Springback Prediction
Springback Prediction is a computational modeling method in sheet metal stamping processes that quantifies the elastic recovery of formed metal components after tool release, distinguishing itself by enabling accurate a priori estimation of geometric deviations to improve die design and dimensional accuracy.
489
Publications
18.8K
Citations
1.2K
Authors
388
Institutions
Publications per year
2017–2026
144
489
R. H. Wagoner, Hojun Lim, Myoung‐Gyu Lee · International Journal of Plasticity · 2012 · 361 citations
K.F. Chung, M. H. Lee, Dae-Yong Kim et al. · International Journal of Plasticity · 2005 · 214 citations
Engineering, Automotive Engineering, Materials Engineering +13
Myoung‐Gyu Lee, Dae-Yong Kim, Chongmin Kim et al. · International Journal of Plasticity · 2004 · 205 citations
Engineering, Automotive Engineering, Materials Engineering +16
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388

Northwestern Polytechnical University
Xi'an, China
19 h-index
91 publications
3.7K citations
The Ohio State University
Columbus, United States
19 h-index
38 publications
3.2K citations
Seoul National University
Seoul, South Korea
18 h-index
40 publications
3K citations
General Motors (United States)
Detroit, United States
15 h-index
26 publications
2.1K citations
Pohang University of Science and Technology
Pohang, South Korea
14 h-index
24 publications
1.3K citations

Centre National de la Recherche Scientifique
Paris, France
11 h-index
19 publications
410 citations
University of Aveiro
Aveiro, Portugal
10 h-index
34 publications
1.4K citations

Shanghai Jiao Tong University
Shanghai, China
10 h-index
45 publications
1.8K citations
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57 publications · 3.4K citations
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40 publications · 2.5K citations
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42 publications · 1.2K citations
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20 publications · 1.2K citations
19
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23 publications · 546 citations
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