Optimizing risk mitigation investment strategies for improving post-earthquake road network resilience

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جزئیات بیشتر

انتشار

۲۰۲۱

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نشریه الزویر

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scopus – master journals – JCR

ایمپکت فاکتور

۴٫۲۷۶ در سال ۲۰۲۰

شاخص H_index

۲۶ در سال ۲۰۲۱

شاخص SJR

۰٫۹۰۱ در سال ۲۰۲۰

شاخص Quartile (چارک)

Q1 در سال ۲۰۲۰

مدل مفهومی

ندارد

پرسشنامه

ندارد

متغیر

ندارد

رفرنس

دارد

قوانین استفاده

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Optimizing risk mitigation investment strategies for improving post-earthquake road network resilience


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Optimizing risk mitigation investment strategies for improving post-earthquake road network resilience

Abstract

The  road network is a major urban lifeline, and its  post-earthquake resiliency is crucial to rapid and reliable rescue work. This  study aims to optimize risk  mitigation investment strategies for improving post-earthquake road network resilience. First,  instead of theoret- ical   assumptions on   link   failure  probability,  an   empirical  predictive  model  of  debris obstruction of  collapsed buildings was used to calculate link   connectivity probability. Second, the Monte Carlo  simulation method was employed to calculate post-earthquake road network accessibility based on  the results of  link  connectivity reliability. Third, an optimal  risk    mitigation  investment  model  was  used  in   order  to  maximize  post- earthquake network accessibility with different government budgets. A case study was analyzed by  using the proposed method in  an  Shanghai historical area. Results may help local  governments  make  better  decisions  of   risk   mitigation  strategies  in   regard to earthquakes.

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  1. Introduction

The worldwide urbanization development brings public safety as a major focus of governments. Natural disasters such as earthquakes can  potentially cause extensive amounts of damage to property and life. The urban road network is an  impor- tant lifeline following an earthquake, and its connectivity is essential for emergency rescue work. Taking the 1976 Tangshan earthquake and the 1995 Hanshin earthquake in Japan as examples, survivors of the first  day  were 81% and 80.5%, which dropped to  ۳۳٫۷% and 36.8% the next day(Guo and Chen,  ۱۹۸۰, Yang and Shen,  ۲۰۰۵).

Previous studies investigated the impacts of earthquakes on road network vulnerability, see  Mine  and Kawai  (۱۹۸۲) and Berdica (2002) as examples, and mitigation strategies for  improving road network resiliency (Ong  et al., 2011). In general, this problem is concerned with finding the overall possible loss of road network under certain link failure probability follow- ing earthquakes. The simulation is usually used for finding critical links or optimal facility locations under different scenar- ios.  However, previous studies usually assumed a certain link  will  fail  randomly or  under some theoretical assumptions following an earthquake (Rupi  et al., 2015). In fact, the link failure probability after earthquake is directly related to building and roadway conditions along the link,  for  example the structure reliability of buildings and the widths of roadways. It is essential to incorporate the empirical link failure probability into network modeling, on the one  hand, it may benefit to more

accurately evaluate the possible loss  of road network following earthquake; on the other hand, it could help to connect the mitigation investment strategies with engineering work for improving the building and roadway conditions.

In this study, an empirical method was  proposed in order to optimize risk mitigation investment strategies based on post- earthquake road network resilience. First,  instead of theoretical assumptions, link  connectivity probability was  calculated based on the predictive model of debris obstructing collapsed buildings. Second, post-earthquake road network accessibility was  evaluated by Monte Carlo  simulation method based on  link  connectivity reliability results. Third,  an  optimal risk  mit- igation investment model was  proposed in order to maximize post-earthquake network accessibility with different govern- ment budgets. A case  study in the Shanghai historical area was  conducted by using the proposed method.

The contents of the paper are  as follows. Section 2 provides a general literature review of post-earthquake road network vulnerability analysis. Section 3 describes the methodology of post-earthquake link  connectivity reliability. Section 4 shows how to evaluate post-earthquake road network reliability. Section 5 proposes earthquake mitigation investment model. Sec- tion 6 describes the case  study in Yu Garden, a historical area in Shanghai.

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