Probabilistic Response of Non-Linear Multi-Degree of FreedomSystems
{'Code': '07000000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}}
{'SignBlockName': 'Norman Caplan', 'PO_EMAI': None, 'PO_PHON': None}
This study focuses upon the development of accurate prediction                  methods of non-linear, multi-degree of freedom (MDOF) structural                systems subject to external and parametric random vibration.  A                 formulation based upon Markov methods, which combines stochastic                averaging, white noise shaping filters and moment closure                       techniques is presented.  The analysis yields a system of                       algebraic equations which can be used to provide non-Gaussian                   response information.  To illustrate this general analytical                    approach, a series of examples focused on the response of deep                  water compliant offshore platforms subjected to realistic surface               wave spectrum are presented.  In order to represent the random                  sea environment, dimensionless shaping filters are developed to                 modify the white noise input and provide the surface elevation                  and fluid kinematic data needed for the response simulation.  The               implications of this approach on MDOF system response and                       reliability estimates is explored and discussed.
{'FirstName': 'John', 'LastName': 'Niedzwecki', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John M Niedzwecki', 'EmailAddress': 'j-niedzwecki@tamu.edu', 'NSF_ID': '000102937', 'StartDate': '10/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Texas A&M Research Foundation', 'CityName': 'COLLEGE STATION', 'ZipCode': '778454375', 'PhoneNumber': '9798626777', 'StreetAddress': '400 HARVEY MITCHELL PKWY S STE 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'EQH8NQ4AXFT7', 'ORG_LGL_BUS_NAME': 'TEXAS A & M RESEARCH FOUNDATION', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '145200', 'Text': 'POWER SYSTEMS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8814021.xml'}