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Optimal decision making in post-hazard bridge recovery strategies for transportation networks after seismic events
Geomatics, Natural Hazards and Risk ( IF 4.2 ) Pub Date : 2021-08-30 , DOI: 10.1080/19475705.2021.1961881
Sungsik Yoon 1 , Wonho Suh 2 , Young-Joo Lee 3
Affiliation  

Abstract

In this study, optimal post-hazard bridge recovery strategies were proposed for transportation networks under seismic conditions. To predict the performance of the transportation network, a robust performance measure, total system travel time (TSTT), was employed, and an artificial neural network (ANN)-based surrogate model was developed to enable an accelerated Monte Carlo analysis. In addition, a sensitivity analysis based on the benefit–cost ratio was proposed to support optimal decision making immediately after an earthquake. To demonstrate the proposed methodology, an actual transportation network in South Korea was adopted, and a network map was reconstructed based on geographic information system (GIS) data. A surrogate model for network performance evaluation was constructed using training data generated based on historical earthquake epicenters. In addition, the damage ratio and required recovery days according to the damage states of bridges were employed to perform network recovery analysis. For the numerical analysis, a limited budget was set for each scenario, and the recovery and damage curve were compared with existing priority strategy. The numerical results showed that the priority strategy of bridge restoration determined through the benefit–cost analysis generated a faster recovery curve and significantly reduced the damage, as compared to existing strategy. Therefore, it is concluded that the proposed methodology enables optimal decision making and also helps risk management that can minimize the economic damage.



中文翻译:

地震后交通网络灾后桥梁恢复策略的最优决策

摘要

在这项研究中,针对地震条件下的交通网络提出了最佳的灾后桥梁恢复策略。为了预测交通网络的性能,采用了一种稳健的性能测量方法,即总系统行程时间 (TSTT),并开发了基于人工神经网络 (ANN) 的替代模型,以实现加速蒙特卡罗分析。此外,还提出了基于收益成本比的敏感性分析,以支持地震后立即做出最佳决策。为了演示所提出的方法,采用了韩国的实际交通网络,并基于地理信息系统 (GIS) 数据重建了网络地图。使用基于历史地震震中生成的训练数据构建了网络性能评估的替代模型。此外,根据桥梁的损坏状态,采用损坏率和所需恢复天数进行网络恢复分析。对于数值分析,为每个场景设定了有限的预算,并将恢复和破坏曲线与现有的优先策略进行比较。数值结果表明,与现有策略相比,通过收益-成本分析确定的桥梁修复优先策略产生了更快的恢复曲线并显着减少了损坏。因此,得出的结论是,所提出的方法可以实现最佳决策,也有助于风险管理,最大限度地减少经济损失。根据桥梁的损坏状态,采用损坏率和所需恢复天数进行网络恢复分析。对于数值分析,为每个场景设定了有限的预算,并将恢复和破坏曲线与现有的优先策略进行比较。数值结果表明,与现有策略相比,通过收益-成本分析确定的桥梁修复优先策略产生了更快的恢复曲线并显着减少了损坏。因此,得出的结论是,所提出的方法可以实现最佳决策,也有助于风险管理,最大限度地减少经济损失。根据桥梁的损坏状态,采用损坏率和所需恢复天数进行网络恢复分析。对于数值分析,为每个场景设定了有限的预算,并将恢复和破坏曲线与现有的优先策略进行比较。数值结果表明,与现有策略相比,通过收益-成本分析确定的桥梁修复优先策略产生了更快的恢复曲线并显着减少了损坏。因此,得出的结论是,所提出的方法可以实现最佳决策,也有助于风险管理,最大限度地减少经济损失。为每个方案设定了有限的预算,并将恢复和损害曲线与现有的优先战略进行了比较。数值结果表明,与现有策略相比,通过收益-成本分析确定的桥梁修复优先策略产生了更快的恢复曲线并显着减少了损坏。因此,得出的结论是,所提出的方法可以实现最佳决策,也有助于风险管理,最大限度地减少经济损失。为每个情景设定了有限的预算,并将恢复和破坏曲线与现有的优先战略进行了比较。数值结果表明,与现有策略相比,通过收益-成本分析确定的桥梁修复优先策略产生了更快的恢复曲线并显着减少了损坏。因此,得出的结论是,所提出的方法可以实现最佳决策,也有助于风险管理,最大限度地减少经济损失。

更新日期:2021-08-31
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