流固耦合在涡轮多学科优化设计中的应用
收稿日期: 2013-02-07
修回日期: 2013-06-13
网络出版日期: 2013-07-12
Application of Fluid-solid Coupling on Multidisciplinary Optimization Design for Turbine Blades
Received date: 2013-02-07
Revised date: 2013-06-13
Online published: 2013-07-12
针对以往的多学科优化设计(MDO)中未能考虑高精度的耦合分析,开展了涉及耦合分析的多学科优化方法研究。以涡轮叶片为研究对象,兼顾优化效率和精度,提出了涉及耦合的涡轮叶片多学科优化策略。该策略以协同优化(CO)策略作为框架,将可变复杂度建模方法(VCM)和3种精度(高、中、低)模型嵌入其中。其中,通过两点式标度函数和周期更新方法提高可变复杂度建模方法管理3种精度模型的能力。3种精度模型包括涡轮叶片的流固耦合分析、单学科分析和响应面近似方程。最终解决了涡轮叶片多学科优化设计精度和效率的难题,得到可行的最优化结果。
贾志刚 , 王荣桥 , 胡殿印 . 流固耦合在涡轮多学科优化设计中的应用[J]. 航空学报, 2013 , 34(12) : 2777 -2784 . DOI: 10.7527/S1000-6893.2013.0303
This paper is a study on the multidisciplinary design optimization (MDO) involving coupling, because the MDO in the past failed to consider the coupling analysis of high precision. Taking both optimization efficiency and precision into consideration, this paper constructs a turbine blade optimization strategy with coupling based on collaborative optimization (CO). This strategy incorporates the variable complexity method (VCM) which is improved by the two-point scale function and the periodic updating technology and three accuracy classes (high, middle, low) of the analysis models, i. e. the fluid-solid coupled analysis, the single discipline analysis and the response surface approximate equation. The new strategy solves the difficulty of precision and efficiency, and shown to be able to complete the turbine MDO with satisfactory performance.
[1] AIAA Technical Committee for MDO. Current state of the art: multidisciplinary design optimization. Washington D.C.: AIAA White Paper. ISBN 1-56347-021-7, 1991.
[2] Kroo I, Altus S, Braun R, et al. Multidisciplinary optimization methods for aircraft preliminary design. AIAA-1994-4325, 1994.
[3] Sangook J, Young-Hee J, Rho A J, et al. Application of collaborative optimization using response surface methodology to an aircraft wing design. AIAA-2004-4442, 2004.
[4] Guo J. Research on multidiscipline design optimization. Xi'an: College of Astronautics, Northwestern Polytechnical University, 2001. (in Chinese) 郭健. 多学科设计优化技术研究. 西安: 西北工业大学航天学院, 2001.
[5] Han M H, Deng J T. Improvement of collaborative optimization. Chinese Journal of Mechanical Engineering, 2006, 42(11): 34-38. (in Chinese) 韩明红, 邓家禔. 协同优化算法的改进. 机械工程学报, 2006, 42(11): 34-38.
[6] Yin Z Y, Mi D, Wu L Q, et al. Study on multidisciplinary design optimization of aero-engine. Engineering Science, 2007, 9(6): 1-10. (in Chinese) 尹泽勇, 米栋, 吴立强, 等. 航空发动机多学科设计优化技术研究. 中国工程科学, 2007, 9(6): 1-10.
[7] Wang R Q, Jia Z G, Yang J J, et al. Study on disk and blade design based on multi-layer optimization strategy. Journal of Aerospace Power, 2012, 27(6): 1201-1209. (in Chinese) 王荣桥, 贾志刚, 杨俊杰, 等. 基于多层优化策略的涡轮盘叶设计研究. 航空动力学报, 2012, 27(6): 1201-1209.
[8] Kaufman M, Balabanov V, Giunta A A, et al. Variable-complexity response surface approximations for wing structural weight in HSCT design. Computational Mechanics, 1996, 18(2): 112-126.
[9] Singh G, Grandhi R V. Mixed-variable optimization strategy employing multifidelity simulation and surrogate models. AIAA Journal, 2010, 48(1): 215-223.
[10] Baker M L, Munson M J, Alston K Y, et al. Integrated hypersonic aeromechanics tool. AIAA-2003-6952, 2003.
[11] Livne E, Navarro I. Nonlinear equivalent plate modeling of wing-box structures. Journal of Aircraft, 1999, 36(5): 851-865.
[12] MacMillin P E. Trim, control, and performance effects in variable-complexity high-speed civil transport design. Blacksburg, VA: School of Aerospace Engineering, Virginia Polytechnic Institute and State University, 1996.
[13] Robinson T D, Eldred M S, Willcox K E, et al. Surrogate-based optimization using multifidelity models with variable parameterization and corrected space mapping. AIAA Journal, 2008, 46(11): 2814-2822.
[14] Wang R Q, Jia Z G, Fan J, et al. Hexahedral mesh regeneration method for MDO on complex aero-engine components. Journal of Aerospace Power, 2011, 26(9): 2032-2038. (in Chinese) 王荣桥, 贾志刚, 樊江, 等. 复杂构件MDO六面体网格重构方法. 航空动力学报, 2011, 26(9): 2032-2038.
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