<p>This praxis develops a simulation-based approach to analyzing the overall reliability of complex systems with high degrees of redundancy, time varying event rates, and the potential for common cause failures. This approach is compared to traditional analytic approaches, and is shown to have some advantages, primarily by avoiding some of the simplifying assumptions used in those approaches. </p><p> Several canonical problems are solved using both traditional and simulation-based approaches to elucidate the method, and the method is then applied to more complex problems for which exact analytic solutions are not available. The method is shown to be flexible to both traditional industrial plant reliability problems and to a new class of problems involving the reliability of swarming unmanned vehicles, where there is a high degree of parallelism and dynamic formation of common cause groups. </p><p> The penultimate chapter examines the impact of common cause failures on the reliability of a swarm of unmanned vehicles performing a search mission, and develops a simulation-based approach to modeling the reliability of swarms in the presence of both independent (single vehicle) and common cause (multiple vehicle) failures. The modeling approach is exercised on a sample problem to illustrate how it can be used as part of a system design or search-planning tool for swarming unmanned vehicles. The simulation provides insight on the impact of design decisions that influence overall system reliability; it also provides metrics of success in a search scenario as a function of user-selectable parameters. </p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10243602 |
| Date | 10 January 2017 |
| Creators | Littlefield, Scott |
| Publisher | The George Washington University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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