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Research Papers

Robust Design Optimization for Crashworthiness of Vehicle Side Impact

[+] Author and Article Information
Souvik Chakraborty

Department of Civil Engineering,
Indian Institute of Technology Roorkee,
Roorkee 247667, India
e-mail: csouvik41@gmail.com

Tanmoy Chatterjee

Department of Civil Engineering,
Indian Institute of Technology Roorkee,
Roorkee 247667, India
e-mail: tanmoydce88@gmail.com

Rajib Chowdhury

Department of Civil Engineering,
Indian Institute of Technology Roorkee,
Roorkee 247667, India
e-mail: rajibfce@iitr.ac.in

Sondipon Adhikari

Professor
College of Engineering,
Swansea University,
Bay Campus, Fabian Way,
Swansea SA18EN, UK
e-mail: s.adhikari@swansea.ac.uk

Manuscript received November 18, 2015; final manuscript received October 18, 2016; published online June 12, 2017. Assoc. Editor: Sankaran Mahadevan.

ASME J. Risk Uncertainty Part B 3(3), 031002 (Jun 12, 2017) (9 pages) Paper No: RISK-15-1110; doi: 10.1115/1.4035439 History: Received November 18, 2015; Revised October 18, 2016

Optimization for crashworthiness is of vast importance in automobile industry. Recent advancement in computational prowess has enabled researchers and design engineers to address vehicle crashworthiness, resulting in reduction of cost and time for new product development. However, a deterministic optimum design often resides at the boundary of failure domain, leaving little or no room for modeling imperfections, parameter uncertainties, and/or human error. In this study, an operational model-based robust design optimization (RDO) scheme has been developed for designing crashworthiness of vehicle against side impact. Within this framework, differential evolution algorithm (DEA) has been coupled with polynomial correlated function expansion (PCFE). An adaptive framework for determining the optimum basis order in PCFE has also been presented. It is argued that the coupled DEA–PCFE is more efficient and accurate, as compared to conventional techniques. For RDO of vehicle against side impact, minimization of the weight and lower rib deflection of the vehicle are considered to be the primary design objectives. Case studies by providing various emphases on the two objectives have also been performed. For all the cases, DEA–PCFE is found to yield highly accurate results.

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Figures

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Fig. 1

Comparison of RDO with that of deterministic design optimization

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Fig. 2

Flowchart for DEA–PCFE

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Fig. 3

2-bar truss structure considered for validation

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Fig. 4

Vehicle model for side impact problem

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