Use of support vector regression in structural optimization: Application to vehicle crashworthiness design

Ping Zhu*, Feng Pan, Wei Chen, Siliang Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)21-31
Number of pages11
JournalMathematics and Computers in Simulation
Volume86
DOIs
StatePublished - 2012

Keywords

  • Crashworthiness
  • Metamodel
  • Structural optimization
  • Support vector regression
  • Vehicle lightweight design

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)
  • Numerical Analysis
  • Modeling and Simulation
  • Applied Mathematics

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