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An evaluation method for experimental necking detection of automotive sheet metals
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0002-8204-4802
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0002-1162-7023
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0001-9889-6746
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0002-7730-506x
2023 (English)In: 42ND CONFERENCE OF THE INTERNATIONAL DEEP DRAWING RESEARCH GROUP / [ed] Asnafi, N Lindgren, LE, IOP PUBLISHING LTD , 2023, Vol. 1284, article id 012020Conference paper, Published paper (Refereed)
Abstract [en]

In sheet metal stamping, the occurrence of strain localization in a deformed sheet is considered a failure. As so, sheet metal's formability is conventionally evaluated using the Forming Limit Diagram (FLD), which separates the principal strain space into safety and unsafety regions by a Forming Limit Curve (FLC). This study presents an evaluation method for detecting strain localization based on Digital Image Correlation (DIC) during the experiment. The commercial DIC software ARAMIS is adopted to monitor the strain-field distribution on the deformed specimen's surface. A detailed analysis of the proposed method is presented considering Nakajima tests conducted for two automotive sheet metals: AA6016 and DP800. The identified FLC based on the proposed method is compared with that of well-established methods such as ISO 12004:2-2008 and time-dependent methods. For both investigated materials, the proposed method presents a lower FLC than the others.

Place, publisher, year, edition, pages
IOP PUBLISHING LTD , 2023. Vol. 1284, article id 012020
Series
IOP Conference Series-Materials Science and Engineering, ISSN 1757-8981
National Category
Other Materials Engineering
Identifiers
URN: urn:nbn:se:bth-25249DOI: 10.1088/1757-899X/1284/1/012020ISI: 001017824300020OAI: oai:DiVA.org:bth-25249DiVA, id: diva2:1786206
Conference
42nd Conference of the International-Deep-Drawing-Research-Group (IDDRG), JUN 19-22, 2023, Lulea, SWEDEN
Part of project
PREDICT- Failure prediction for complex load cases, Knowledge Foundation, Vinnova
Funder
Vinnova, 2020-02986Available from: 2023-08-08 Created: 2023-08-08 Last updated: 2023-08-08Bibliographically approved

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Tuan Pham, QuocIslam, Md. ShafiqulBarlo, AlexanderSigvant, Mats

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