Multimodal uncertainty propagation analysis for the morphing wings of cross-domain variant aircraft

A multimodal distribution based uncertainty analysis method for cross-domain aircraft morphing wing mechanisms is proposed to address the engineering issue of the reliability of morphing mechanisms. This method is based on Gaussian mixture model, isotropic sparse mesh method combined with maximum en...

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Bibliographic Details
Published in:Meccanica (Milan) 2024-09, Vol.59 (9), p.1555-1576
Main Authors: Yao, Qishui, Liu, Siyuan, Tang, Jiachang, Zhang, Hairui, Qiu, Zitong
Format: Article
Language:English
Subjects:
Aircraft
Aircraft reliability
Automotive Engineering
Civil Engineering
Classical Mechanics
Domains
Engineering
External pressure
Flight altitude
Geographical distribution
Geographical locations
Grid method
Maximum entropy method
Mechanical Engineering
Morphing aircraft
Normal distribution
Probabilistic models
Propagation
Random variables
Uncertainty analysis
Wings (aircraft)
Working conditions
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Summary:A multimodal distribution based uncertainty analysis method for cross-domain aircraft morphing wing mechanisms is proposed to address the engineering issue of the reliability of morphing mechanisms. This method is based on Gaussian mixture model, isotropic sparse mesh method combined with maximum entropy method analysis. In the working environment of the morphing wings, the external load exhibits a multimodal distribution with changes in flight altitude and geographical location. Traditional uncertainty methods are difficult to accurately determine the reliability of aircraft under the influence of multiple variable influencing factors. Therefore, the proposed method is proposed to evaluate the reliability of morphing wing mechanisms. Firstly, a Gaussian mixture model is used to establish the mixture density function of the pressure and the leading edge size of the variant aircraft. Secondly, the integral points and weights of the multimodal random variables are calculated by the sparse grid method. Finally, an adaptive convergence mechanism is used to improve the uncertainty propagation accuracy. After a mathematical example and two engineering examples, it can be considered that the proposed method has a certain reference value in analyzing the uncertainty propagation under the multimodal distribution state of multiple factors.
ISSN:0025-6455
1572-9648
DOI:10.1007/s11012-024-01857-4