Many metamodeling techniques have been developed in the past two decades to reduce the computational cost of design evaluation. With the increasing scale and complexity of engineering problems, popular metamodeling techniques including artificial neural network (ANN), Polynomial regression (PR), Kriging (KG), radial basis functions (RBF), and multivariate adaptive regression splines (MARS) face difficulties in solving highly nonlinear problems, such as the crashworthiness design. Therefore, in this work, we integrate the least support vector regression (LSSVR) with the mode pursuing sampling (MPS) optimization method and applied the integrated approach for crashworthiness design. The MPS is used for generating new samples which are concentrated near the current local minima at each iteration and yet still statistically cover the entire design space. The LSSVR is used for establishing a more robust metamodel from noisy data. Therefore, the proposed method integrates the advantages of both the LSSVR and MPS to more efficiently achieve reasonably accurate results. In order to verify the proposed method, well-known highly nonlinear functions are used for testing. Finally, the proposed method is applied to three typical crashworthiness optimization cases. The results demonstrate the potential capability of this method in the crashworthiness design of vehicles.
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e-mail: wanghuenying@hotmail.com
e-mail: shans@cc.umanitoba.ca
e-mail: gary_wang@sfu.ca
e-mail: gyli@hnu.cn
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April 2011
Research Papers
Integrating Least Square Support Vector Regression and Mode Pursuing Sampling Optimization for Crashworthiness Design
Hu Wang,
Hu Wang
The State Key Laboratory of Advanced Technology for Vehicle Design and Manufacture, College of Mechanical and Vehicle Engineering,
e-mail: wanghuenying@hotmail.com
Hunan University
, Changsha, Hunan, P. R. China
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Songqing Shan,
Songqing Shan
Department of Mechanical and Manufacturing Engineering,
e-mail: shans@cc.umanitoba.ca
University of Manitoba
, Winnipeg, MB, R3T 5V6, Canada
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G. Gary Wang,
G. Gary Wang
School of Engineering Science,
e-mail: gary_wang@sfu.ca
Simon Fraser University
, Surrey, BC, V3T 0A3, Canada
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Guangyao Li
Guangyao Li
The State Key Laboratory of Advanced Technology for Vehicle Design and Manufacture, College of Mechanical and Vehicle Engineering,
e-mail: gyli@hnu.cn
Hunan University
, Changsha, Hunan, P. R. China
Search for other works by this author on:
Hu Wang
The State Key Laboratory of Advanced Technology for Vehicle Design and Manufacture, College of Mechanical and Vehicle Engineering,
Hunan University
, Changsha, Hunan, P. R. China
e-mail: wanghuenying@hotmail.com
Songqing Shan
Department of Mechanical and Manufacturing Engineering,
University of Manitoba
, Winnipeg, MB, R3T 5V6, Canada
e-mail: shans@cc.umanitoba.ca
G. Gary Wang
School of Engineering Science,
Simon Fraser University
, Surrey, BC, V3T 0A3, Canada
e-mail: gary_wang@sfu.ca
Guangyao Li
The State Key Laboratory of Advanced Technology for Vehicle Design and Manufacture, College of Mechanical and Vehicle Engineering,
Hunan University
, Changsha, Hunan, P. R. China
e-mail: gyli@hnu.cn
J. Mech. Des. Apr 2011, 133(4): 041002 (10 pages)
Published Online: May 9, 2011
Article history
Received:
September 22, 2009
Revised:
February 24, 2011
Accepted:
March 16, 2011
Online:
May 9, 2011
Published:
May 9, 2011
Citation
Wang, H., Shan, S., Wang, G. G., and Li, G. (May 9, 2011). "Integrating Least Square Support Vector Regression and Mode Pursuing Sampling Optimization for Crashworthiness Design." ASME. J. Mech. Des. April 2011; 133(4): 041002. https://doi.org/10.1115/1.4003840
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