An advanced rigid-flexible hybrid assembly deviation analysis method for aerostructures

Abstract

Aerostructures are important components of an aircraft's aerodynamic shape, and their assembly requires high precision. To ensure optimal external shape performance, a significant number of assembly deviation calculations must be performed during the design process of an aerostructure. However, accurately describing shape deviation necessitates high-fidelity surface deformation data. Therefore, an assembly deviation analysis method that balances rapid response and accurate calculation under conditions of large data volume and high cost plays a vital role in promoting the external performance of aerostructures. While some progress has been made in this field, the existing methods are still unable to fill this research gap completely. This paper proposes an advanced rigid-flexible hybrid assembly deviation analysis (RFHA) method for aerostructural shape deviation. It decomposes assembly deviation into rigid deviation transmission and flexible deformation, unifying them in one framework. This method predicts the flexible deformation of aerostructures using discrete cosine transform (DCT) and surrogate model (SM). It also develops a rigid-flexible hybrid assembly deviation analysis method in combination with the Jacobian-Torsor model (J-T). To further reduce computational resources and improve the performance of the surrogate model, the mega-trend diffusion (MTD) is utilized to generate virtual samples to expand the sample set. Relevant parameters of the proposed method are determined using experimental methods. The proposed method is validated and compared with an existing RFHA and a commercial software package. The results show that the proposed method can guarantee prediction performance under small sample conditions and reduce computational burden, while maintaining a certain advantage in rapid response and accurate calculation.