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High-Lift Optimization Design Using Neural Networks on a Multi-Element AirfoilThe high-lift performance of a multi-element airfoil was optimized by using neural-net predictions that were trained using a computational data set. The numerical data was generated using a two-dimensional, incompressible, Navier-Stokes algorithm with the Spalart-Allmaras turbulence model. Because it is difficult to predict maximum lift for high-lift systems, an empirically-based maximum lift criteria was used in this study to determine both the maximum lift and the angle at which it occurs. Multiple input, single output networks were trained using the NASA Ames variation of the Levenberg-Marquardt algorithm for each of the aerodynamic coefficients (lift, drag, and moment). The artificial neural networks were integrated with a gradient-based optimizer. Using independent numerical simulations and experimental data for this high-lift configuration, it was shown that this design process successfully optimized flap deflection, gap, overlap, and angle of attack to maximize lift. Once the neural networks were trained and integrated with the optimizer, minimal additional computer resources were required to perform optimization runs with different initial conditions and parameters. Applying the neural networks within the high-lift rigging optimization process reduced the amount of computational time and resources by 83% compared with traditional gradient-based optimization procedures for multiple optimization runs.
Document ID
20020060751
Acquisition Source
Ames Research Center
Document Type
Preprint (Draft being sent to journal)
Authors
Greenman, Roxana M.
(NASA Ames Research Center Moffett Field, CA United States)
Roth, Karlin R.
(NASA Ames Research Center Moffett Field, CA United States)
Smith, Charles A.
Date Acquired
September 7, 2013
Publication Date
January 1, 1998
Subject Category
Aircraft Design, Testing And Performance
Report/Patent Number
DETC98/CIE-6006
Meeting Information
Meeting: Proceedings of DETC98: ASME 1998 Computers in Engineering Conference
Location: Atlanta, GA
Country: United States
Start Date: September 13, 1998
End Date: September 16, 1998
Funding Number(s)
PROJECT: RTOP 519-10-42
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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