In Set Based Design, discoveries are made by first identifying the sets of solutions that represent feasible regions of the design space. Then, those candidate sets are analyzed to derive insights that enable decision makers to understand the relationships between competing objectives, costs, and the design decisions that drive those outcomes. Set Based Design informs design tradeoffs, requirements definition, and concept selection, but it is particularly valuable for addressing critical capability gaps that demand new cutting-edge technologies. The Navy is continually advancing Combat, Power, and Energy Systems (CPES) that require novel solutions to address increased power demands and electrical loads. In turn, this creates the need for evolved modeling and simulation capabilities to address these new domains. In early-stage design, designers face a common set of challenges and questions. What happens when the tools needed to generate the solutions sets do not yet exist? Or what if the tools exist but do not yet provide the desired level of confidence? What if the only way to get a complete representation of a design is to accept low fidelity estimates of some characteristics alongside higher fidelity estimates of others? And what happens when our ability to make sense of the data is hampered by limited access to state-of-the-art analytic tools (due to security or funding constraints)? This paper addresses these questions and offers practical solutions for conducting a Set Based Design study that is constrained by the limitations of the tool suite available at the time of the study.
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