Date of Award
3-2023
Document Type
Thesis
Degree Name
Master of Science in Engineering Management
Department
Department of Systems Engineering and Management
First Advisor
Brigham A. Moore, PhD
Abstract
ccurately modeling the interdependent operation of critical infrastructure systems is an effective and efficient way of proactively evaluating system vulnerabilities and resiliency. Infrastructure systems are designed to transport essential commodities from where they are produced to where they are consumed and network flow-based models are one of the most effective ways to simulate and quantify infrastructure performance. The literature is populated with proposed models that must balance accuracy of interdependent operations, capability to include real-world considerations, and computational cost. This research proposes an alternative network-flow based model called the Critical Infrastructure System Resiliency Model (CISRM) that focuses on modeling a subset of operational interdependencies and allows user-input damage scenarios to include partial functionality of components, restrict the available repair resources, and limit the number of work crews available to make repairs. Due to the difficulties associated with obtaining real-world infrastructure data, this research demonstrated CISRM capabilities on a notional test network. The damage scenario simulations demonstrated the superiority of CISRM in quickly restoring infrastructure services when compared to alternative restoration prioritization heuristics. The simulations also show CISRM could be a powerful decision-making tool for weighing the costs and benefits of different levels of recovery investment and the potential impact on overall system resiliency.
AFIT Designator
AFIT-ENV-MS-23-M-191
Recommended Citation
Figge, Spencer R., "Critical Infrastructure System Resiliency Modeling Using Multi-Layer Network Optimization" (2023). Theses and Dissertations. 7035.
https://scholar.afit.edu/etd/7035
Comments
A 12-month embargo was observed.
Approved for public release. Case number on file.