评估易受灾社区基础设施组成部分重要性的系统方法

IF 4.2 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY International journal of disaster risk reduction Pub Date : 2024-10-15 DOI:10.1016/j.ijdrr.2024.104880
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引用次数: 0

摘要

由于资源有限,投资于有形基础设施的灾前减灾干预措施(如结构改造和加固)可能成本高昂。为了确定投资的优先次序,基础设施的各个组成部分要根据其在整个系统中的重要性进行排序。要想在实际部署中行之有效,这种方法必须考虑到各组成部分之间复杂的相互作用,因为由于灾害足迹的影响,故障可能会在大片地理区域同时发生。因此,特定灾害的不确定性和空间相关性可能会导致独特的故障模式。在本研究中,我们提出了一种利用蒙特卡罗模拟的新型数据驱动框架,该框架利用单个变现来捕捉和模拟特定灾害情景下的实际组件损坏模式。该框架超越了通常将部件故障视为独立事件的传统方法,填补了文献空白。通过捕捉桥梁之间的相互依存关系(主要是通过故障相互作用)和全系统影响,我们的方法提供了更全面的临界度评估。模拟数据为该框架奠定了基础,该框架适用于各种基础设施网络和性能指标。为了证明该方法的有效性,我们分析了田纳西州谢尔比县受地震事件影响的简化交通网络。所提出的框架为构件排序提供了一种有效的方法,适用于人类直觉和简单方法不足的决策。其广泛的适用性表明,它具有解决大规模和相互依存的网络问题的潜力。
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A systemic approach for assessing infrastructure component importance in hazard-prone communities
Investing in pre-event disaster mitigation interventions for physical infrastructure, such as structural retrofits and enhancements, can be costly due to limited resources. To prioritize investments, infrastructure components are ranked by their criticality within the overall system. To be effective in real-world deployment, this approach must account for the complex interactions between components, as failures can occur simultaneously across large geographical areas due to the hazard footprint. As a result, hazard-specific uncertainties and spatial correlations may lead to distinctive failure patterns. In this study, we propose a novel data-driven framework leveraging Monte Carlo simulation, that harnesses the individual realizations to capture and model realistic component damage patterns under a specified hazard scenario. This framework addresses a gap in literature by moving beyond traditional methods that often treat component failures as independent events. By capturing the interdependence between bridges, primarily through failure interactions, and system-wide effects, our method provides a more comprehensive criticality assessment. The simulation data provides a foundation for the framework, which applies to a wide variety of infrastructure networks and performance metrics. To demonstrate the method's effectiveness, a simplified transportation network from Shelby County, TN subjected to an earthquake event is analyzed. The proposed framework provides an effective approach for component ranking, suitable for decision-making where human intuition and simple methods are insufficient. Its broad applicability suggests a potential for large-scale and interdependent network problems.
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来源期刊
International journal of disaster risk reduction
International journal of disaster risk reduction GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
8.70
自引率
18.00%
发文量
688
审稿时长
79 days
期刊介绍: The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international. Key topics:- -multifaceted disaster and cascading disasters -the development of disaster risk reduction strategies and techniques -discussion and development of effective warning and educational systems for risk management at all levels -disasters associated with climate change -vulnerability analysis and vulnerability trends -emerging risks -resilience against disasters. The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.
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