Tradespace analysis for multiple performance measures
MacCalman, Alex D.
Sanchez, Susan M.
McDonald, Mary L.
Goerger, Simon R.
Karl, Andrew T.
MetadataShow full item record
To meet the changing demands of operational environments, future Department of Defense solutions require the engineering of resilient systems. Scientists, engineers and analysts rely on modeling, simulation, and tradespace analysis to design future resilient systems. During conceptual system design, high performance computing clusters and models from multiple domains are leveraged to conduct large-scale simulation experiments that generate multi-dimensional data for tradespace exploration. Despite recent breakthroughs in computation capabilities, the world’s most powerful computers cannot effectively explore a high-dimensional tradespace using a brute-force approach. This paper outlines a viable methodology and process to generate large numbers of variant solutions for tradeoff analysis. Design of experiments is used to efficiently explore a high-dimensional tradespace and identify system design drivers. These drivers are used to identify model inputs that help focus tradespace generation in areas that promise viable solutions. A dashboard illustrates how viable variant exploration can be conducted to illuminate trade decisions.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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Gillespie, Stephen E. (Monterey, California: Naval Postgraduate School, 2016-06);This research presents the system of systems (SoS) tradespace definition methodology (SoS-TDM) and SoS architecture feasibility assessment model (SoS-AFAM). Together, these extend current model-based systems engineering ...
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