CRISP Type 1/Collaborative Research: Financial and Physical Infrastructure: A Computational Approach for Integrated Network Resilience Analysis Under Extreme Events

CRISP 类型 1/协作研究：金融和物理基础设施：极端事件下综合网络弹性分析的计算方法

• 批准号: 1638230
• 负责人: Andreea Minca
• 金额: $ 14.96万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-11-01 至 2018-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638230&HistoricalAwards=false
• 关键词: CRISP; Type; Collaborative; Research; Financial

The effects of extreme events on society are not only a function of the immediate damage induced on the physical infrastructure system, but also of the post-event recovery process that a community is able to implement. This recovery process depends on the availability of investments from the financial sector (e.g. by private banks, insurance, and re-insurance companies). Appropriate relationships between these financial and physical infrastructures are therefore necessary to provide the financial pre-conditions for rapid and efficient restoration of the physical system. On the other hand, these extreme events also represent stressors for the financial network, and can cause collapses if the relationships between financial and physical infrastructures are not established in a sustainable, resilient manner. This project aims at developing a deeper understanding of the relationships coupling the financial and physical infrastructures and their effect on the resilience of these interconnected systems. This improved understanding will ultimately lead to support for policy makers and for financial and physical infrastructure managers in order to improve preparedness for and responsiveness to extreme events.The aims of this project will be accomplished through the integration of existing research in the fields of physical infrastructure risk assessment and financial network modeling with computational techniques for the analysis of large interconnected systems. Models and methods for engineering reliability analysis of systems subjected to extreme events, Markov chain models for system evolution and recovery following major disruption, and network models of transportation and supply infrastructures will be used for describing the physical infrastructures. Financial infrastructures and the contractual relationships among these institutions and between physical and financial sectors will be modeled using financial network analysis techniques, incorporating recent results in distress propagation and progressive financial collapse. Combining these into a common heterogeneous network model for interconnected physical and financial infrastructures, resilience analysis will be conducted under a suite of potential hazard scenarios. Because of the computational challenges associated will modeling the responses of large systems of physical and financial assets during the hazard recovery process, surrogate models for network diffusion analysis, analyzed using graph-theoretical approaches, will be developed and calibrated, allowing for efficient analysis of large-scale systems. Finally, making use of the above resilience analysis, the graphical structure of the physical-financial network, representing the contractual relationships between these entities, will be optimized in order to maximize the resilience of the resulting system under the extreme hazard event. The results of this network optimization will be useful to policy makers in determining which contractual structures and policies best support and improve the resilience of the interconnected system. Overall, this project will result in a better understanding of the interactions of hazard, vulnerability, and financing in the post-event recovery of communities exposed to extreme events from an interdisciplinary perspective combining engineering, finance, and network theory. Computationally, the framework will allow for analysis of large systems, including random (or uncertain) heterogeneous network structures.

极端事件对社会的影响不仅是物理基础设施系统造成的直接损害的函数，而且是社区能够实施的事后恢复过程的函数。这种恢复过程取决于金融部门（例如私人银行，保险和再保险公司）的投资可用性。因此，这些财务基础设施和物理基础设施之间的适当关系对于提供财务预先条件以快速有效地恢复物理系统是必要的。另一方面，这些极端事件也代表了金融网络的压力源，如果未以可持续的弹性方式建立金融和物理基础设施之间的关系，可能会导致崩溃。该项目旨在更深入地了解将财务和物理基础设施结合的关系及其对这些相互联系系统的弹性的影响。这种改善的理解最终将为政策制定者以及财务和物理基础设施经理提供支持，以提高对极端事件的准备和响应能力。该项目的目的将通过将现有研究的整合到物理​​基础设施风险评估和财务网络模型中，以与大型互连系统分析的计算技术来实现。对发生极端事件的系统，马尔可夫链模型的系统演变和恢复后的模型和方法分析，以及运输和供应基础架构的网络模型将用于描述物理基础架构。这些机构之间以及物理和金融部门之间的金融基础设施以及合同关系将使用金融网络分析技术进行建模，并将最新成果纳入遇险传播和渐进的金融崩溃中。将它们结合成一个常见的异质网络模型，用于互连的物理和金融基础设施，将在一系列潜在的危险情况下进行弹性分析。由于相关的计算挑战将在危险恢复过程中建模大型物理和金融资产系统的响应，因此将开发和校准使用图理论方法进行分析的网络扩散分析的替代模型，从而有效地分析大型系统。最后，利用上述弹性分析，将优化代表这些实体之间合同关系的物理金融网络的图形结构，以最大程度地提高极端危害事件下产生系统的弹性。该网络优化的结果将对决策者确定哪些合同结构和政策最能提供最佳支持并提高互连系统的弹性。总体而言，该项目将从跨学科的角度结合工程，财务和网络理论的危险，脆弱性和融资的相互作用，从而更好地了解危害，脆弱性和融资的相互作用。在计算上，该框架将允许分析大型系统，包括随机（或不确定的）异质网络结构。