Multi-Objective Genetic Algorithm to Optimize Variable Drawbead Geometry for Tailor Welded Blanks Made of Dissimilar Steels
- Authors
- Hariharan, Krishnaswamy; Ngoc-Trung Nguyen; Chakraborti, Nirupam; Lee, Myoung-Gyu; Barlat, Frederic
- Issue Date
- 12월-2014
- Publisher
- WILEY-V C H VERLAG GMBH
- Keywords
- TWB; drawbead; TWIP steel; multi-objective optimization; genetic algorithm; neural net
- Citation
- STEEL RESEARCH INTERNATIONAL, v.85, no.12, pp.1597 - 1607
- Indexed
- SCIE
SCOPUS
- Journal Title
- STEEL RESEARCH INTERNATIONAL
- Volume
- 85
- Number
- 12
- Start Page
- 1597
- End Page
- 1607
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/96707
- DOI
- 10.1002/srin.201300471
- ISSN
- 1611-3683
- 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.
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Collections - College of Engineering > Department of Materials Science and Engineering > 1. Journal Articles
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