Experimental and numerical investigation of crashworthiness performance for optimal automobile structures using response surface methodology and oppositional based learning differential evolution algorithm

In this study, experimental and numerical crash analyses are carried out to reach an optimum bumper beam and energy absorber design for a passenger car. Design parameters have been created to determine the most crash-efficient bumper beam and energy absorber models. The models that are formed by usi...

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Veröffentlicht in:Materialprüfung 2023-03, Vol.65 (3), p.346-363
Hauptverfasser: Yildirim, Ahmet, Demirci, Emre, Karagöz, Selçuk, Özcan, Şevket, Yildiz, Ali Riza
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container_end_page 363
container_issue 3
container_start_page 346
container_title Materialprüfung
container_volume 65
creator Yildirim, Ahmet
Demirci, Emre
Karagöz, Selçuk
Özcan, Şevket
Yildiz, Ali Riza
description In this study, experimental and numerical crash analyses are carried out to reach an optimum bumper beam and energy absorber design for a passenger car. Design parameters have been created to determine the most crash-efficient bumper beam and energy absorber models. The models that are formed by using Taguchi tables are subjected to crash analysis, and the responses are obtained to find an optimal design. Response surface methodology is used to approximate the structural responses in crash analysis, and the optimum bumper beam and energy absorber models are obtained by the differential evolution algorithm. The optimum model is subjected to crash analysis in the Hyperform software without considering the sheet metal forming effect. Besides, the model is analyzed by incorporating forming history into the crash analysis. As a result of the numerical analysis, a new energy absorber and bumper beam model with the better crash performance and weight reduction are obtained.
doi_str_mv 10.1515/mt-2022-0304
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source De Gruyter journals
subjects bumper beam
crashworthiness
energy absorber
optimization
sheet metal forming
title Experimental and numerical investigation of crashworthiness performance for optimal automobile structures using response surface methodology and oppositional based learning differential evolution algorithm
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