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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2020, Vol. 41 ›› Issue (5): 623344-623344.doi: 10.7527/S1000-6893.2019.23344

• Specical Topic of Numerical Optimization and Design of Aircraft Aerodynamic Shape • Previous Articles     Next Articles

Recent progress of efficient global aerodynamic shape optimization using surrogate-based approach

HAN Zhonghua, XU Chenzhou, QIAO Jianling, LIU Fei, CHI Jiangbo, MENG Guanyu, ZHANG Keshi, SONG Wenping   

  1. National Key Laboratory of Science and Technology on Aerodynamic Design and Research, Institute of Aerodynamic and Multidisciplinary Design Optimization, School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China
  • Received:2019-08-06 Revised:2019-08-25 Published:2019-10-17
  • Supported by:
    National Natural Science Foundation of China (11772261, 11972305); Foundation of National Key Laboratory of Science and Technology on Aerodynamic Design and Research (61XXX01010020117)

Abstract: Aerodynamic shape optimization based on high-fidelity computational fluid dynamics plays an increasingly important role in improving aerodynamic and overall performance of an aircraft. Surrogate-Based Optimization (SBO), a genetic efficient global optimization, has become a hot topic in this area. During the past two decades, a great progress has been made. Various advanced new surrogate modelling techniques have been proposed, and optimization theory and algorithm are constantly improved. In this article, recent progress of efficient global aerodynamic shape optimization using SBO is reviewed. First, the state of the art of optimizations with variable-fidelity surrogate models, gradient-enhanced models, and a parallel optimization method based on none-bio-inspired evolutionary mechanism are reviewed. Second, in terms of frontier issues, recent progress of multi-objective design optimization, hybrid inverse/optimization design method, robust design optimization, as well as multidisciplinary design optimization are discussed. Literature review shows that SBO has significant superiority in efficiency, robustness, and global search. In addition, it enables efficient aerodynamic shape optimizations with number of design variables up to 100, showing huge potential in engineering applications. Finally, some key issues and challenges relevant to the theory, method, and applications of SBO are presented, and future research directions are suggested.

Key words: aerodynamic shape optimization, multidisciplinary design optimization, surrogate model, surrogate-based optimization, computational fluid dynamics

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