为意外准备基础设施:融合合成网络、相互依赖和级联故障模型

Ryan M Hoff, M. Chester
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引用次数: 1

摘要

面对人类世不稳定的条件,基础设施弹性建模仍然面临挑战,以应对日益复杂的条件,从而快速而有意义地推进适应。数据差距、日益相互关联的系统以及准确的行为估计(跨规模以及渐进和级联故障)仍然是基础设施建模者面临的挑战。然而,新的方法正在出现——大部分是独立的——如果把它们结合起来,就会为我们迅速提高对脆弱性的理解和对恢复力的外科手术式投资提供重要的机会。特别有希望的是相互依赖建模、级联故障建模和合成网络生成。我们描述了一个框架,用于将这三个领域集成到一个集成的建模框架中,以评估没有数据存在的基础设施网络,连接基础设施以建立相互依赖关系,评估这些相互连接的基础设施对危险的脆弱性,并模拟故障如何跨系统传播。我们从文献中提取作为证据基础,提供实施的概念结构,并通过讨论这种框架的重要性以及它可能为基础设施研究人员和管理人员提供的关键工具来结束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Preparing infrastructure for surprise: fusing synthetic network, interdependency, and cascading failure models
Faced with destabilizing conditions in the Anthropocene, infrastructure resilience modeling remains challenged to confront increasingly complex conditions toward quickly and meaningfully advancing adaptation. Data gaps, increasingly interconnected systems, and accurate behavior estimation (across scales and as both gradual and cascading failure) remain challenges for infrastructure modelers. Yet novel approaches are emerging—largely independently—that, if brought together, offer significant opportunities for rapidly advancing how we understand vulnerabilities and surgically invest in resilience. Of particular promise are interdependency modeling, cascading failure modeling, and synthetic network generation. We describe a framework for integrating these three domains toward an integrated modeling framework to estimate infrastructure networks where no data exist, connect infrastructure to establish interdependencies, assess the vulnerabilities of these interconnected infrastructure to hazards, and simulate how failures may propagate across systems. We draw from the literature as an evidence base, provide a conceptual structure for implementation, and conclude by discussing the significance of such a framework and the critical tools it may provide to infrastructure researchers and managers.
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