Integrated optimization on aerodynamics-structure coupling and flight stability of a large airplane in preliminary design

作     者：Xiaozhe WANG Zhiqiang WAN Zhu LIU Chao YANG 

作者机构：School of Aeronautic Science and Engineering Beihang University Key Laboratory of Aircraft Advanced Design Technology Ministry of Industry and Information 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2018年第31卷第6期

页      面：1258-1272页

核心收录：

学科分类：08[工学] 082501[工学-飞行器设计] 0802[工学-机械工程] 0825[工学-航空宇航科学与技术] 0801[工学-力学（可授工学、理学学位）] 

基　　金：supported by the National Key Research and Development Program (No.2016YFB0200703) the Academic Excellence Foundation of Beihang University for Ph.D. Students 

主　　题：Aeroelasticity Integrated optimization Multidisciptinary analysis Large airplane Preliminary design 

摘      要：The preliminary phase is significant during the whole design process of a large airplane because of its enormous potential in enhancing the overall performance. However, classical sequential designs can hardly adapt to modern airplanes, due to their repeated iterations, long periods, and massive computational burdens. Multidisciplinary analysis and optimization demonstrates the capability to tackle such complex design issues. In this paper, an integrated optimization method for the preliminary design of a large airplane is proposed, accounting for aerodynamics, structure, and stability. Aeroelastic responses are computed by a rapid three-dimensional flight load analysis method combining the high-order panel method and the structural elasticity correction. The flow field is determined by the viscous/inviscid iteration method, and the cruise stability is evaluated by the linear small-disturbance theory. Parametric optimization is carried out using genetic algorithm to seek the minimal weight of a simplified plate-beam wing structure in the cruise trim condition subject to aeroelastic, aerodynamic, and stability constraints, and the optimal wing geometry shape, front/rear spar positions, and structural sizes are obtained simultaneously. To reduce the computational burden of the static aeroelasticity analysis in the optimization process, the Kriging method is employed to predict aerodynamic influence coefficient matrices of different aerodynamic shapes. The multidisciplinary analyses guarantee computational accuracy and efficiency, and the integrated optimization considers the coupling effect sufficiently between different disciplines to improve the overall performance, avoiding the limitations of sequential approaches utilized currently.