Surrogate models based optimization methods for the design of underwater glider wing

被引:0
|
作者
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China [1 ]
不详 [2 ]
机构
[1] State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences
[2] Graduate School, Chinese Academy of Sciences
来源
Jixie Gongcheng Xuebao | 2009年 / 12卷 / 7-14期
关键词
Design of experiment; Design optimization; Surrogate models; Underwater glider;
D O I
10.3901/JME.2009.12.007
中图分类号
学科分类号
摘要
High precision numerical analysis methods have been extensively used in the conceptual design of complex engineering systems. Combining high precision numerical analysis methods with optimization algorithms to make a systematic exploration of the design space has become an important topic in the modern design method. During the design process of an underwater glider's wing, a surrogate model is introduced to decrease the computation times of high precision analysis. By this means, the contradiction between precision and efficiency is solved effectively. Through integrating the parametric geometry modeling, mesh generation and computational fluid dynamics analysis as an automatic workflow, and adopting the design of experiment (DOE) theory, a surrogate model is constructed to solve the multi-objects design optimization problem of the underwater glider. The procedure of surrogate model construction is presented and several DOE methods are compared systematically, especially the characteristics and applicability of the response surface model and the radial basis functions model. A fast design exploration and optimization is implemented and the optimal plane of the underwater glider is found out based on the surrogate model. Optimization results show that the lift drag ratio improves about 6.76%, and the pitch moment is reduced from 0.2760 N·m to 0.0015 N·m. © 2009 Journal of Mechanical Engineering.
引用
收藏
页码:7 / 14
页数:7
相关论文
共 15 条
  • [1] Giunta A.A., Aircraft multidisciplinary design optimization using design of experiments theory and response surface modeling methods, (1997)
  • [2] Booker A.J., Dennis J.E., Frank P.D., A rigorous framework for optimization of expensive functions by surrogates, Structural Optimization, 17, pp. 1-13, (1999)
  • [3] Simpson T.W., Peplinski J.D., Kochet P.N., Meta-models for computer-based engineering design: Survey and recommendations, Engineering with Computers, 17, pp. 129-150, (2001)
  • [4] Wang X., Xi G., Aerodynamic optimization design for airfoil based on kriging model, Acta Aeronautica et Astronautica Sinica, 26, 5, pp. 545-549, (2005)
  • [5] Zeng H., Yu X., An approach to aerodynamic shape optimization using surrogate models, Aeronautical Computer Technique, 35, 4, pp. 84-87, (2005)
  • [6] Queipo N.V., Haftka R.T., Shyy W., Et al., Surrogate-based analysis and optimization, Progress in Aerospace Sciences, 41, pp. 1-28, (2005)
  • [7] Jeon K.S., Lee J.W., Byun Y.H., Development of repretitive response surface enhancement Technique for the multidisciplinary system optimization, 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, pp. 1-9, (2006)
  • [8] Jouhaud J.C., Sagaut P., Montagnac M., Et al., A surrogate-model based multidisciplinary shape optimization method with application to a 2D subsonic airfoil, Computers & Fluids, 36, pp. 520-529, (2007)
  • [9] Hu K., Yu J., Zhang Q., Design and optimization of underwater glider shape, Robot, 27, 2, pp. 108-112, (2005)
  • [10] Jin R., Chen W., Simpson T.W., Comparative studies of metamodelling techniques under multiple modeling criteria, Journal of Structural Multidisciplinary Optimization, 23, pp. 1-13, (2001)