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Article

Study on Nonlinear Correlation in Modal Coefficients of the Bionic Airfoil

School of Energy and Power Engineering, Huazhong University of Science and Technology, Luoyu Road No. 1037, Wuhan 430074, China
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Author to whom correspondence should be addressed.
Machines 2023, 11(1), 88; https://doi.org/10.3390/machines11010088
Submission received: 10 November 2022 / Revised: 31 December 2022 / Accepted: 8 January 2023 / Published: 10 January 2023
(This article belongs to the Special Issue Selected Papers from CITC2022)

Abstract

Applying bionic airfoils is essential in enlightening the design of rotating machinery and flow control. Dynamic mode decomposition was used to reveal the low dimensional flow structure of Riblets, Seagull, and Teal bionic airfoils at low Reynolds numbers 1 × 105 and is compared with NACA4412 airfoils. The attack angle of the two-dimensional airfoil is 19°, and the SST k-ω turbulence model and ANSYS fluent were used to obtain the transient flow field data. The sparse identification of nonlinear dynamics reveals the nonlinear correlation between modal coefficients and establishes manifold dynamics. The results show that the bionic airfoil and NACA4412 airfoil have the same type of nonlinear correlation, and the dimension and form of the minimum reduced-order model are consistent. The modal coefficients always appear in the manifold equation in pairs with a phase difference of 90°. The dimension of the manifold equation is two-dimensional, and the absolute value of the coefficient corresponds to the fundamental frequency of airfoil vortex shedding. The reconstructed flow field based on the manifold equation is highly consistent with the numerical simulation flow field, which reveals the accuracy of the manifold equation. The relevant conclusions of this study emphasize the unity of the nonlinear correlation of bionic airfoils.
Keywords: bionic airfoil; nonlinear correlation; dynamic mode decomposition; reduced-order model; sparse identification of nonlinear dynamics; manifold equation bionic airfoil; nonlinear correlation; dynamic mode decomposition; reduced-order model; sparse identification of nonlinear dynamics; manifold equation

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MDPI and ACS Style

Xiao, Q.; Wang, J.; Jiang, B.; Ding, Y.; Yang, X. Study on Nonlinear Correlation in Modal Coefficients of the Bionic Airfoil. Machines 2023, 11, 88. https://doi.org/10.3390/machines11010088

AMA Style

Xiao Q, Wang J, Jiang B, Ding Y, Yang X. Study on Nonlinear Correlation in Modal Coefficients of the Bionic Airfoil. Machines. 2023; 11(1):88. https://doi.org/10.3390/machines11010088

Chicago/Turabian Style

Xiao, Qianhao, Jun Wang, Boyan Jiang, Yanyan Ding, and Xiaopei Yang. 2023. "Study on Nonlinear Correlation in Modal Coefficients of the Bionic Airfoil" Machines 11, no. 1: 88. https://doi.org/10.3390/machines11010088

APA Style

Xiao, Q., Wang, J., Jiang, B., Ding, Y., & Yang, X. (2023). Study on Nonlinear Correlation in Modal Coefficients of the Bionic Airfoil. Machines, 11(1), 88. https://doi.org/10.3390/machines11010088

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