Resilience of coastal bridges under extreme wave-induced loads

Jesika Rahman , Vahid Aghaeidoost , AHM Muntasir Billah

Resilient Cities and Structures ›› 2024, Vol. 3 ›› Issue (2) : 85 -100.

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Resilient Cities and Structures ›› 2024, Vol. 3 ›› Issue (2) : 85 -100. DOI: 10.1016/j.rcns.2024.07.002
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Resilience of coastal bridges under extreme wave-induced loads

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Abstract

Records of wave-induced damage on coastal bridges during natural hazards have been well documented over the past two decades. It is of utmost importance to decipher the loading mechanism and enhance the resilience of coastal bridges during extreme wave-inducing events. Quantification of vulnerability of these structures is an essential step in designing a resilient bridge system. Recently, considerable efforts have been made to study the force applied and the response of coastal bridge systems during extreme wave loading conditions. Although remarkable progress can be found in the quantification of load and response of coastal superstructures, very few studies assessed coastal bridge resiliency against extreme wave-induced loads. This paper adopts a simplified and practical technique to analyze and assess the resilience of coastal bridges exposed to extreme waves. Component-level and system-level fragility analyses form the basis of the resiliency analysis where the recovery functions are adopted based on the damage levels. It is shown that wave period has the highest contribution to the variation of bridge resiliency. Moreover, this study presents the uncertainty quantification in resiliency variation due to changes in wave load intensity. Results show that the bridge resiliency becomes more uncertain as the intensity of wave parameters increases. Finally, possible restoration strategies based on the desired resilience level and the attitude of decision-makers are also discussed.

Keywords

Coastal bridges / Resiliency / Extreme wave loads / Elastomeric bearing / Fragility curves / Resilience index / Recovery function / Restoration strategy

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Jesika Rahman, Vahid Aghaeidoost, AHM Muntasir Billah. Resilience of coastal bridges under extreme wave-induced loads. Resilient Cities and Structures, 2024, 3(2): 85-100 DOI:10.1016/j.rcns.2024.07.002

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Relevance to resilience

This study is focused on investigating the resilience of coastal bridges under extreme wave-induced loads. With the rising frequency and severity of natural hazards taking place in recent times, it is a critical need to develop adequate prevention and recovery strategies during the very early stages of the design of coastal bridges. Since bridges are one of the lifeline structures that allow evacuation of vulnerable communities and transportation between important facilities, maintaining a target resiliency during and post-hazard events is of utmost importance. Studies regarding the resilience quantification of coastal bridges subjected to extreme wave loads considering the highly dynamic nature of wave particles and behavior of substructure, superstructure as well as the connection elements (bearings and shear keys) in the literature are scarce. Thus, with the objective of developing a simplified framework to assess the resiliency of coastal bridges subjected to high wave loads, this study presents a detailed overview of the variation in resiliency of reinforced concrete (RC) I-girder bridges corresponding to different wave loading scenarios. This study presents the uncertainty quantification in resiliency variation due to changes in wave load intensity. Results show that the bridge resiliency becomes more uncertain as the intensity of wave parameters increases.

CRediT authorship contribution statement

Jesika Rahman: Writing - original draft, Methodology, Investigation, Formal analysis, Data curation. Vahid Aghaeidoost: Writing - review & editing, Investigation, Formal analysis. AHM Muntasir Billah: Writing - review & editing, Supervision, Methodology, Funding acquisition, Conceptualization.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This research was sponsored by the Natural Science and Engineering Research Council (NSERC) of Canada through the Discovery Grant and additional funding provided by University of Calgary through the start-up grant. This financial support is greatly appreciated.

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