TY - JOUR
T1 - Use of support vector regression in structural optimization
T2 - Application to vehicle crashworthiness design
AU - Zhu, Ping
AU - Pan, Feng
AU - Chen, Wei
AU - Zhang, Siliang
N1 - Funding Information:
The work presented in this paper was supported by National Natural Science Foundation of China (Grant No. 50875164 ), also partially supported by State Key Laboratory of Mechanical System and Vibration of Shanghai Jiao Tong University (Grant No. MSV-MS-2008-14 ). The authors also thank Science and Technology Commission of Shanghai Municipality (Grant No. 08DZ1150303 ) for providing research funding for this work.
Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - Metamodel is widely used to deal with analysis and optimization of complex system. Structural optimization related to crashworthiness is of particular importance to automotive industry nowadays, which involves highly nonlinear characteristics with material and structural parameters. This paper presents two industrial cases using support vector regression (SVR) for vehicle crashworthiness design. The first application aims to improve roof crush resistance force, and the other is lightweight design of vehicle front end structure subject to frontal crash, where SVR is utilized to construct crashworthiness responses. The use of multiple instances of SVR with different kernel types and hyper-parameters simultaneously and select the best accurate one for subsequent optimization is proposed. The case studies present the successful use of SVR for structural crashworthiness design. It is also demonstrated that SVR is a promising alternative for approximating highly nonlinear crash problems, showing a successfully alternative for metamodel-based design optimization in practice.
AB - Metamodel is widely used to deal with analysis and optimization of complex system. Structural optimization related to crashworthiness is of particular importance to automotive industry nowadays, which involves highly nonlinear characteristics with material and structural parameters. This paper presents two industrial cases using support vector regression (SVR) for vehicle crashworthiness design. The first application aims to improve roof crush resistance force, and the other is lightweight design of vehicle front end structure subject to frontal crash, where SVR is utilized to construct crashworthiness responses. The use of multiple instances of SVR with different kernel types and hyper-parameters simultaneously and select the best accurate one for subsequent optimization is proposed. The case studies present the successful use of SVR for structural crashworthiness design. It is also demonstrated that SVR is a promising alternative for approximating highly nonlinear crash problems, showing a successfully alternative for metamodel-based design optimization in practice.
KW - Crashworthiness
KW - Metamodel
KW - Structural optimization
KW - Support vector regression
KW - Vehicle lightweight design
UR - http://www.scopus.com/inward/record.url?scp=84876031678&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84876031678&partnerID=8YFLogxK
U2 - 10.1016/j.matcom.2011.11.008
DO - 10.1016/j.matcom.2011.11.008
M3 - Article
AN - SCOPUS:84876031678
VL - 86
SP - 21
EP - 31
JO - Mathematics and Computers in Simulation
JF - Mathematics and Computers in Simulation
SN - 0378-4754
ER -