{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/38051"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/38051","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"A Bayesian statistics approach to updating finite element models with frequency response data","abstract":"This dissertation addresses the task of updating finite element models with frequency response data acquired in a structural dynamics test. Standard statistical techniques are used to generate statistically qualified data, which is then used in a Bayesian statistics regression formulation to update the finite element model. The Bayesian formulation allows the analyst to incorporate engineering judgment (in the form of prior knowledge) into the analysis and helps ensure that reasonable and realistic answers are obtained. The formulation includes true statistical weights derived from experimental data as well as a new formulation of the Bayesian regression problem that reduces the effects of numerical ill-conditioning. Model updates are performed with a simulated free-free beam, a simple steel frame, and a cantilever beam. Improved finite element models of the structures are obtained and several statistical tests are used to ensure that the models are improved.","abstract_html":"This dissertation addresses the task of updating finite element models with frequency response data acquired in a structural dynamics test. Standard statistical techniques are used to generate statistically qualified data, which is then used in a Bayesian statistics regression formulation to update the finite element model. The Bayesian formulation allows the analyst to incorporate engineering judgment (in the form of prior knowledge) into the analysis and helps ensure that reasonable and realistic answers are obtained. 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