Building complex physics-based systems in a timely cost-effective manner, that perform well, meet diverse user needs, and have no bad emergent behaviors is a challenge. To meet these requirements the solution is to model the physics-based system before building it. Modeling and Simulation capabilities for these type systems have advanced continuously during the past 20 years thanks to progress in the application of high fidelity computational codes that are able to model the real physical performance of system components. The problem is that it is often too time consuming and costly to model complex systems, end-to-end, using these high fidelity computational models alone. Missing are good approaches to segment the modeling of complex systems performance and behaviors, keep the model chain coherent and only model what is necessary. Current research efforts have shown that using multi-fidelity and/or surrogate models might offer alternative methods of performing the modeling and simulations needed to design and develop physics-based systems more efficiently. This study demonstrates that it is possible reduce the number of high fidelity runs allowing the use of classical systems engineering analysis and tools that would not be possible if only high fidelity codes were employed. This study advances the systems engineering of physics-based systems by reducing the number of time consuming high fidelity models and simulations that must be used to design and develop the systems. The study produced a novel approach to the design and development of complex physics-based systems by using a mix of variable fidelity physics-based models and surrogate models. It shows that this combination of increasing fidelity models enables the computationally and cost efficient modeling and simulation of these complex systems and their components. The study presents an example of the methodology for the analysis and design of two physics-based systems: a Ground Penetrating Radar (GPR) and a Nuclear Electromagnetic Pulse Bounded Wave System.
|Advisor:||Eveleigh, Timothy, Sarkani, Shahryar|
|Commitee:||Eveleigh, Timothy, Mazzuchi, Thomas, Murphree, E. Lile, Sarkani, Shahram, Sarkani, Shahryar|
|School:||The George Washington University|
|Department:||Engineering Mgt and Systems Engineering|
|School Location:||United States -- District of Columbia|
|Source:||DAI-B 76/08(E), Dissertation Abstracts International|
|Subjects:||Management, Engineering, Systems science|
|Keywords:||Fdtd, Kriging, Models, Multi-fidelity, Surrogate models, Systems engineering|
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