Analysis of ESAFORM 2021 cup drawing benchmark of an Al alloy, critical factors for accuracy and efficiency of FE simulations

Journal Article (2022)
Author(s)

Anne Marie Habraken (Katholieke Universiteit Leuven)

Toros Arda Aksen (University of Sakarya)

José L. Alves (University of Minho)

Rui L. Amaral (Universidade do Porto)

Nitin Chandola (University of Florida)

Luca Corallo (Universiteit Gent)

Bernd Engel (University of Siegen)

Emre Esener (Bilecik Seyh Edebali University)

Jesús Galán-López (TU Delft - Team Erik Offerman)

Leo A.I. Kestens (Universiteit Gent)

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DOI related publication
https://doi.org/10.1007/s12289-022-01672-w Final published version
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Publication Year
2022
Language
English
Issue number
5
Volume number
15
Article number
61
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367
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Abstract

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.