{"id":{"repo_id":"tdl","oai_identifier":"oai:tdl-ir.tdl.org:20.500.12588/6501"},"canonical_url":"https://search.dev.ndltd.org/etd/tdl/oai:tdl-ir.tdl.org:20.500.12588/6501","repository":{"repo_id":"tdl","name":"Texas Digital Library","base_url":"https://tdl-ir.tdl.org/server/oai/request"},"display":{"title":"Structural Vulnerability of Coastal Bridges Under Hurricane Conditions","abstract":"Hurricane waves can cause catastrophic damage to coastal bridges that lack sufficient clearance. This research focused on improving the understanding of the behavior of coastal bridges under hurricane-induced wave impact. High-fidelity finite element (FE) models were developed within ABAQUS, utilizing a Coupled Eulerian Lagrangian (CEL) analysis, to provide a cost-effective approach for evaluating bridge behavior under various hydrodynamic conditions. An experimental scaled model was used to calibrate numerical models with a range of explicit parameters (mass scaling factor, damping hourglass control, displacement hourglass scaling factor, and bulk viscosity scaling factors) and configurations (mesh size) and to determine optimal filter designs. This work resulted in recommendations for conducting numerical analyses, summarizing best practices for modeling coastal bridges under wave impacts using the CEL technique. The knowledge gained from numerical simulations led to the development of an analytical approach for estimating wave-induced forces affecting a submerged bridge superstructure under various hydrodynamic conditions. The analytical equation was developed using a simplified machine learning (ML) technique with novel attributes. Initially, ML tools were employed to predict the magnitude and duration of the pressure signal reliably. Subsequently, the study utilized the Duhamel integral to derive the mathematical formula for the analytical solution. To validate the accuracy of the analytical model predictions, the results were compared with numerical data obtained from hydrodynamic FE models estimating the wave forces impacting bridge superstructures. Finally, the study compared the maximum wave forces obtained through a physics-based method with the effects of upstream currents on bridge superstructures with varying submergence ratios. The analysis concluded that the proposed analytical model can effectively predict the maximum forces exerted on a bridge superstructure during hurricanes, providing a cost-effective tool to guide the design and retrofitting of coastal bridges.","abstract_html":"Hurricane waves can cause catastrophic damage to coastal bridges that lack sufficient clearance. This research focused on improving the understanding of the behavior of coastal bridges under hurricane-induced wave impact. High-fidelity finite element (FE) models were developed within ABAQUS, utilizing a Coupled Eulerian Lagrangian (CEL) analysis, to provide a cost-effective approach for evaluating bridge behavior under various hydrodynamic conditions. An experimental scaled model was used to calibrate numerical models with a range of explicit parameters (mass scaling factor, damping hourglass control, displacement hourglass scaling factor, and bulk viscosity scaling factors) and configurations (mesh size) and to determine optimal filter designs. This work resulted in recommendations for conducting numerical analyses, summarizing best practices for modeling coastal bridges under wave impacts using the CEL technique. The knowledge gained from numerical simulations led to the development of an analytical approach for estimating wave-induced forces affecting a submerged bridge superstructure under various hydrodynamic conditions. The analytical equation was developed using a simplified machine learning (ML) technique with novel attributes. Initially, ML tools were employed to predict the magnitude and duration of the pressure signal reliably. Subsequently, the study utilized the Duhamel integral to derive the mathematical formula for the analytical solution. To validate the accuracy of the analytical model predictions, the results were compared with numerical data obtained from hydrodynamic FE models estimating the wave forces impacting bridge superstructures. Finally, the study compared the maximum wave forces obtained through a physics-based method with the effects of upstream currents on bridge superstructures with varying submergence ratios. The analysis concluded that the proposed analytical model can effectively predict the maximum forces exerted on a bridge superstructure during hurricanes, providing a cost-effective tool to guide the design and retrofitting of coastal bridges.","abstract_has_math":false,"creators":["Majlesi, Seyedarsalan"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Montoya, Arturo","Matamoros, Adolfo","Du, Ao","Testik, Firat","Haikal, Ghadir"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024","date_published":"2024","updated_at":"2026-07-27T21:19:21Z","subjects":["bridges","coupled Eulerian Lagrangian","finite element","flexibility","nonlinear dynamic analysis","wave-structure interaction"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9798382610184"],"render_values":[{"text":"9798382610184","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/20.500.12588/6501","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Montoya, Arturo","Matamoros, Adolfo","Du, Ao","Testik, Firat","Haikal, Ghadir"]},{"key":"dc:creator","label":"Author","values":["Majlesi, Seyedarsalan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-07-02T14:38:08Z","2026-03-25T16:20:37Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-07-02T14:38:08Z"]},{"key":"dc:date.issued","label":"Date","values":["2024"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["bridges","coupled