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A systems approach to risk reduction of transportation infrastructure networks subject to multiple hazards : final report, December 31, 2008.
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    Final report; Jan. 1, 2008-Dec. 31, 2008.
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  • Abstract:
    Integrity, robustness, reliability, and resiliency of infrastructure networks are vital to the economy, security and well-being of any country. Faced with threats caused by natural and man-made hazards, transportation infrastructure network management must be directed towards: (1) understanding the network performance as a system; (2) modeling the dynamic interaction between the network and the external and internal demands; and (3) defining hazard management strategies to optimize resource allocation. The objective of the project is to develop a model of infrastructure transportation network that can be used to design efficient risk management strategies to ensure an acceptable performance (e.g., in terms of expected damage or recovery times) when subject to the action of individual, simultaneous, or sequential hazards. This study explores the performance of infrastructure networks using a systems approach. This approach is different from most existing modeling techniques in that networks will not be modeled as a collection of separate elements, but rather as a dynamic structured functional unit. This project develops new analytical methods built on a hierarchical structure of the system, which directs the analysis to the interaction and dependencies between components. This are used to characterize and model the emergent properties of the entire system. The performance of the network is integrated with the analysis of individual network components. Time-dependent models will be used for studying the life-cycle performance (mechanical and operational) of network components (e.g., bridges) and to maximize the objective performance function (e.g., cost or efficiency of the response) for different time windows. The case of the transportation network of Texas is used as an illustrative example of some parts of the model.
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