Modeling the strain localization of shell elements subjected to combined stretch–bend loads: Application on automotive sheet metal stamping simulationsShow others and affiliations
2023 (English)In: Thin-walled structures, ISSN 0263-8231, E-ISSN 1879-3223, Vol. 188, article id 110804Article in journal (Refereed) Published
Abstract [en]
This study presents a modeling approach for predicting strain localization during sheet metal stamping processes focused on automotive engineering applications. The so-called stretching-to-bending ratio, ρ, is proposed to characterize the loading conditions acting on an element during stamping processes. Then, localized strain or necking strain is suggested to be a function of ρ. Different stretch–bending tests with different tool radii, i.e., R3, R6, R10, and R50 are conducted for two automotive sheet metals, DP800 and AA6010, to identify their forming limits under combined stretch–bend loads. The calibrated necking limit curve of the AA6016 sheet is then employed in AutoForm R10 software to predict the necking and failure of a stamped panel. Agreement with the experimental observation of failure positions of the panel validates the usefulness of the proposed modeling approach in practice.
Place, publisher, year, edition, pages
Elsevier Ltd , 2023. Vol. 188, article id 110804
Keywords [en]
Automotive sheet metal, Shell element, Strain localization, Stretch–bending load, Through-thickness strain gradient, Ductile fracture, Sheet metal, Stamping, Automotive sheet metals, Bending load, Strain gradients, Strain localizations, Stretch-bending, Thickness strain, Through-thickness, Bending tests
National Category
Applied Mechanics
Identifiers
URN: urn:nbn:se:ri:diva-64851DOI: 10.1016/j.tws.2023.110804Scopus ID: 2-s2.0-85158853466OAI: oai:DiVA.org:ri-64851DiVA, id: diva2:1758236
Funder
Vinnova, 2020-02986Knowledge Foundation, 20200125)
Note
The authors gratefully acknowledge the financial support from VINNOVA in the Sustainable Production subprogram within Vehicle Strategic Research and Innovation (FFI) program, Sweden(grant number 2020-02986) and KK-Stiftelsen, Sweden (grant number 20200125). Open Access funding was provided by the Blekinge Institute of Technology, Sweden .
2023-05-222023-05-222023-05-25Bibliographically approved