Physical Essence of Stall Phenomena and its WNN-Based Aerodynamic Modeling from Flight Data

Xu Sheng Gan; Xue Qin Tang; Hai Long Gao

doi:10.4028/www.scientific.net/AMM.602-605.3140

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Physical Essence of Stall Phenomena and its...

Physical Essence of Stall Phenomena and its WNN-Based Aerodynamic Modeling from Flight Data

Abstract:

To understand the characteristics of aircraft stall for better aerodynamic model, the physical essence of the stall phenomena of aircraft is first introduced, and then a Wavelet Neural Network (WNN) is proposed to set up the stall aerodynamic model. Numerical examples indicates that through the deep cognition of the stall phenomena of aircraft the proposed stall aerodynamic method has a better accuracy than the traditional neural network and is also effective and feasible.

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Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

3140-3143

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.3140

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Online since:

August 2014

Authors:

Xu Sheng Gan*, Xue Qin Tang, Hai Long Gao

Keywords:

Aerodynamics Modeling, Flight Data, Stall Phenomena, Wavelet Neural Network

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* - Corresponding Author

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