{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108707"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108707","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Target reliability index optimization framework for building classes","abstract":"Buildings are vital for critical community functions and it is of great importance to efficiently invest the limited societal resources in the design of the buildings. To achieve economically viable and safe building structures, careful assessment of risk from future hazards is required. In practice, the risk to building structures is regulated by structural design codes through target safety levels, which are reflected in many code factors, including partial safety factors, load combination factors, and modification factors. The target safety levels in the design codes are primarily based on experience-based approach without a comprehensive risk assessment, leading to a possible sub-optimality in building performance and resource allocation. In addition, despite being designed in accordance with the code provisions, communities have suffered significant socio-economic losses when natural hazards have occurred. Primary reason for such losses is that building design codes mainly focus on the life safety objective and achieving post-hazard functionality has never been a direct goal, rather a subsidiary goal that is expected to satisfy. Since the impact of a hazard is spread over a region, the corresponding risks can be managed effectively by considering the community impact. Determining the target safety levels by considering community disaster impact will help move toward effective risk management for building structures. However, community disaster impact can be properly evaluated by considering loss interdependency among different buildings, which could be a complex task. Furthermore, implementing a community-level objective to design safety level determination requires the establishment of feasible methods to calculate it in a reasonable time. This research develops a practical and efficient framework for target safety optimization of building classes based on community-level objective, contributing to enhance the performance of communities in the event of a disaster. The proposed framework incorporates the building loss interdependencies in the risk evaluation. The framework focuses mainly on seismic hazard. However, the concepts and formulations are applicable to other types of hazards. To reduce the computation cost in implementing optimization process in target safety level determination, the framework employs an efficient procedure of using neural networks to approximate the seismic response of buildings with common characteristics (occupancy use, and type and size of lateral resisting system). The framework is illustrated for optimizing the target reliability indexes of office and hospital building classes exposed to seismic hazard, with minimizing regional economic cost as the objective.","abstract_html":"Buildings are vital for critical community functions and it is of great importance to efficiently invest the limited societal resources in the design of the buildings. To achieve economically viable and safe building structures, careful assessment of risk from future hazards is required. In practice, the risk to building structures is regulated by structural design codes through target safety levels, which are reflected in many code factors, including partial safety factors, load combination factors, and modification factors. The target safety levels in the design codes are primarily based on experience-based approach without a comprehensive risk assessment, leading to a possible sub-optimality in building performance and resource allocation. In addition, despite being designed in accordance with the code provisions, communities have suffered significant socio-economic losses when natural hazards have occurred. Primary reason for such losses is that building design codes mainly focus on the life safety objective and achieving post-hazard functionality has never been a direct goal, rather a subsidiary goal that is expected to satisfy. Since the impact of a hazard is spread over a region, the corresponding risks can be managed effectively by considering the community impact. Determining the target safety levels by considering community disaster impact will help move toward effective risk management for building structures. However, community disaster impact can be properly evaluated by considering loss interdependency among different buildings, which could be a complex task. Furthermore, implementing a community-level objective to design safety level determination requires the establishment of feasible methods to calculate it in a reasonable time. This research develops a practical and efficient framework for target safety optimization of building classes based on community-level objective, contributing to enhance the performance of communities in the event of a disaster. The proposed framework incorporates the building loss interdependencies in the risk evaluation. The framework focuses mainly on seismic hazard. However, the concepts and formulations are applicable to other types of hazards. To reduce the computation cost in implementing optimization process in target safety level determination, the framework employs an efficient procedure of using neural networks to approximate the seismic response of buildings with common characteristics (occupancy use, and type and size of lateral resisting system). The framework is illustrated for optimizing the target reliability indexes of office and hospital building classes exposed to seismic hazard, with minimizing regional economic cost as the objective.","abstract_has_math":false,"creators":["Gudipati, Vamshi Krishna"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Cha, Eun Jeong","Gardoni, Paolo","Fahnestock, Larry A","Meidani, Hadi"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-10-07T22:49:59Z","date_published":"2020-10-07T22:49:59Z","updated_at":"2026-07-22T22:24:48Z","subjects":["building class","interdependency","target reliability index","seismic","surrogate model"],"languages":["en"],"rights":["Copyright 2020 Vamshi Krishna Gudipati"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108707","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Cha, Eun Jeong","Gardoni, Paolo","Fahnestock, Larry A","Meidani, Hadi"]},{"key":"dc:creator","label":"Author","values":["Gudipati, Vamshi Krishna"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-10-07T22:49:59Z","2022-10-07T22:50:13Z","2020-07-15","2020-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"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":["building