Rapid Emergency Response Resilience Assessment of Highway Bridge Networks under Moderate Earthquakes

Longshuang Ma, Chi Zhang, Xinru Liu, Kun Fang and Zhenliang Liu ()
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Longshuang Ma: School of Safety Engineering and Emergency Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
Chi Zhang: School of Safety Engineering and Emergency Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
Xinru Liu: School of Safety Engineering and Emergency Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
Kun Fang: Luoyang Ship Material Research Institute, Luoyang 471023, China
Zhenliang Liu: School of Safety Engineering and Emergency Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China

Sustainability, 2024, vol. 16, issue 13, 1-22

Abstract: Quick post-disaster emergency response of highway bridge networks (HBNs) is vital to alleviating the impact of disasters in affected areas. Nevertheless, achieving their emergency response resilience remains challenging due to the difficulty in accurately capturing the response capacity of HBNs and rapidly evaluating the damage states of regional bridges. This study delves into the emergency response, seismic resilience, and recovery scheduling of HBNs subjected to frequent yet mostly ignored moderate earthquakes. Firstly, the feasibility of intelligent methods is explored as a substitute for nonlinear time-history analysis of regional bridges. Subsequently, for realistic modeling of post-disaster HBNs, a decision tree model is developed to determine potential traffic restrictions imposed on damaged bridges. Moreover, their emergency response functionalities are thoroughly investigated, upon which a comprehensive multi-dimensional resilience metric vector is proposed. Finally, the proposed methodologies are applied to the Sioux Falls HBN as a case study, revealing a decreasing mean value and increasing deviation values in the long term. The results are expected to provide important theoretical and practical emergency response guidance.

Keywords: highway bridge networks; emergency response resilience; intelligent methods; real-time seismic assessment; regional bridges (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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