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Analysis of ESAFORM 2021 cup drawing benchmark of an Al alloy, critical factors for accuracy and efficiency of FE simulations
This article details the ESAFORM Benchmark 2021. The deep drawing cup of a 1 mm thick, AA 6016-T4 sheet with a strong cube texture was simulated by 11 teams relying on phenomenological or crystal plasticity approaches, using commercial or self-developed Finite Element (FE) codes, with solid, continu...
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Published in: | International journal of material forming 2022, Vol.15 (5) |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | This article details the ESAFORM Benchmark 2021. The deep drawing cup of a 1 mm thick, AA 6016-T4 sheet with a strong cube texture was simulated by 11 teams relying on phenomenological or crystal plasticity approaches, using commercial or self-developed Finite Element (FE) codes, with solid, continuum or classical shell elements and different contact models. The material characterization (tensile tests, biaxial tensile tests, monotonic and reverse shear tests, EBSD measurements) and the cup forming steps were performed with care (redundancy of measurements). The Benchmark organizers identified some constitutive laws but each team could perform its own identification. The methodology to reach material data is systematically described as well as the final data set. The ability of the constitutive law and of the FE model to predict Lankford and yield stress in different directions is verified. Then, the simulation results such as the earing (number and average height and amplitude), the punch force evolution and thickness in the cup wall are evaluated and analysed. The CPU time, the manpower for each step as well as the required tests versus the final prediction accuracy of more than 20 FE simulations are commented. The article aims to guide students and engineers in their choice of a constitutive law (yield locus, hardening law or plasticity approach) and data set used in the identification, without neglecting the other FE features, such as software, explicit or implicit strategy, element type and contact model.
The Benchmark organizers thank ESAFORM for the 10 000 epsilon Benchmark Grant as well as the opportunity to perform and diffuse such a state-of-the-art about deep drawing simulations. As director of the Fund for Scientific Research (F. R.S.-FNRS) Anne Marie Habraken thanks this institution of Wallonia-Brussels Federation for its support. UA and UCoimbra acknowledge the support of the projects POCI-01-0145-FEDER-032362 (PTDC/EME-ESP/32362/2017), POCI-01-0145-FEDER-030592 (PTDC/EME-EME/30592/2017), UIDB/00285/2020 and PTDC/EMEEME/31216/2017 (POCI-01-0145-FEDER-031216). Andre Pereira (UC) was funded under this later project. All projects were financed by the Operational Program for Competitiveness and Internationalization, in its FEDER/FNR component, and the Portuguese Foundation of Science and Technology (FCT), in its State Budget component (OE). Sara S. Miranda is grateful to FCT for the Doctoral grant SFRH/BD/146083/2019. Carlos Rojas-Ulloa now PhD s |
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ISSN: | 1960-6214 |
DOI: | 10.1007/s12289-022-01672-w |