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Uncertainty quantification for conical hole expansion test of DP800 sheet metal
Hanoi University of Science & Technology, Vietnam.
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: 0000-0002-1162-7023
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0002-7730-506x
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2025 (English)In: International Journal of Material Forming, ISSN 1960-6206, E-ISSN 1960-6214, Vol. 18, no 1, article id 5Article in journal (Refereed) Published
Abstract [en]

The hole expansion ratio (HER) observed in a standardized hole expansion test (HET) is commonly used to determine the edge fracture of steel sheets. A large variation of the measured HER restricts the practical application of the method. This study presents a systematic investigation on uncertainties in the HER of DP800 sheet material, including the hole-edge quality, pre-strain due to the hole-punching process, the friction coefficient, and the determination of fracture. An artificial neural network was trained to develop a surrogate model using a database gained from a thousand finite element simulations of the HET. Monte-Carlo simulations were performed using the trained surrogate model to characterize the distribution of the HER. Sensitivity analysis via Sobol's indices is calculated to determine the influence of the input variables on the output. It is found that the pre-strain and pre-damage generated during the hole punching process in the shear-affected zone dominate the variation of the HER. Discussions on reducing the output's variation are detailed. In general, these findings provide valuable insights for the determination of HER as well as the edge crack behavior of the investigated DP800 steel sheet.

Place, publisher, year, edition, pages
Springer, 2025. Vol. 18, no 1, article id 5
Keywords [en]
Hole expansion test, Edge crack, Uncertainty quantification, Monte-Carlo simulation, Sensitivity analysis, DP800 steel
National Category
Materials Engineering
Identifiers
URN: urn:nbn:se:bth-27261DOI: 10.1007/s12289-024-01869-1ISI: 001371208200001Scopus ID: 2-s2.0-85211151297OAI: oai:DiVA.org:bth-27261DiVA, id: diva2:1922066
Part of project
PREDICT- Failure prediction for complex load cases, Knowledge Foundation, Vinnova
Funder
Vinnova, 2020-02986Available from: 2024-12-17 Created: 2024-12-17 Last updated: 2025-09-30Bibliographically approved

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Barlo, AlexanderIslam, Md. ShafiqulSigvant, MatsPilthammar, Johan

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