"Filtering Techniques For Large Scale Turbulent Flow         Simulation"
{'Code': '07020000', 'Directorate': {'LongName': 'Directorate For Engineering'}, 'Division': {'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
{'SignBlockName': 'HUSEYIN A. SEHITOGLU'}
This research will model large and complex turbulent flows such as bays         using a temporal and spatial filtering approach.  This involves certain         arbitrary ad hoc assumptions.  Their use would in all likelihood be             considered unscientific by the peer review community; the intent,               however, is to test an intuitive, only party verified, expectation that         the proposed method is highly insensitive to these input assumptions,           and that calibration of the method from other, much simpler flows,              would therefore validate their application to a much wider range of             conditions for which verification data will be either extremely sparse          or even absent.  Such conditions are typical of large, shallow waters           whose characteristics must be modeled ffor a variety of civil/coastal           engineering applications.
{'FirstName': 'Donald', 'LastName': 'Harleman', 'EmailAddress': None, 'StartDate': '05/01/1986', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'Cambridge', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA'}
{'Code': '1443', 'Text': 'FLUID DYNAMICS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8611631.xml'}