Long-term resilience and loss assessment of highway bridges under multiple natural hazards. Issue 4 (2nd April 2020)

• Record Type: Journal Article
• Authors: Li, Yaohan; Dong, You; Frangopol, Dan M.; Gautam, Dipendra
• Is Part Of: Structure and infrastructure engineering. Volume 16:Issue 4(2020)
• Page Start: 626
• Page End: 641
• Publication Date: 2020-04-02
• Subjects: Resilience -- long-term loss assessment -- highway bridges -- life-cycle performance -- multiple natural hazards; Structural analysis (Engineering) -- Periodicals; Structural engineering -- Periodicals; Buildings -- Performance -- Periodicals; 620.005
• DOI: 10.1080/15732479.2019.1699936
• Languages: English
• ISSNs: 1573-2479

Abstract

Abstract: Highway bridges play a significant role in maintaining safety and functionality of the society. The immediate damage of highway bridges caused by natural hazards can disrupt transportation systems, impede rescue and recovery activities. This disruption may result in tremendous financial and societal losses. Therefore, assessing vulnerability, recovery capability, and potential losses of bridges under natural hazards becomes a primary concern to decision-makers to facilitate the emergency response and recovery efforts. Under these concerns, resilience is a paramount performance indicator to evaluate and recover the functionality of structural systems under extreme events. In this article, an integrated framework for long-term resilience and loss assessment of highway bridges under multiple independent natural hazards is presented. The impacts of extreme events such as earthquakes, hurricanes and floods on the life-cycle performance of bridges are illustrated. A stochastic renewal process model of the random occurrence of hazard events is used to compute the expected long-term resilience and damage loss by considering both time-independent and time varying occurrence characteristics. The proposed approach is applied to a bridge by considering the impacts of earthquake and hurricane hazards. The proposed framework can be implemented to the design, maintenance and retrofit optimisation of infrastructure systems under multiple extreme events.