一种基于协同近似的多学科设计优化方法

doi:10.3969/j.issn.1004-132X.2021.01.002

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Abstract In order to avoid complex time-consuming multidisciplinary analysis and cumbersome sensitivity calculation in solving complex engineering multidisciplinary design optimization problems, a CMSO method was proposed for multidisciplinary design optimization. Firstly, a collaboration model was used to filter sample points which might reflect the characteristics of the multidisciplinary design optimization problem better and to maintain the multidisciplinary consistency of the system. Then, adaptive surrogate models were constructed, verified and confirmed through the selected sample points. Then the best surrogate model was selected to approximate the multidisciplinary design optimization model and the sequence quadratic program method was used for optimization solution. The feasibility and effectiveness of the CSMO method were verified by a mathematical example and a cylindrical spiral compression spring design case, and the high efficiency of CMSO method was demonstrated by comparison with individual discipline feasible.

Key words： collaboration model adaptive surrogate model collaboration model surrogate optimization（CMSO） multidisciplinary design optimization

PACS:	TH122
	O244

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	Articles by authors
	YI Yongsheng1
	2
	LI Wei1
	GAO Liang1
	XIAO Mi1
	QIU Haobo1

Cite this article:

YI Yongsheng1,2,LI Wei1等. CMSO for Multidisciplinary Design Optimization Method[J]. China Mechanical Engineering, 2021, 32(01): 12-17.

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http://www.cmemo.org.cn/EN/10.3969/j.issn.1004-132X.2021.01.002 OR http://www.cmemo.org.cn/EN/Y2021/V32/I01/12

[1]	SOBIESZCZANSKI-SOBIESKI J, HAFTKA R T. Multidisciplinary Aerospace Design Optimization: Survey of Recent Developments[J]. Structural and Multidisciplinary Optimization, 1997, 14(1): 1-23.
[2]	DESHPANDE S G, WATSON L T, LOVE N J, et al. Aircraft Design Markup Language for Multidisciplinary Aircraft Design and Analysis[J]. Journal of Aerospace Information Systems, 2015, 12(2): 267-283.
[3]	LOBBIA M A. Multidisciplinary Design Optimization of Waverider-derived Crew Reentry Vehicles[J]. Journal of Spacecraft and Rockets, 2017, 54(1): 233-245.
[4]	HU X Z, CHEN X Q, LATTARULO V, et al. Multidisciplinary Optimization under High-dimensional Uncertainty for Small Satellite System Design[J]. AIAA Journal, 2016, 54(5): 1732-1741.
[5]	WANG D P, WANG G G, NATERER G F. Extended Collaboration Pursuing Method for Solving Larger Multidisciplinary Design Optimization Problems[J]. AIAA Journal, 2007, 45(6): 1208-1221.
[6]	WANG D P, WANG G G, NATERER G F. Collaboration Pursuing Method for Multidisciplinary Design Optimization Problems[J]. AIAA Journal, 2007, 45(5): 1091-1103.
[7]	YANG D C, JANG I S, JANG M H, et al. Optimization of Additive Compositions for Anode in Ni-MH Secondary Battery Using the Response Surface Method[J]. Metals and Materials International, 2009, 15(3): 421-425.
[8]	BUHMANN M D. Radial Basis Functions[J]. Acta Numerica, 2000, 9(5): 1-38.
[9]	STEIN MICHAEL L. Interpolation of Spatial Data: Some Theory for Kriging［M］. New York: Springer-Verlag, 1999.
[10]	FANG K T, WINKER P, ZHANG Y. Uniform Design: Theory and Application[J]. Technometrics, 2000, 42(3): 237-248.
[11]	BOX G E P. The Exploration and Exploitation of Response Surfaces: Some General Considerations and Examples[J]. Biometrics, 1954, 10(1): 16-60.
[12]	MCKAY M D, BECKMAN R J, CONOVER W J. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code[J]. Technometrics, 2000, 42(1): 55-61.
[13]	ZHOU W H, YUEN K V, TAN F. Estimation of Maximum Pullout Shear Stress of Grouted Soil Nails Using Bayesian Probabilistic Approach[J]. International Journal of Geomechanics, 2013, 13(5): 659-664.
[14]	LI W, XIAO M, PENG X B, et al. A Surrogate Thermal Modeling and Parametric Optimization of Battery Pack with Air Cooling for EVs[J]. Applied Thermal Engineering, 2019, 147: 90-100.
[15]	PEREZ R, LIU H H T, BEHDINAN K. Evaluation of Multidisciplinary Optimization Approaches for Aircraft Conceptual Design[J]. AIAA Journal, 2004.
[16]	李永华, 黄洪钟, 刘忠贺. 结构稳健可靠性分析的凸集模型[J]. 应用基础与工程科学学报, 2004, 12(4): 383-391.
	LI Yonghua, HUANG Hongzhong, LIU Zhonghe. Convex Model in Robust Reliability Analysis of Structure[J]. Journal of Basic Science and Engineering, 2004, 12(4): 383-391.
[17]	李伟. 基于时变不确定分析的多学科设计优化方法研究[D]. 成都：电子科技大学, 2017.
	LI Wei. Study for Multidisciplinary Design Optimization Based on Time-varying Uncertainty Analysis[D].Chengdu：University of Electronic Science and Technology of China, 2017.