{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/72203"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/72203","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Response Surface Method for Time-Variant Reliability Analysis","abstract":"An efficient, approximate method for computing the structural reliability of uncertain systems subjected to time-varying loads is presented in this study. The method uses response surface methodology and the fast integration scheme developed by Wen and Chen (1987). The mean and coefficient of variation of the maximum response of the structure are modeled by second order polynomials fitted using central composite designs applied to data from response time histories. The structural failure probability conditional upon the uncertain system parameter values is assumed to follow an extreme value distribution, the parameters of which are fitted by the response surface models. The fast integration scheme provides a formulation of a limit state function which incorporates this information. The failure probability over a specified time interval can then be evaluated using Monte Carlo simulation. Four numerical examples are solved by the proposed approach, with results compared against approximate solutions by existing methods. An empirical measure is introduced to provide information on the goodness-of-fit of the response surface models. The proposed method is shown to be particularly efficient when used for analyzing the sensitivity of the failure probability to the distribution parameters of the uncertain system parameters.","abstract_html":"An efficient, approximate method for computing the structural reliability of uncertain systems subjected to time-varying loads is presented in this study. The method uses response surface methodology and the fast integration scheme developed by Wen and Chen (1987). The mean and coefficient of variation of the maximum response of the structure are modeled by second order polynomials fitted using central composite designs applied to data from response time histories. The structural failure probability conditional upon the uncertain system parameter values is assumed to follow an extreme value distribution, the parameters of which are fitted by the response surface models. The fast integration scheme provides a formulation of a limit state function which incorporates this information. The failure probability over a specified time interval can then be evaluated using Monte Carlo simulation. Four numerical examples are solved by the proposed approach, with results compared against approximate solutions by existing methods. An empirical measure is introduced to provide information on the goodness-of-fit of the response surface models. The proposed method is shown to be particularly efficient when used for analyzing the sensitivity of the failure probability to the distribution parameters of the uncertain system parameters.","abstract_has_math":false,"creators":["Yao, Timothy Hun-Jen"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Wen, Y.K."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-12-17T21:05:08Z","date_published":"2014-12-17T21:05:08Z","updated_at":"2026-07-22T22:26:06Z","subjects":["Mathematics","Statistics","Engineering, Civil"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(UMI)AAI9329206"],"render_values":[{"text":"(UMI)AAI9329206","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/72203","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Wen, Y.K."]},{"key":"dc:creator","label":"Author","values":["Yao, Timothy Hun-Jen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-12-17T21:05:08Z","10000-01-01","1993"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Mathematics","Statistics","Engineering, Civil"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/72203","(UMI)AAI9329206"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["An efficient, approximate method for computing the structural reliability of uncertain systems subjected to time-varying loads is presented in this study. The method uses response surface methodology and the fast integration scheme developed by Wen and Chen (1987). The mean and coefficient of variation of the maximum response of the structure are modeled by second order polynomials fitted using central composite designs applied to data from response time histories. The structural failure probability conditional upon the uncertain system parameter values is assumed to follow an extreme value distribution, the parameters of which are fitted by the response surface models. The fast integration scheme provides a formulation of a limit state function which incorporates this information. The failure probability over a specified time interval can then be evaluated using Monte Carlo simulation. Four numerical examples are solved by the proposed approach, with results compared against approximate solutions by existing methods. An empirical measure is introduced to provide information on the goodness-of-fit of the response surface models. 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The method uses response surface methodology and the fast integration scheme developed by Wen and Chen (1987). The mean and coefficient of variation of the maximum response of the structure are modeled by second order polynomials fitted using central composite designs applied to data from response time histories. The structural failure probability conditional upon the uncertain system parameter values is assumed to follow an extreme value distribution, the parameters of which are fitted by the response surface models. The fast integration scheme provides a formulation of a limit state function which incorporates this information. The failure probability over a specified time interval can then be evaluated using Monte Carlo simulation. Four numerical examples are solved by the proposed approach, with results compared against approximate solutions by existing methods. An empirical measure is introduced to provide information on the goodness-of-fit of the response surface models. 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