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Journal Article

Citation

Kulkarni SM, Priyal V, Mali KD, Kulkarni DM. Int. J. Crashworthiness 2023; 28(5): 616-628.

Copyright

(Copyright © 2023, Informa - Taylor and Francis Group)

DOI

10.1080/13588265.2022.2111489

PMID

unavailable

Abstract

Crash-box is an essential passive safety device in an automobile that absorbs the kinetic energy of an external impact during an accident, thereby improving passenger safety. Selecting a suitable material for fabricating a crash-box to maximize its crashworthiness performance is a critical issue and is a multi-attribute decision-making (MADM) problem. This study focuses on choosing an appropriate aluminium alloy for a crash-box out of 16 different frequently used wrought aluminium alloys considered as alternatives based on eight crashworthiness performance indicators used as attributes by taking the opinions of three decision-makers (DMs). The effect of varying the material of thin-walled circular crash-boxes with identical geometry is first examined by simulating their axial quasi-static collapse using ABAQUS/Explicit. Various crashworthiness performance indicators obtained from these simulations are used for the decision-making process. While taking a decision, the opinions of several DMs from varied backgrounds are generally considered. A systematic approach is proposed to determine the importance of each DM involved in group decision-making situations by considering their credentials, such as educational qualification, work experience, etc., using a ranking based MADM technique known as 'R-Method'. Opinions of multiple DMs are then combined to come up with a single final decision, called a consensus. The application of the R-Method is discussed in detail to derive consensus in a group decision-making environment. The aluminium alloy AA 7075 T6 is the best, while AA 3003 H12 is the least preferred material for manufacturing a crash-box of the considered geometry as per the proposed method.


Language: en

Keywords

aluminium alloys; Crash-box; crashworthiness; multi-attribute group decision-making; R-method

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