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Multi-Objective Genetic Algorithm to Optimize Variable Drawbead Geometry for Tailor Welded Blanks Made of Dissimilar Steels

Title
Multi-Objective Genetic Algorithm to Optimize Variable Drawbead Geometry for Tailor Welded Blanks Made of Dissimilar Steels
Authors
Hariharan, KNguyen, NTChakraborti, NLee, MGBarlat, F이명규
Date Issued
Dec-2014
Publisher
WILEY-V C H VERLAG GMBH
Abstract
Formability of a tailor welded blank (TWB) is affected by the strength ratio of the base metals joined. In this paper, formability of TWB with very high strength ratio made by joining twinning-induced plasticity (TWIP) and low carbon steels is numerically studied using a limiting dome height test. The drawbead geometry at the weaker side is modified to increase the dome height. The design of drawbead is optimized by treating it as a multi-objective problem with maximum dome height and minimum weldline movement as objectives, which were constructed as metamodels through a genetic algorithms based approach. The necessary data for the metamodeling are generated by finite element (FE) simulation using the commercial solver, LS-DYNA (R). The multi-objective optimization is carried out using a predator-prey genetic algorithm. The Pareto front estimated using this evolutionary approach is validated using FE simulations and a good correlation is obtained.
Keywords
TWB; drawbead; TWIP steel; multi-objective optimization; genetic algorithm; neural net; SHEET-METAL FORMABILITY; NATURE-INSPIRED TOOL; MATERIALS SCIENCE; BLAST-FURNACE; AUTOMOTIVE APPLICATIONS; LINE MOVEMENTS; DUAL-PHASE; DESIGN; MODEL; PREDICTION
URI
http://oasis.postech.ac.kr/handle/2014.oak/13824
DOI
10.1002/SRIN.201300471
ISSN
1611-3683
Article Type
ARTICLE
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