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Aerodynamic Shape Optimization Using Hybridized Differential EvolutionAn aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.
Document ID
20030007917
Document Type
Preprint (Draft being sent to journal)
Authors
Madavan, Nateri K.
(NASA Ames Research Center Moffett Field, CA United States)
Date Acquired
September 7, 2013
Publication Date
January 1, 2003
Subject Category
Aerodynamics
Meeting Information
Meeting: AIAA 21st Applied Aerodynamics Conference
Location: Orlando, FL
Country: United States
Start Date: June 23, 2003
End Date: June 26, 2003
Sponsors: American Inst. of Aeronautics and Astronautics
Funding Number(s)
PROJECT: RTOP 512-40-12
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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