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Probability-based least square support vector regression metamodeling technique for crashworthiness optimization problems

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Abstract

This paper presents a crashworthiness design optimization method based on a metamodeling technique. The crashworthiness optimization is a highly nonlinear and large scale problem, which is composed various nonlinearities, such as geometry, material and contact and needs a large number expensive evaluations. In order to obtain a robust approximation efficiently, a probability-based least square support vector regression is suggested to construct metamodels by considering structure risk minimization. Further, to save the computational cost, an intelligent sampling strategy is applied to generate sample points at the stage of design of experiment (DOE). In this paper, a cylinder, a full vehicle frontal collision is involved. The results demonstrate that the proposed metamodel-based optimization is efficient and effective in solving crashworthiness, design optimization problems.

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Abbreviations

AIMS:

Adaptive and interactive modeling system

BBNS:

Boundary and best neighbor sampling

D-OPT:

D-optimum

DOE:

Design of experiment

ERM:

Empirical risk minimization

FE:

Finite element

FF:

Full factorial

KKT:

Karush–Kuhn–Tucker

LHS:

Latin hypercube sampling

LS-SVR:

Least square support vector regression

PR-RSM:

Polynomial regression response surface methodology

PSO:

Particle swarm optimization

RBF:

Radial basis function

PLS-SVR:

Probability-based least square support vector regression

SM:

Space mapping

SVR:

Support vector regression

SSE:

Sum-squared error

SRM:

Structure risk minimization

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Authors and Affiliations

  1. Key Laboratory of Advanced Technology for Vehicle Body Design and Manufacture, College of Mechanical and Automobile Engineering, Hunan University, Changsha, 410082, People’s Republic of China

    Hu Wang & G. Y. Li

  2. School of Logistics, Central South University of Forestry and Teleology, Changsha, 41004, People’s Republic of China

    Enying Li

Authors
  1. Hu Wang
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  2. Enying Li
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  3. G. Y. Li
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Correspondence to Hu Wang or G. Y. Li.

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Wang, H., Li, E. & Li, G.Y. Probability-based least square support vector regression metamodeling technique for crashworthiness optimization problems. Comput Mech 47, 251–263 (2011). https://doi.org/10.1007/s00466-010-0532-y

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