Thermal-electric coupling systems analysis of electronic cabinets with consideration of numerical noises
ZHANG Zhuo 1 YU Fei 2 Wang Qiuying 3 Du Shipeng 1
Author information+
1. College of Automation,Harbin Engineering University,Harbin 150001,China;
2. College of Science, Harbin Engineering University, Harbin 150001, China;
3.College of Information And Communication Engineering, Harbin Engineering University 150001, China
One of the difficulties in multidisciplinary design optimization for electronic cabinets is that the design functions are often not smooth or even discontinuous due to numerical noises. In order to tackle this problem, a global optimization strategy for multidisciplinary systems is developed. Firstly, the system analysis problem is transformed into an optimization problem according to the idea of SAND(Simultaneous Analysis and Design). Kriging models are introduced as surrogate models for the output variables of each subsystem in order to filter the numerical noises. The initial Kriging models are built by using sparse sample points. The location of next samples is determined by an “infill sampling criterion” which is derived by the maximum likelihood estimation. When the simulation tools exhibit large numerical noises, this method can greatly reduce the number of subsystem simulations needed in system analysis compared with other methods such as the fixed point iteration method. Lastly, a typical thermal-electric coupling problem is taken as an example for demonstration of the effectiveness of the proposed method.
ZHANG Zhuo 1 YU Fei 2 Wang Qiuying 3 Du Shipeng 1.
Thermal-electric coupling systems analysis of electronic cabinets with consideration of numerical noises[J]. Journal of Vibration and Shock, 2017, 36(13): 214-222
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] Renaud J. E. and Gabriele G. A. ,“Approximation in Nonhierarchic System Optimization” , AIAA Journal, Vol.32, No.1, 1994, pp.198-205.
[2] Eyal Arian, “Convergence estimates for multidisciplinary analysis and optimization,” NASA/CR-201752, ICASE report no. 97-57 (Oct. 1997) .
[3] Han Yong-zhi, Gao Hang-shan, Li Li-zhou, “Kriging Model-Based Multidisciplinary Design Optimization for Turbine Blade” , Journal of Aerospace Power, Vol.22, No.7, 2007, pp.1055-1059.
[4] Koch P. N., Simpson T.W., Allen J. K., and Mistree F., “Statistical Approximations for Multidisciplinary Design Optimization: The Problem of Size” , Journal of Aircraft, AIAA, Vol.36, No.1,1999, pp. 275-286.
[5] Jang B.S., Yang Y.S., Jung H.S. and Yeun Y.S., “Managing Approximation Models in Collaborative Optimization” , Stuct. Multidisc Optim., Vol.30, No.1, 2005, pp.11-26.
[6] Bai Xiao-tao, Li Wei-ji, “Application of Collaborative Optimization Based on Approximate Methods in Wing Design Optimization” . Acta Aeronautica Et Astronautica Sinica, Vol.27, No.5, 2006, pp.847-850.
[7] 韩永志 ,高行山,李立州,岳珠峰,基于Kriging模型的涡轮叶片多学科优化设计[J],航空动力学报,2007,22(7):1055~1059.
HAN Yong-zhi, GAO Hang-shan, LI Li-zhou, Kriging Model-Based Multidisciplinary Design Optimization for Turbine Blade [J]. Journal of Aerospace Power, 2007, 22(7): 1055-1059/
[8] 白小涛,李为吉,基于近似技术的协同优化方法在机翼设计优化中的应用 [J],航空学报,2006,27(5):847-850.
BAI Xiao-tao, LI Wei-ji, Application of Collaborative Optimization Based on Approximate Methods in Wing Design Optimization [J]. Acta Aeronautica Et Astronautica Sinica, 2006,27(5):847-850.
[9] Cramer EJ, Dennis JE, Frank PD, Lewis RM, Shubin GR. “Problem formulation for multidisciplinary optimization” , SIAM J Optim, Vol.4, No.4,1994, pp.754–776.
[10] Balling, R.J. and Sobieszczanski-Sobieski, J.,“Optimization of coupled system: A critical overview of approaches,” Proceeding of the 5th AIAA/NASA/USAF/ISSMO Symposium of Multidisciplinary Analysis and Optimization, AIAA-94-4330-CP, Panama City, Florida, 1994,pp.697-707.
[11] S. L. Padula, N. M. Alexandrov, L. L. Green. MDO Test Suite at NASA LangleyResearch Center [C], AIAA paper AIAA-96-4028, Proceedings of the Sixth AIAA/NASA/ ISSMO Symposium on Multidisciplinary Analysis and Optimization, Bellevue, WA, Sept. 4-6, 1996.
[12] Kay E. Vugrin, “On the Effect of Numerical Noise in Simulation-Based Optimization. Master of Science in Mathematics”, the Virginia Polytechnic Institute and State University, 2003.
