Long-term loss assessment of coastal bridges from hurricanes incorporating overturning failure mode

Deming Zhu , Yaohan Li , You Dong , Peng Yuan

Advances in Bridge Engineering ›› 2021, Vol. 2 ›› Issue (1)

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Advances in Bridge Engineering ›› 2021, Vol. 2 ›› Issue (1) DOI: 10.1186/s43251-020-00030-7
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Long-term loss assessment of coastal bridges from hurricanes incorporating overturning failure mode

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Abstract

Coastal highway bridge is an essential component of the transportation system but threatened by natural hazards such as hurricanes. Damaged highway bridges result in not only transportation disruption, but also tremendous financial, societal, and life loss. Therefore, vulnerability and loss assessments of bridges under hurricane events are becoming primary concerns for decision-makers. This study provides an elaborate framework to assess the vulnerability and long-term loss of coastal bridges subjected to hurricane hazards based on three-dimensional (3D) numerical analyses. A 3D Computational Fluid Dynamics (CFD) numerical model is established to investigate wave-bridge interaction and a Finite Element (FE) model is established for the bridge to calculate structural responses under wave impacts. Based on the numerical results, the effects of wave force and overturning moment on structural capacity are studied and a probabilistic vulnerability model is developed. Structural demand, capacity, and limit states are determined, respectively. Uncertainties associated with wave parameters, structural capacity, and material properties, and the resulting consequences are considered. Then, fragility curves are calculated, and long-term damage loss is assessed. The proposed approach can benefit the management and design of coastal bridges against the impacts of hurricane hazards.

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Deming Zhu, Yaohan Li, You Dong, Peng Yuan. Long-term loss assessment of coastal bridges from hurricanes incorporating overturning failure mode. Advances in Bridge Engineering, 2021, 2(1): DOI:10.1186/s43251-020-00030-7

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Funding

National Key R&D Program of China(2019YFB1600702)

Research Grant Council of Hong Kong(No. PolyU 15219819)

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