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Resilience assessment for interdependent urban infrastructure systems using dynamic network flow models

机译：使用动态网络流模型的相互依赖的城市基础设施系统的弹性评估

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摘要

Critical infrastructure systems are becoming increasingly interdependent, which can exacerbate the impacts of disruptive events through cascading failures, hindered asset repairs and network congestion. Current resilience assessment methods fall short of fully capturing such interdependency effects as they tend to model asset reliability and network flows separately and often rely on static flow assignment methods. In this paper, we develop an integrated, dynamic modelling and simulation framework that combines network and asset representations of infrastructure systems and models the optimal response to disruptions using a rolling planning horizon. The framework considers dependencies pertaining to failure propagation, system-of-systems architecture and resources required for operating and repairing assets. Stochastic asset failure is captured by a scenario tree generation algorithm whereas the redistribution of network flows and the optimal deployment of repair resources are modelled using a minimum cost flow approach. A case study on London's metro and electric power networks shows how the proposed methodology can be used to assess the resilience of city-scale infrastructure systems to a local flooding incident and estimate the value of the resilience loss triangle for different levels of hazard exposure and repair capabilities.
机译：关键基础架构系统变得越来越相互依存，通过级联故障，阻碍资产修复和网络拥塞，可能加剧破坏性事件的影响。当前的弹性评估方法无法完全捕获这种相互依赖性的影响，因为它们倾向于分别对资产可靠性和网络流量建模，并且通常依赖于静态流量分配方法。在本文中，我们开发了一个集成的动态建模和仿真框架，该框架结合了基础设施系统的网络和资产表示形式，并使用滚动计划范围来建模对中断的最佳响应。该框架考虑了与故障传播，系统的体系结构以及操作和维修资产所需的资源有关的依赖性。随机资产故障由方案树生成算法捕获，而网络流的重新分配和维修资源的最佳部署则使用最小成本流方法进行建模。伦敦地铁和电力网络的案例研究表明，如何使用拟议的方法来评估城市规模的基础设施系统对当地洪灾的适应能力，并估算不同风险暴露水平和修复水平下的抗灾损失三角形的价值能力。

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