[13] Timothy W Simpson, Farrokh Mistree. “Kriging Models for Global Approximation in Simulation-Based Multidisciplinary Design Optimization” , AIAA JOURNAL, Vol.39, No.12, 2001, pp.54-61.
[14]王彦.基于改进EGO算法的黑箱函数全局最优化.[硕士学位论文].北京:北京工业大学,2014
Wang Yan.Global Optimization of Black-box Function Using Improved Ego Algorithm,[D].Peking:Peking University
[15]杨晓涛,谷正气,杨振东,董光平,谢超,汽车乘员舱多层吸声材料的多目标优化[J],振动与冲击,2013,32(4):21-25.
Yang Xiaotao,Gu Zhengqi,Yang Zhendong,Huang Guangpin,Multi-target optimization of multilayer sound absorption material combinations in passenger compartment of a car[J],Journal of Vibration and Shock,2013,32(4):21-25.
[16]郭旺柳,宋文萍,许建华,许瑞飞,旋翼桨尖气动/降噪综合优化设计研究[J],西北工业大学学报,2012,30(1):73-79.
Guo Wangliu,Song Wenping,Xu Jianhua,Xu Ruifei,An Effective Aerodynamics/Acoustic Optimization of Blade Tip Planform for Helicopter Rotors.[J].Journal of Northwestern Polytechnical University,2012,30(1):73-79.
[17]匡玲.基于近似模型的两级集成系统协同优化方法研究.[硕士学位论文].武汉:华中科技大学,2012.
Kuang Ling, Bi-Level Integrated System Synthesis Collaborative Optimization Method based on Approximate Model[D].Wuhan: Huazhong University of Science and Technology,2012.
[18]张勇.基于近似模型的汽车轻量化优化设计方法.[博士学位论文].湖南:湖南大学,2008
Zhang Yong.Optimization Design Method of Vehiele Lightweight Based on Approximate Model.[D].Hunan:Hunan University.2008
[19]黎凯,杨旭静,郑娟,基于参数和代理模型不确定性的冲压稳健性设计优化[J],振动与冲击,2015,26(23):3234-3239.
Li Kai,Yang Xujing,Zheng Juan,Robust Design Optimization for Stamping Based on Parametric and Metamodel Uncertainty[J],Journal of Vibration and Shock,2015,26(23):3234-3239.
[20]高海洋.基于振动特征指标与Kriging模型的结构损伤识别方法研究.[博士学位论文].大连:大连理工大学,2013.
Gao Haiyang, Study on structural damage identification method based on vibration characteristic index and Kriging model,[D],Dalian: Dalian University of Technology,2013.
[21]张晓琳.基于二次外罚函数和Kriging模型的目标级联方法研究.[硕士学位论文].武汉:华中科技大学,2013
Zhang xiaoling, Analytical Target Cascading based on the Quadratic Exterior Penalty Function and Kriging Model.[D].Wuhan: Huazhong University of Science and Technology,2013
[22]左曙光,韦开君,吴旭东,聂玉洁,许思传,采用 Kriging 模型的离心压缩机叶轮多目标参数优化[J],农业工程学报,2016,32(2):77-83.
Zuo Shuguang,Wei Kaijun,Wu xudong,Multi-objective parameter optimization of centrifugal compressor impeller with Kriging model[J]Transactions of the Chinese Society of Agricultural Engineering,2016,32(2):77-83.
[23]高月华.基于Kriging代理模型的优化设计方法及其在注塑成型中的应用.[博士学位论文].大连:大连理工大学,2009.
Gao Yuehua.Optimization Methods Based on Kriging Surrogate Model and Their Applieation in Injection Molding.[D].Dalin: Dalian University of Technology. 2009.
[24]Hoerl, A. E., and Kennard, R. W., Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, Vol. 12, No. 1, 1970, pp. 55-67.
[25]Tikhonov, A. N., and Arsenin, V. Y., Solutions of Ill-Posed Problems. Winston, Washington, D.C., 1977.
[26]Jones, D.R.. A Taxonomy of Global Optimization Methods Based on Response Surfaces [J], Journal of Global Optimization 2001,21(4) :345–383.
[27]Forrester, A.I.J.. Efficient Global Optimization Using Expensive CFD Simulations [D], PhD thesis, University of Southampton, Southampton, 2004.
[28]Alexander I.J. Forrester, Andy J. Keane and Neil W.Bressloff, Design and Analysis of “Noisy” Computer Experiments, AIAA Journal, 2006,44(10):2331-2339.
[29]Michael James Sasena, “Flexibility and efficiency enhancements for constrained global design optimization with Kriging approximations,”PHD thesis, University of Michigan, Michigan, the U.S. 2002.