{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/34471"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/34471","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Seismic site response analysis and extraction of dynamic soil behavior and pore pressure response from downhole array measurements","abstract":"Seismic site response analysis is commonly used to predict ground response due to local soil effects. Advancements in the knowledge of shear-induced excess pore pressure generation has led to the development and implementation of pore pressure response models for site response analysis with effective stress consideration. This thesis chiefly regards the further development of an inverse analysis procedure to extract dynamic soil behavior and pore pressure response from downhole array measurements. Downhole arrays are increasingly being deployed to measure motions at the ground surface and within the soil profile, with some arrays instrumented to measure the pore pressure response throughout the soil profile. The measurements from these arrays provide valuable data to validate site response analysis models and also to reveal the coupled soil behavior and pore pressure response during seismic excitation. However, the current approaches do not fully benefit from the downhole array measurements. Once the prediction is different from the measurements, site response analysis models cannot be readily calibrated to match field measurements. Early developments in inverse analysis schemes allowed for the identification of soil properties from downhole array measurements, but the identified parameters could not be readily integrated into a material constitutive model for future use in site response analysis. Recent development of an inverse analysis algorithm, Self-learning Simulations (SelfSim), integrated field measurements with site response analysis to capture the measured ground response while extracting the underlying soil behavior under total stress consideration. This research extends the SelfSim inverse analysis algorithm to effective stress consideration by including measurements of both motions and pore pressure response from downhole arrays. The extended framework is able to gradually capture the measured global iii response while simultaneously extracting the underlying soil behavior and pore pressure response. When used in site response analysis, the resulting soil model and pore pressure response model provide correct ground motion and pore pressure response throughout the soil profile. The extracted soil behavior and pore pressure response can be enhanced using additional field measurements. The algorithm is verified with four synthetic downhole array recordings and is also applied to downhole array recordings from the Imperial Valley Wildlife Liquefaction Array. The extracted soil behavior is compared with laboratory measurements and is used to identify the effects of excess pore pressures, number of loading cycles, and loading rate on soil behavior. The extracted pore pressure response is compared with current pore pressure response models employed in seismic site response simulation to assess the validity of such models.","abstract_html":"Seismic site response analysis is commonly used to predict ground response due to local soil effects. Advancements in the knowledge of shear-induced excess pore pressure generation has led to the development and implementation of pore pressure response models for site response analysis with effective stress consideration. This thesis chiefly regards the further development of an inverse analysis procedure to extract dynamic soil behavior and pore pressure response from downhole array measurements. Downhole arrays are increasingly being deployed to measure motions at the ground surface and within the soil profile, with some arrays instrumented to measure the pore pressure response throughout the soil profile. The measurements from these arrays provide valuable data to validate site response analysis models and also to reveal the coupled soil behavior and pore pressure response during seismic excitation. However, the current approaches do not fully benefit from the downhole array measurements. Once the prediction is different from the measurements, site response analysis models cannot be readily calibrated to match field measurements. Early developments in inverse analysis schemes allowed for the identification of soil properties from downhole array measurements, but the identified parameters could not be readily integrated into a material constitutive model for future use in site response analysis. Recent development of an inverse analysis algorithm, Self-learning Simulations (SelfSim), integrated field measurements with site response analysis to capture the measured ground response while extracting the underlying soil behavior under total stress consideration. This research extends the SelfSim inverse analysis algorithm to effective stress consideration by including measurements of both motions and pore pressure response from downhole arrays. The extended framework is able to gradually capture the measured global iii response while simultaneously extracting the underlying soil behavior and pore pressure response. When used in site response analysis, the resulting soil model and pore pressure response model provide correct ground motion and pore pressure response throughout the soil profile. The extracted soil behavior and pore pressure response can be enhanced using additional field measurements. The algorithm is verified with four synthetic downhole array recordings and is also applied to downhole array recordings from the Imperial Valley Wildlife Liquefaction Array. The extracted soil behavior is compared with laboratory measurements and is used to identify the effects of excess pore pressures, number of loading cycles, and loading rate on soil behavior. The extracted pore pressure response is compared with current pore pressure response models employed in seismic site response simulation to assess the validity of such models.","abstract_has_math":false,"creators":["Groholski, David"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Hashash, Youssef M.","Ghaboussi, Jamshid","Long, James H.","Mesri, Gholamreza","Olson, Scott M.","Matasovic, Neven"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-09-18T21:18:43Z","date_published":"2012-09-18T21:18:43Z","updated_at":"2026-07-22T22:25:31Z","subjects":["downhole array","inverse analysis","soil behavior","site response analysis","pore pressure response"],"languages":["en"],"rights":["Copyright 