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Application of dimension reduction based multi-parameter optimization for the design of blast-resistant vehicle

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Abstract

The design of blast-resistant vehicle provides an appropriate level of protection for the vehicle and occupants against the serious threat from landmine and improvised explosive devices (IED). Mathematically, the objective of this research is to optimize the configuration of light armored vehicle installed multilayer honeycomb sandwich structures (MHSS), shock-mitigating seat and seat belt, and cope with the challenge of highly computational cost on dealing with the large scale, multi-parameter, nonlinear and fluid-structure interaction simulation models. Multi material Arbitrary Lagrangian-Eulerian (MM-ALE) method is used to obtain the high-precision vehicle responses and occupant injuries under blast wave. The baseline model validated by the blast test is built, and the optimization model for blast-resistant vehicle is defined. Then, identifying important design parameters accurately is so difficultly when sufficient samples are not provided due to the expensive computational cost, and it’s inappropriate to screen parameters with inconsistent sequence of variable sensitivities for occupant injuries. Factor analysis based multi-parameter optimization (FAMO) is proposed to reduce the computational cost on improving the blast resistant performance of vehicle. The normal-boundary intersection (NBI) and the R 2 metric are used to obtain optimal compromise solution which noticeable reduced the peak value of occupant injuries, and the physical insights which drive the optimal solution to reduce the occupant injuries is analyzed. Additional studies are conducted on comparing between proposed algorithm and the conventional algorithm, including shape of the Pareto front, optimal compromise solution, design variables and responses.

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Abbreviations

t h1 :

Thickness of front face-sheet

t h2 :

Thickness of interlayer

t h3 :

Thickness of back face-sheet

t b1 :

Thickness of floor board

t b2 :

Thickness of shock-mitigating seat bracket

k s :

Stiffness of shock absorber

c s :

Damping coefficient of viscous damper

E s :

Young’s modulus of seat belt

X :

Matrix of design variable

C :

Covariance matrix of X

F :

Matrix of factor

A :

Loading matrix of factor

ε :

the error factor

p :

Number of design variables

m :

Number of factors

n :

Number of responses

λ :

Multiple parameter of P

Κ:

Correlation matrix

Λ:

Partial correlation matrix

ρ-value:

Level ofχ 2 distribution

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Acknowledgements

This work is funded by the National Natural Science Foundation of China (grant number: 51405232). The authors would like to thank the Nanjing University of Science &Technology for supporting and providing the relational equipment.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Nanjing University of Science & Technology Nanjing, Nanjing, Jiangsu, 210094, People’s Republic of China

    Ran Wei, Xianhui Wang, Ming Zhang, Yunbo Zhou & Liangmo Wang

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  1. Ran Wei
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  2. Xianhui Wang
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  3. Ming Zhang
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Correspondence to Xianhui Wang.

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Wei, R., Wang, X., Zhang, M. et al. Application of dimension reduction based multi-parameter optimization for the design of blast-resistant vehicle. Struct Multidisc Optim 56, 903–917 (2017). https://doi.org/10.1007/s00158-017-1696-2

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  • DOI: https://doi.org/10.1007/s00158-017-1696-2

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