Eulerian Lagrangian","finite element","flexibility","nonlinear dynamic analysis","wave-structure interaction"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9798382610184","https://hdl.handle.net/20.500.12588/6501"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.12588/6501"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Hurricane waves can cause catastrophic damage to coastal bridges that lack sufficient clearance. This research focused on improving the understanding of the behavior of coastal bridges under hurricane-induced wave impact. High-fidelity finite element (FE) models were developed within ABAQUS, utilizing a Coupled Eulerian Lagrangian (CEL) analysis, to provide a cost-effective approach for evaluating bridge behavior under various hydrodynamic conditions. An experimental scaled model was used to calibrate numerical models with a range of explicit parameters (mass scaling factor, damping hourglass control, displacement hourglass scaling factor, and bulk viscosity scaling factors) and configurations (mesh size) and to determine optimal filter designs. This work resulted in recommendations for conducting numerical analyses, summarizing best practices for modeling coastal bridges under wave impacts using the CEL technique. The knowledge gained from numerical simulations led to the development of an analytical approach for estimating wave-induced forces affecting a submerged bridge superstructure under various hydrodynamic conditions. The analytical equation was developed using a simplified machine learning (ML) technique with novel attributes. Initially, ML tools were employed to predict the magnitude and duration of the pressure signal reliably. Subsequently, the study utilized the Duhamel integral to derive the mathematical formula for the analytical solution. To validate the accuracy of the analytical model predictions, the results were compared with numerical data obtained from hydrodynamic FE models estimating the wave forces impacting bridge superstructures. Finally, the study compared the maximum wave forces obtained through a physics-based method with the effects of upstream currents on bridge superstructures with varying submergence ratios. The analysis concluded that the proposed analytical model can effectively predict the maximum forces exerted on a bridge superstructure during hurricanes, providing a cost-effective tool to guide the design and retrofitting of coastal bridges."]},{"key":"dc:title","label":"Title","values":["Structural Vulnerability of Coastal Bridges Under Hurricane Conditions"]}]}],"canonical_facts":{"dc:contributor":["Montoya, Arturo","Matamoros, Adolfo","Du, Ao","Testik, Firat","Haikal, Ghadir"],"dc:creator":["Majlesi, Seyedarsalan"],"dc:date.accessioned":["2024-07-02T14:38:08Z","2026-03-25T16:20:37Z"],"dc:date.available":["2024-07-02T14:38:08Z"],"dc:date.issued":["2024"],"dc:description.abstract":["Hurricane waves can cause catastrophic damage to coastal bridges that lack sufficient clearance. This research focused on improving the understanding of the behavior of coastal bridges under hurricane-induced wave impact. High-fidelity finite element (FE) models were developed within ABAQUS, utilizing a Coupled Eulerian Lagrangian (CEL) analysis, to provide a cost-effective approach for evaluating bridge behavior under various hydrodynamic conditions. An experimental scaled model was used to calibrate numerical models with a range of explicit parameters (mass scaling factor, damping hourglass control, displacement hourglass scaling factor, and bulk viscosity scaling factors) and configurations (mesh size) and to determine optimal filter designs. This work resulted in recommendations for conducting numerical analyses, summarizing best practices for modeling coastal bridges under wave impacts using the CEL technique. The knowledge gained from numerical simulations led to the development of an analytical approach for estimating wave-induced forces affecting a submerged bridge superstructure under various hydrodynamic conditions. The analytical equation was developed using a simplified machine learning (ML) technique with novel attributes. Initially, ML tools were employed to predict the magnitude and duration of the pressure signal reliably. Subsequently, the study utilized the Duhamel integral to derive the mathematical formula for the analytical solution. To validate the accuracy of the analytical model predictions, the results were compared with numerical data obtained from hydrodynamic FE models estimating the wave forces impacting bridge superstructures. Finally, the study compared the maximum wave forces obtained through a physics-based method with the effects of upstream currents on bridge superstructures with varying submergence ratios. The analysis concluded that the proposed analytical model can effectively predict the maximum forces exerted on a bridge superstructure during hurricanes, providing a cost-effective tool to guide the design and retrofitting of coastal bridges."],"dc:identifier":["9798382610184","https://hdl.handle.net/20.500.12588/6501"],"dc:identifier.uri":["https://hdl.handle.net/20.500.12588/6501"],"dc:language":["eng"],"dc:subject":["bridges","coupled Eulerian Lagrangian","finite element","flexibility","nonlinear dynamic analysis","wave-structure interaction"],"dc:title":["Structural Vulnerability of Coastal Bridges Under Hurricane Conditions"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:19:21Z"}