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An Optimization Study of Hot Stamping Operation

Authors: Bonyoung Ghoo; Yasuyoshi Umezu; Yuko Watanabe; Ninshu Ma; Ron Averill; F. Barlat; Y. H. Moon; +1 Authors

An Optimization Study of Hot Stamping Operation

Abstract

In the present study, 3‐dimensional finite element analyses for hot‐stamping processes of Audi B‐pillar product are conducted using JSTAMP/NV and HEEDS. Special attention is paid to the optimization of simulation technology coupling with thermal‐mechanical formulations. Numerical simulation based on FEM technology and optimization design using the hybrid adaptive SHERPA algorithm are applied to hot stamping operation to improve productivity. The robustness of the SHERPA algorithm is found through the results of the benchmark example. The SHERPA algorithm is shown to be far superior to the GA (Genetic Algorithm) in terms of efficiency, whose calculation time is about 7 times faster than that of the GA. The SHERPA algorithm could show high performance in a large scale problem having complicated design space and long calculation time.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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