Keyu Li, Chao Yang, Xiaozhe Wang, Zhiqiang Wan, Liang Ma, Chang Li

DOI Number: N/A

Conference number: IFASD-2024-064

During the design stage of commercial aircraft, aeroelastic tailoring can efficiently improve the wing’s aeroelastic properties. However, the high-precision aerodynamic analysis
method used in static aeroelastic analysis is time-consuming and not suitable for tailoring design. This paper proposes an aeroelastic optimization method that considers high-precision aerodynamics. The wing torsion angle and deflection are used to realize a high-precision aeroelastic prediction through the Kriging surrogate model. Additionally, a genetic algorithm is employed to optimize the wing skin and web layup thickness variables while considering stiffness, strength, aerodynamic, and aileron efficiency constraints. The objective is to minimize the structural mass of the wing. The results indicate that the surrogate model error is 0.32%, which realizes the efficient prediction of aerodynamic. Furthermore, the final wing configuration achieves a 20 kg reduction in mass compared to the initial configuration while satisfying the constraints.

Read the full paper here

Email
Print
LinkedIn
The paper above was part of  proceedings of a CEAS event and as such the author has signed a publication agreement to have their paper published in the repository. In the case this paper is found somewhere else CEAS always links to the other source.  CEAS takes great care in making the correct content available to the reader. If any mistakes are found  in the listings please contact us directly at papers@aerospacerepository.org and we will correct the listing promptly.  CEAS cannot be held liable either for mistakes in editorial or technical aspects, nor for omissions, nor for the correctness of the content. In particular, CEAS does not guarantee completeness or correctness of information contained in external websites which can be accessed via links from CEAS’s websites. Despite accurate research on the content of such linked external websites, CEAS cannot be held liable for their content. Only the content providers of such external sites are liable for their content. Should you notice any mistake in technical or editorial aspects of the CEAS site, please do not hesitate to inform us.