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Evolutionary computing for the design search and optimization of space vehicle power subsystemsEvolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.
Document ID
20060043821
Acquisition Source
Jet Propulsion Laboratory
Document Type
Conference Paper
External Source(s)
Authors
Kordon, Mark
Klimeck, Gerhard
Hanks, David
Hua, Hook
Date Acquired
August 23, 2013
Publication Date
March 6, 2004
Meeting Information
Meeting: IEEE Aerospace Conference
Location: Big Sky, MT
Country: United States
Start Date: March 6, 2004
End Date: March 13, 2004
Distribution Limits
Public
Copyright
Other
Keywords
power
genetic algorithms
evolutionary computing
optimization

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