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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 50880 (09)
- University: Sharif University of Technology
- Department: Civil Engineering
- Advisor(s): Mahsuli, Mojtaba
- Abstract:
- This study proposes a probabilistic framework to quantitatively evaluate the resilience of a community comprising a building stock, commercial facilities, and interdependent infrastructure systems. To this end, the proposed framework employs Monte Carlo sampling in which each sample comprises multiple stages. The sample starts with the occurrence of a hazard event. It then follows by evaluating the consequences incurred by the community in the face of the hazard event. It is concluded by simulating the operations aimed at complete recovery of the community comprising inspection, rescue and relief, restoration, and recovery. For this purpose, chains of interacting probabilistic models are employed to simulate the hazard intensity, structural responses, consequences such as damage and casualties, operations such as inspection, search and rescue, and repair and replacement, and the ensuing social and economic losses, including repair costs, business interruption, costs of treating the injured, and losses arising from the death toll. Each model collects the outputs of its preceding models and provides input to its successive models. To simulate the uncertain sequence of the post-hazard operations, and to account for the behavior and priorities of decision makers and their interaction, a novel implementation of agent-based simulation is proposed. In this context, an agent is a decision maker responsible for a designated set of components and independently decides about the prioritization of these components for various operations given the limited resources. The proposed framework takes into account the interaction between different agents, i.e., modeling how the consequences of one agent’s decisions can influence those of the other agents. In each sample, over the time period that spans from the hazard event until the full recovery of the community, all consequences and operations are translated into cost, which is accumulated over time. The sum of all costs at the end of the recovery period, which marks the end of the sample, is called the total community cost, which represent the total costs incurred by the community against the hazards. At the end of the sampling analysis, the probability distribution of the total community cost is obtained and used to define a single, global measure of the community resilience. This measure incorporates the functionality of all buildings and infrastructure systems as well as different properties of resilience, i.e., robustness, rapidity, resourcefulness, and redundancy. Next, a novel importance measure is proposed that ranks the components in accordance with their influence on the proposed community resilience measure. Moreover, a decision support methodology is proposed to evaluate and compare different policies on enhancing the community resilience based on a benefit-cost analysis using the proposed resilience measure. The developments are implemented as a new module in the Rtx, a computer program for reliability, optimizations, and risk analysis. The proposed framework is showcased by a comprehensive application to a hypothetical community located in Tehran, subject to seismic hazard from three sources. This community is composed of residential and commercial buildings, healthcare facilities, an electric power system, and a potable water system. The proposed community resilience measure is estimated at 51%, and the mean total community costs as $151 million. Next, two policies to enhance the community resilience are evaluated and compared. The first policy is to spend the resources to retrofit a power substation, which, on average, reduces the total community cost by $9.5 million and enhances the community resilience measure by 3%. The second policy is to retrofit a water pumping station, which, on average, reduces the total community cost by $0.5 million and enhances the community resilience measure by 0.16%
- Keywords:
- Agent Based Simulation ; Probability Analysis ; Hazard Analysis ; Consequence Analysis ; Community Resilience ; Interdependent Infrastructure Systems
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