将基础设施恢复建模为资源受限的项目调度问题,从而量化抗灾能力

Taylor Glen Johnson, Jorge Leandro, D. Ahadzie
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引用次数: 0

摘要

摘要。个人、企业和机构对基础设施的依赖增加了对自然灾害造成的破坏的脆弱性。为了评估自然灾害对基础设施性能的影响,本文提出了一个量化抗灾能力的框架。该框架扩展了之前的文献研究,通过提出标准化的评估期来提高复原力指标的可比性。恢复是评估抗灾能力的核心要素,尤其是在极端灾害情况下,因此我们在应用资源受限项目调度问题(RCPSP)的基础上开发了一个恢复模型。该恢复模型为评估不同事件以及不同研究区域之间的抗洪能力提供了理论依据。复原力框架和复原模型已被应用于一项案例研究,以评估加纳阿克拉一个社区 Alajo 的建筑基础设施对洪水灾害的复原力。对于所调查的三种洪水事件(5 年、50 年和 500 年重现期)和所选择的标准化评估期(300 d),"300 d 复原力 "成功地显示出随着危害程度的增加而有意义的下降趋势(0.94、0.82 和 0.69)。这些信息对于确定建筑基础设施的脆弱性、评估性能下降造成的影响、协调洪水事件的应对措施以及为后续恢复做准备都非常有价值。本框架扩展了之前的文献研究,提出了一个标准化的评估周期,即 "n-时间复原力",从而提高了复原力指标的可比性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying hazard resilience by modeling infrastructure recovery as a resource-constrained project scheduling problem
Abstract. Reliance on infrastructure by individuals, businesses, and institutions creates additional vulnerabilities to the disruptions posed by natural hazards. In order to assess the impacts of natural hazards on the performance of infrastructure, a framework for quantifying resilience is presented. This framework expands upon prior work in the literature to improve the comparability of the resilience metric by proposing a standardized assessment period. With recovery being a central component of assessing resilience, especially in cases of extreme hazards, we develop a recovery model based upon an application of the resource-constrained project scheduling problem (RCPSP). This recovery model offers the opportunity to assess flood resilience across different events and also, theoretically, between different study areas. The resilience framework and recovery model have been applied in a case study to assess the resilience of building infrastructure to flooding hazards in Alajo, a neighborhood in Accra, Ghana. For the three flood events investigated (5-, 50-, and 500-year return periods) and the chosen standardized assessment period (300 d), the “300 d resilience” successfully shows a meaningful decreasing trend (0.94, 0.82, and 0.69) with increasing hazard magnitude. This information is most valuable for identifying the vulnerabilities of building infrastructure, assessing the impacts resulting in reduced performance, coordinating responses to flooding events, and preparing for the subsequent recovery. This framework expands upon prior work in the literature to improve the comparability of the resilience metric by proposing a standardized assessment period, the “n-time resilience”.
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