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oai:mountainscholar.org:10217/2392672025-12-30T03:15:18Zcom_10217_100532com_10217_100000com_10217_199888com_10217_100303col_10217_182111col_10217_199889

Younes, Megan Elizabeth, author Cale, James, advisor Gallegos, Erika, committee member Simske, Steve, committee member Gaofeng, Jia, committee member 2024-09-09T20:52:11Z 2024-09-09T20:52:11Z 2024 Younes_colostate_0053A_18505.pdf https://hdl.handle.net/10217/239267 https://doi.org/10.25675/3.02340 Increasing high probability low frequency events such as extreme weather incidents in combination with aging infrastructure in the United States puts the nation's critical infrastructure such as hydroelectric dams' survivability at risk. Maximizing resiliency in complex systems can be viewed as a multi-objective optimization that includes system performance, survivability, economic and social factors. Systems requiring high survivability: a hydroelectric dam, typically require one or more redundant (standby) subsystems, which increases system cost. To optimize the tradeoffs between system survivability and cost, this research introduces an approach for obtaining the Pareto-optimal set of design candidates ("resilience frontier"). The method combines Monte Carlo (MC) sampling to estimate total survivability and a genetic algorithm (GA), referred to as the MCGA, to obtain the resilience frontier. The MCGA is applied to a hydroelectric dam to maximize overall system survivability. The MCGA is demonstrated through several numerical case studies. The results of the case studies indicate that the MCGA approach shows promise as a tool for evaluating survivability versus cost tradeoffs and also as a potential design tool for choosing system configuration and components to maximize overall system resiliency. born digital doctoral dissertations English eng Colorado State University. Libraries 2020- Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. hydroelectric dam complex systems survivability Framework for optimizing survivability in complex systems Text Doctor of Philosophy (Ph.D.) Doctoral Systems Engineering Colorado State University This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). open.access