A typical integrated design method for aerodynamic shape optimization of large civil aircraft

被引：0
|
作者：
Huang J. [1 ]
Gao Z. [2 ]
Yu J. [1 ]
Zheng C. [1 ]
Zhou Z. [1 ]
机构：
[1] Computational Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang
[2] School of Aeronautics, Northwestern Polytechnical University, Xi'an
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2019年 / 40卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Correlation analysis; Discrete adjoint optimization; Multi-objective optimization; Non-dominated solution optimization; Virtual Pareto solution set;
D O I：
10.7527/S1000-6893.2019.22369
中图分类号：
学科分类号：
摘要：
To study multi-objective optimization in the high-dimensional target space, a multi-objective integrated design for the aerodynamic shape of large civilian aircraft is carried out by using the AMDEsign, a self-developed software for large-scale parallelization and distributed optimization of aircraft aerodynamic shape. The multi-objective optimization of the digitized model of a wide-body aircraft is performed by two typical modules of AMDEsign: Principal Componet Analysi (PCA) and the discrete adjoint method. The discrete adjoint method is combined with the virtual pareto solution set method to provide an effective directional choice for the weight coefficient. The design results show that the principal component analysis can effectively identify the correlation of the objective function, and the virtual feasible solution set method has high efficiency. The design also fully utilizes the advantages of high efficiency of discrete adjoint and the prediction capabilities of the guided weight function. The multi-point optimized configuration demonstrate significant improvements in cruise lift-drag ratio, drag convergence characteristics, and resistance divergence. The integrated design method proposed is shown to be simple, efficient and applicable in practice. © 2019, Press of Chinese Journal of Aeronautics. All right reserved.
引用
收藏
相关论文
共 21 条
  • [1] Fang X.M., Zhang Y.F., Chen H.X., Transonic nacelle aerodynamic optimization based on hybrid genetic algorithm: AIAA-2016-3833, (2016)
  • [2] Han Z.H., Zhang K.S., Liu J., Et al., Surrogate-based aerodynamic shape optimization with application to wind turbine airfoils: AIAA-2013-1108, (2013)
  • [3] Zhang K.S., Han Z.H., Li W.J., Et al., Coupled aerodynamic and structural optimization of a subsonic-transport wing using surrogate model: AIAA-2008-897, (2008)
  • [4] Huang J.T., Gao Z.H., Zhao K., Et al., Robust design of supercritical wing aerodynamic optimization considering fuselage interfering, Chinese Journal of Aeronautics, 23, 5, pp. 523-528, (2010)
  • [5] Zhang Y., Han Z.H., Shi L.X., Et al., Multi-round surrogate-based optimization for benchmark aerodynamic design problems: AIAA-2016-1545, (2016)
  • [6] Li J.Z., Gao Z.H., The application of multi-objective evolutionary algorithm and surrogate model to aerodynamic robust optimization design, Acta Aerodynamica Sinica, 30, 1, pp. 47-51, (2012)
  • [7] Wang C., Gao Z.H., Refined aerodynamic design optimization of a wing with small aspect ratio, Scientia Sinica Technologica, 45, 6, pp. 643-653, (2015)
  • [8] Jameson A., Aerodynamic design via control theory, Journal of Scientific Computing, 3, pp. 233-260, (1988)
  • [9] Carpentieri G., An adjoint-based shape-optimization method for aerodynamic design, (2009)
  • [10] Dwight R.P., Brezillon J., Effect of various approximations of the discrete adjoint on gradient-based optimization: AIAA-2006-0690, (2006)
123