Development of consequence mitigation models for water infrastructure networks against intentional physical attacks
Abstract
As one of critical infrastructure systems, protecting the nation's water infrastructure and improving water network security have become top priorities in the water industry. To date, most vulnerability assessment and mitigation approaches for water infrastructure systems have been subjective and qualitative, with relatively few quantitative methods being developed or proposed. This research develops quantitative and operational strategies to minimize the consequences in the event of physical attacks on water networks. A series of mathematical models are developed in three stages. In the first stage, a theoretical model is formulated. The objective is to identify a feasible water customer demand pattern that minimizes the consequences of water shortage in the downgraded network. The model integrates search techniques such as branch-and-bound and genetic algorithms linked with a hydraulic solver (EPANET2.0) in order to check hydraulic feasibilities across a residual water network. In the second stage, a quantitative and realistic approach to measure the consequences of intentional physical attacks on water networks is presented using three indices (a) degree of disruption of critical infrastructure services, (b) economic loss, and (c) number of people affected. A multi-objective genetic algorithm based model is developed to find Pareto solutions for minimum consequences using these three indicators. In the third stage, the dynamic nature of water demand of different water customers are considered in the consequence assessment by implementing extended period (24 hours) simulation of water network. The consequence minimization model developed in this stage is a water rationing model which attempts to rotate water supply to customers during 24-hour period. The performances of the models developed in this research are evaluated using water networks and the results are discussed. Computational efficiency and solution quality of the optimal solution search techniques utilized in this study are also evaluated. The models developed in this research can be used as a tool for emergency planning and preparation of water utilities in identifying critical facilities in their networks and/or mitigating the consequences of failure in instances of intentional physical attacks. Such an approach can help asset managers plan and allocate the budgets for future capital investments for water infrastructure.
Degree
Ph.D.
Advisors
Abraham, Purdue University.
Subject Area
Civil engineering|Area Planning and Development
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