An Intelligent Algorithm for Aerodynamic Parameters Calibration of Wind Tunnel Experiment at a High Angle of Attack
In this paper, an intelligent algorithm for the aerodynamic parameter calibration of wind tunnel experiments of advanced layout aircraft at a high angle of attack is proposed. The proposed algorithm is based on a homologous comparison and tuning algorithm, and it can effectively improve the accuracy...
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Veröffentlicht in: | International Journal of Aerospace Engineering 2023-01, Vol.2023, p.1-15 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In this paper, an intelligent algorithm for the aerodynamic parameter calibration of wind tunnel experiments of advanced layout aircraft at a high angle of attack is proposed. The proposed algorithm is based on a homologous comparison and tuning algorithm, and it can effectively improve the accuracy of the wind tunnel experiment model. First, based on the analysis of large oscillation wind tunnel experimental data of an advanced layout scaled aircraft, the high angle of attack wind tunnel experimental model composed of static derivative, dynamic derivative, and rotating balance derivative is established. Second, to improve the accuracy of the wind tunnel experimental model effectively, the idea of combing layered calibration and intelligent algorithm for high angle of attack homologous comparison correction is proposed. The proposed method solves the problems of complex structure, a large amount of data, and poor accuracy in homologous comparison of high angle of attack aerodynamic models of advanced layout aircraft. Finally, the homologous comparison interface software is designed based on MATLAB GUI, which integrates the proposed methods and ideas and realizes effective adjustment of aerodynamic parameters of high angle of attack simulation flight wind tunnel test of an advanced layout aircraft. This study provides a reliable engineering and technical means for subsequent high angle of attack flight test verification of the advanced layout aircraft. |
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ISSN: | 1687-5966 1687-5974 |
DOI: | 10.1155/2023/3093526 |