class","interdependency","target reliability index","seismic","surrogate model"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Vamshi Krishna Gudipati"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/108707"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Buildings are vital for critical community functions and it is of great importance to efficiently invest the limited societal resources in the design of the buildings. To achieve economically viable and safe building structures, careful assessment of risk from future hazards is required. In practice, the risk to building structures is regulated by structural design codes through target safety levels, which are reflected in many code factors, including partial safety factors, load combination factors, and modification factors. The target safety levels in the design codes are primarily based on experience-based approach without a comprehensive risk assessment, leading to a possible sub-optimality in building performance and resource allocation. In addition, despite being designed in accordance with the code provisions, communities have suffered significant socio-economic losses when natural hazards have occurred. Primary reason for such losses is that building design codes mainly focus on the life safety objective and achieving post-hazard functionality has never been a direct goal, rather a subsidiary goal that is expected to satisfy. Since the impact of a hazard is spread over a region, the corresponding risks can be managed effectively by considering the community impact. Determining the target safety levels by considering community disaster impact will help move toward effective risk management for building structures. However, community disaster impact can be properly evaluated by considering loss interdependency among different buildings, which could be a complex task. Furthermore, implementing a community-level objective to design safety level determination requires the establishment of feasible methods to calculate it in a reasonable time. This research develops a practical and efficient framework for target safety optimization of building classes based on community-level objective, contributing to enhance the performance of communities in the event of a disaster. The proposed framework incorporates the building loss interdependencies in the risk evaluation. The framework focuses mainly on seismic hazard. However, the concepts and formulations are applicable to other types of hazards. To reduce the computation cost in implementing optimization process in target safety level determination, the framework employs an efficient procedure of using neural networks to approximate the seismic response of buildings with common characteristics (occupancy use, and type and size of lateral resisting system). The framework is illustrated for optimizing the target reliability indexes of office and hospital building classes exposed to seismic hazard, with minimizing regional economic cost as the objective.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-08-01","The student, Vamshi Krishna Gudipati, accepted the attached license on 2020-07-15 at 09:55.","The student, Vamshi Krishna Gudipati, submitted this Dissertation for approval on 2020-07-15 at 10:08.","This Dissertation was approved for publication on 2020-07-15 at 14:07.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15630 on 2020-10-02 at 15:50:51","Made available in DSpace on 2020-10-07T22:49:59Z (GMT). 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To achieve economically viable and safe building structures, careful assessment of risk from future hazards is required. In practice, the risk to building structures is regulated by structural design codes through target safety levels, which are reflected in many code factors, including partial safety factors, load combination factors, and modification factors. The target safety levels in the design codes are primarily based on experience-based approach without a comprehensive risk assessment, leading to a possible sub-optimality in building performance and resource allocation. In addition, despite being designed in accordance with the code provisions, communities have suffered significant socio-economic losses when natural hazards have occurred. Primary reason for such losses is that building design codes mainly focus on the life safety objective and achieving post-hazard functionality has never been a direct goal, rather a subsidiary goal that is expected to satisfy. Since the impact of a hazard is spread over a region, the corresponding risks can be managed effectively by considering the community impact. Determining the target safety levels by considering community disaster impact will help move toward effective risk management for building structures. However, community disaster impact can be properly evaluated by considering loss interdependency among different buildings, which could be a complex task. Furthermore, implementing a community-level objective to design safety level determination requires the establishment of feasible methods to calculate it in a reasonable time. This research develops a practical and efficient framework for target safety optimization of building classes based on community-level objective, contributing to enhance the performance of communities in the event of a disaster. The proposed framework incorporates the building loss interdependencies in the risk evaluation. The framework focuses mainly on seismic hazard. However, the concepts and formulations are applicable to other types of hazards. To reduce the computation cost in implementing optimization process in target safety level determination, the framework employs an efficient procedure of using neural networks to approximate the seismic response of buildings with common characteristics (occupancy use, and type and size of lateral resisting system). The framework is illustrated for optimizing the target reliability indexes of office and hospital building classes exposed to seismic hazard, with minimizing regional economic cost as the objective.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-08-01","The student, Vamshi Krishna Gudipati, accepted the attached license on 2020-07-15 at 09:55.","The student, Vamshi Krishna Gudipati, submitted this Dissertation for approval on 2020-07-15 at 10:08.","This Dissertation was approved for publication on 2020-07-15 at 14:07.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15630 on 2020-10-02 at 15:50:51","Made available in DSpace on 2020-10-07T22:49:59Z (GMT). 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