Multi-disciplinary seismic resilience modeling for developing mitigation policies and recovery planning

Milad Roohi , Saeid Ghasemi , Omar Sediek , Hwayoung Jeon , John W. van de Lindt , Martin Shields , Sara Hamideh , Harvey Cutler
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Abstract

The multi-disciplinary data and information available at a community level comprise the foundation of natural hazard resilience modeling. These data enable and inform mitigation and recovery planning decisions prior to and following damaging events such as earthquakes. This paper presents a multi-disciplinary seismic resilience modeling methodology to assess the vulnerability of the built environment and economic systems. This methodology can assist decision-makers with developing effective mitigation policies to improve the seismic resilience of communities. Two complementary modeling strategies are designed to examine the impacts of scenario earthquakes from a combined engineering and economic perspective. The engineering model is developed using a probabilistic fragility-based modeling approach and is analyzed using Monte Carlo (MC) simulations subject to seismic multi-hazard, including simulated ground shaking and resulting liquefaction of the soil, to quantify the physical damage to buildings and electric power substations (EPS). The outcome of the analysis is subsequently used as input to repair and recovery models to quantify repair cost and recovery time metrics for buildings and as input to functionality models to estimate the functionality of individual buildings and substations by accounting for their interdependency. The economic model consists of a spatial computable general equilibrium (SCGE) model that aggregates commercial buildings into sectors for retail, manufacturing, services, etc., and aggregates residential buildings into a wide range of household groups. The SCGE model employs building functionality estimates to quantify the economic losses. The outcomes of this integrated modeling consist of engineering and economic impact metrics, which are used to investigate mitigation actions to help inform a community on approaches to achieve its resilience goals. An illustrative case study of Salt Lake County (SLC), Utah, developed through an extensive collaborative partnership and engagement with SLC officials, is presented. The results demonstrate the effectiveness of the proposed methodology in quantifying the loss and functional recovery of infrastructure systems, the impacts on capital stock, employment, and household income and the effect of various mitigation strategies in reducing the losses and functional recovery time subject to earthquakes with varying intensities.

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为制定减灾政策和恢复规划建立多学科抗震能力模型
社区层面的多学科数据和信息构成了自然灾害复原力建模的基础。在地震等破坏性事件发生之前和发生之后,这些数据为减灾和恢复规划决策提供了依据和信息。本文介绍了一种多学科抗震能力建模方法,用于评估建筑环境和经济系统的脆弱性。该方法可帮助决策者制定有效的减灾政策,提高社区的抗震能力。设计了两种互补的建模策略,从工程和经济的角度综合考察情景地震的影响。工程模型采用基于概率脆性的建模方法开发,并使用蒙特卡洛(MC)模拟法对地震多重危害进行分析,包括模拟地震动和由此产生的土壤液化,以量化对建筑物和变电站(EPS)造成的物理破坏。分析结果随后将作为修复和恢复模型的输入,以量化建筑物的修复成本和恢复时间指标,并作为功能模型的输入,通过考虑单个建筑物和变电站之间的相互依存关系来估算其功能。经济模型包括一个空间可计算一般均衡(SCGE)模型,该模型将商业建筑汇总到零售、制造、服务等部门,并将住宅建筑汇总到各种家庭群体。SCGE 模型采用建筑物功能估算来量化经济损失。这种综合建模的结果包括工程和经济影响指标,用于调查缓解行动,帮助社区了解实现抗灾目标的方法。本报告介绍了犹他州盐湖县(SLC)的一个示例研究,该研究是通过与盐湖县官员的广泛合作和参与而开发的。研究结果表明,所建议的方法在量化基础设施系统的损失和功能恢复、对资本存量、就业和家庭收入的影响以及各种减灾策略在减少不同强度地震的损失和功能恢复时间方面的效果非常有效。
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