A Computational Framework for Optimization-Based Interdependent Infrastructure Analysis and Vulnerability

Abstract

Civilian communities and military installations operate numerous critical infrastructure systems to deliver services like power, water, mobility, and communications to people and missions. The vulnerability of these systems can be measured by considering the robustness of each infrastructure network on its own or by considering the interdependencies between different networks. Diverse infrastructure network modelsare available to analyze system vulnerability, yet a standard architecture for linking pre-existing models for interdependent analysis does not exist. We develop a computational framework to generate combined models that link multiple network-flow optimization models together for interdependent analysis. We validate our methods and implementation in the Python programming language with well-studied interdependent energy networks. We further demonstrate the versatility of our methods by developing a new assessment of fictitious energy and transportation networks with models not originally created with interdependencies. Overall, this work develops a standard way to conduct interdependent infrastructure analysis with pre-built models and sets a foundation for future analysis of other interdependencies and systems.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2020
Accession Number
AD1126971

Entities

People

  • Matthias P Kuc

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Air Force
  • Application Software
  • Climate Change
  • Communication Systems
  • Computer Programming
  • Computer Programs
  • Department Of Defense
  • Drinking Water
  • Electrical Grids
  • Environmental Protection
  • Failure Mode And Effect Analysis
  • Flow Network
  • Geography
  • Mathematical Programming
  • Military Science
  • National Security
  • Nato
  • Operations Research
  • Optimization
  • Physical Properties
  • Programming Languages
  • United States
  • United States Government

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Neural Network Machine Learning.
  • Software Engineering.