Knowledge Acquisition in Expert Systems for Structural      Engineering Design
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
{'SignBlockName': 'William Hakala', 'PO_EMAI': None, 'PO_PHON': None}
The purpose of this study is to explore the use of existing technology          in expert systems, particularly in the area of knowledge acquisition,           for the development of more advanced design tools for structural                engineering.  The study will look at both sources of knowledge                  acquisition using an existing system, HI-RISE, as a basis.  HI-RISE is          an expert system for the preliminary structural design of high-rise             buildings.  The study is divided into three tasks.  The first task              involves the calibration of HI-RISE with recognized experts in the              domain of structural design of high-rise buildings.  The second task            involves the development of an automated knowledge acquisition module           for structural design problems.  During this task, a generic expert             system framework for structural design will be developed using the              basic representation and control strategy in HI-RISE.  The third task           is the incorporation of machine learning in HI-RISE using some of the           elementary mechanisms developed in the artificial intelligence                  community.
{'FirstName': 'Mary Lou', 'LastName': 'Maher', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mary Lou Maher', 'EmailAddress': 'mary@archsci.arch.su.edu.au             http://www.arch.su.edu.au/~mary/', 'NSF_ID': '000245098', 'StartDate': '08/01/1985', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'ZipCode': '152133815', 'PhoneNumber': '4122688746', 'StreetAddress': '5000 FORBES AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '18', 'CONGRESS_DISTRICT_ORG': 'PA18', 'ORG_UEI_NUM': 'U3NKNFLNQ613', 'ORG_LGL_BUS_NAME': 'CARNEGIE MELLON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NKNFLNQ613'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '1442', 'Text': 'CONSTRUCTION AND INFRASTRUCTUR'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1985&All=true', 'xml': '8505643.xml'}