Structural Vulnerability of Coastal Bridges Under Hurricane Conditions
type: CreativeWork
description: 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 super…
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 super…
author: Majlesi, Seyedarsalan
language: eng
keywords: bridges, coupled Eulerian Lagrangian, finite element, flexibility, nonlinear dynamic analysis, wave-structure interaction
date published: 2024
date modified: 2026-07-27T21:19:21Z
provider: Texas Digital Library
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Texas Digital Library

PropertyValue
property ID: Handle
value: https://hdl.handle.net/20.500.12588/6501