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Design Sensitivity for a Subsonic Aircraft Predicted by Neural Network and Regression ModelsA preliminary methodology was obtained for the design optimization of a subsonic aircraft by coupling NASA Langley Research Center s Flight Optimization System (FLOPS) with NASA Glenn Research Center s design optimization testbed (COMETBOARDS with regression and neural network analysis approximators). The aircraft modeled can carry 200 passengers at a cruise speed of Mach 0.85 over a range of 2500 n mi and can operate on standard 6000-ft takeoff and landing runways. The design simulation was extended to evaluate the optimal airframe and engine parameters for the subsonic aircraft to operate on nonstandard runways. Regression and neural network approximators were used to examine aircraft operation on runways ranging in length from 4500 to 7500 ft.
Document ID
Document Type
Hopkins, Dale A.
(NASA Glenn Research Center Cleveland, OH, United States)
Patnaik, Surya N.
Date Acquired
September 7, 2013
Publication Date
June 1, 2005
Publication Information
Publication: Research and Technology 2004
Subject Category
Aircraft Design, Testing And Performance
Distribution Limits
Work of the US Gov. Public Use Permitted.
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