2012 David Groholski"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/34471","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hashash, Youssef M.","Ghaboussi, Jamshid","Long, James H.","Mesri, Gholamreza","Olson, Scott M.","Matasovic, Neven"]},{"key":"dc:creator","label":"Author","values":["Groholski, David"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2012-09-18T21:18:43Z","2014-09-18T10:00:35Z","2012-08"]},{"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":["downhole array","inverse analysis","soil behavior","site response analysis","pore pressure response"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2012 David Groholski"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/34471"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Seismic site response analysis is commonly used to predict ground response due to local soil effects. Advancements in the knowledge of shear-induced excess pore pressure generation has led to the development and implementation of pore pressure response models for site response analysis with effective stress consideration. This thesis chiefly regards the further development of an inverse analysis procedure to extract dynamic soil behavior and pore pressure response from downhole array measurements. Downhole arrays are increasingly being deployed to measure motions at the ground surface and within the soil profile, with some arrays instrumented to measure the pore pressure response throughout the soil profile. The measurements from these arrays provide valuable data to validate site response analysis models and also to reveal the coupled soil behavior and pore pressure response during seismic excitation. However, the current approaches do not fully benefit from the downhole array measurements. Once the prediction is different from the measurements, site response analysis models cannot be readily calibrated to match field measurements. Early developments in inverse analysis schemes allowed for the identification of soil properties from downhole array measurements, but the identified parameters could not be readily integrated into a material constitutive model for future use in site response analysis. Recent development of an inverse analysis algorithm, Self-learning Simulations (SelfSim), integrated field measurements with site response analysis to capture the measured ground response while extracting the underlying soil behavior under total stress consideration. This research extends the SelfSim inverse analysis algorithm to effective stress consideration by including measurements of both motions and pore pressure response from downhole arrays. The extended framework is able to gradually capture the measured global iii response while simultaneously extracting the underlying soil behavior and pore pressure response. When used in site response analysis, the resulting soil model and pore pressure response model provide correct ground motion and pore pressure response throughout the soil profile. The extracted soil behavior and pore pressure response can be enhanced using additional field measurements. The algorithm is verified with four synthetic downhole array recordings and is also applied to downhole array recordings from the Imperial Valley Wildlife Liquefaction Array. The extracted soil behavior is compared with laboratory measurements and is used to identify the effects of excess pore pressures, number of loading cycles, and loading rate on soil behavior. 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Advancements in the knowledge of shear-induced excess pore pressure generation has led to the development and implementation of pore pressure response models for site response analysis with effective stress consideration. This thesis chiefly regards the further development of an inverse analysis procedure to extract dynamic soil behavior and pore pressure response from downhole array measurements. Downhole arrays are increasingly being deployed to measure motions at the ground surface and within the soil profile, with some arrays instrumented to measure the pore pressure response throughout the soil profile. The measurements from these arrays provide valuable data to validate site response analysis models and also to reveal the coupled soil behavior and pore pressure response during seismic excitation. However, the current approaches do not fully benefit from the downhole array measurements. Once the prediction is different from the measurements, site response analysis models cannot be readily calibrated to match field measurements. Early developments in inverse analysis schemes allowed for the identification of soil properties from downhole array measurements, but the identified parameters could not be readily integrated into a material constitutive model for future use in site response analysis. Recent development of an inverse analysis algorithm, Self-learning Simulations (SelfSim), integrated field measurements with site response analysis to capture the measured ground response while extracting the underlying soil behavior under total stress consideration. This research extends the SelfSim inverse analysis algorithm to effective stress consideration by including measurements of both motions and pore pressure response from downhole arrays. The extended framework is able to gradually capture the measured global iii response while simultaneously extracting the underlying soil behavior and pore pressure response. When used in site response analysis, the resulting soil model and pore pressure response model provide correct ground motion and pore pressure response throughout the soil profile. The extracted soil behavior and pore pressure response can be enhanced using additional field measurements. The algorithm is verified with four synthetic downhole array recordings and is also applied to downhole array recordings from the Imperial Valley Wildlife Liquefaction Array. The extracted soil behavior is compared with laboratory measurements and is used to identify the effects of excess pore pressures, number of loading cycles, and loading rate on soil behavior. The extracted pore pressure response is compared with current pore pressure response models employed in seismic site response simulation to assess the validity of such models.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-06-27T15:57:55Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Groholski_David.pdf: 13690651 bytes, checksum: aae0bd744a8e998df9a53a074f41597a (MD5)","Made available in DSpace on 2012-09-18T21:18:43Z (GMT). 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