Time-Varying Statistics Identification of Nonstationary Random Fluctuating Pressure via Orthogonal Polynomial Representation and Karhunen–Loève Expansion
Publication: Journal of Aerospace Engineering
Volume 36, Issue 6
Abstract
A novel time domain method is proposed to estimate the time-varying statistics of nonstationary random pressure load from structural strain response samples. Orthogonal polynomials and Karhunen–Loève expansion are adopted to represent the spatial distribution of the stochastic pressure load and the random structural strain data, respectively, which transform the random pressure load identification problem to a problem of estimating a few deterministic time-varying coefficients. Numerical simulation on a plate structure subjected to nonstationary random fluctuating load is conducted to validate the proposed method, and the influence of the load’s correlation length on the identification accuracy is also discussed. To show the application perspective of the proposed method, the nonstationary gust-induced random pressure load on a wing structure is reconstructed from structural strain data. Some practical aspects, such as the number of response samples, the level of noise in the strain response, the order of orthogonal polynomial used, and the regularization method used, on the performance of the load identification method are also discussed.
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Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research work is supported by the Jiangsu Natural Science Foundation (BK20180062), the Six Talent Climax Foundation of Jiangsu Province, China (KTHY-005), and the Fundamental Research Funds for Central Universities of China (2242023k30044).
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Published In
Journal of Aerospace Engineering
Volume 36 • Issue 6 • November 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: May 17, 2022
Accepted: Jul 12, 2023
Published online: Sep 8, 2023
Published in print: Nov 1, 2023
Discussion open until: Feb 8, 2024
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