                   solutions will be examined, they include: developing the diffusion              synthetic acceleration algorithm (DSA) in multidimensional                      geometries, applying a multigrid method for the acceleration on                 inner iterations, and applying a "synthetic" acceleration method for            the acceleration of outer iterations.                                                                                                                           Transport process is characterized by the movement of some                      quantity in an interacting medium.  The transport of heat in a solid,           of steam-water mixture in a heat exchanger, or of photons in the                upper atmosphere, are all examples of transport process.  Transport             process can be categorized as continuum or particle depending on                whether one describe the transfer of continuum quantities; e.g. mass,           momentum, or energy, or particles; e.g. protons or neutrons.                    However, if the number density of the particles are sufficiently                large, then the detailed statistical fluctuations can be smeared out            so that an approximate continuum formulation may be used; i.e.                  Boltzman transport equation which for the linear case can be further            reduced to a diffusion limit.  The key issue is to strike a balance             between the accuracy and efficiency (cost) of doing the                         computations associated with each of these formulations
[{'FirstName': 'Edward', 'LastName': 'Larsen', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edward W Larsen', 'EmailAddress': None, 'NSF_ID': '000174808', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'William', 'LastName': 'Martin', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William R Martin', 'EmailAddress': 'wrm@umich.edu', 'NSF_ID': '000323019', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
[{'Code': '1271', 'Text': 'COMPUTATIONAL MATHEMATICS'}, {'Code': '1495', 'Text': 'COMPUTATIONAL ENGINEERING'}, {'Code': '1518', 'Text': 'CONTROL, NETWORKS, & COMP INTE'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8721680.xml'}