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Turbopump Performance Improved by Evolutionary AlgorithmsThe development of design optimization technology for turbomachinery has been initiated using the multiobjective evolutionary algorithm under NASA's Intelligent Synthesis Environment and Revolutionary Aeropropulsion Concepts programs. As an alternative to the traditional gradient-based methods, evolutionary algorithms (EA's) are emergent design-optimization algorithms modeled after the mechanisms found in natural evolution. EA's search from multiple points, instead of moving from a single point. In addition, they require no derivatives or gradients of the objective function, leading to robustness and simplicity in coupling any evaluation codes. Parallel efficiency also becomes very high by using a simple master-slave concept for function evaluations, since such evaluations often consume the most CPU time, such as computational fluid dynamics. Application of EA's to multiobjective design problems is also straightforward because EA's maintain a population of design candidates in parallel. Because of these advantages, EA's are a unique and attractive approach to real-world design optimization problems.
Document ID
20050203879
Acquisition Source
Glenn Research Center
Document Type
Other
Authors
Oyama, Akira
Liou, Meng-Sing (NASA Glenn Research Center Cleveland, OH, United States)
Date Acquired
September 8, 2013
Publication Date
March 1, 2002
Publication Information
Publication: Research and Technology 2001
Subject Category
Aircraft Propulsion And Power
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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