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

Author:

Habraken Anne MarieORCID,Aksen Toros Arda,Alves José L.,Amaral Rui L.,Betaieb Ehssen,Chandola Nitin,Corallo Luca,Cruz Daniel J.,Duchêne Laurent,Engel Bernd,Esener Emre,Firat Mehmet,Frohn-Sörensen Peter,Galán-López Jesús,Ghiabakloo Hadi,Kestens Leo A. I.,Lian Junhe,Lingam Rakesh,Liu Wencheng,Ma Jun,Menezes Luís F.,Nguyen-Minh Tuan,Miranda Sara S.,Neto Diogo M.,Pereira André F. G.,Prates Pedro A.,Reuter Jonas,Revil-Baudard Benoit,Rojas-Ulloa Carlos,Sener Bora,Shen Fuhui,Van Bael Albert,Verleysen Patricia,Barlat Frederic,Cazacu Oana,Kuwabara Toshihiko,Lopes Augusto,Oliveira Marta C.,Santos Abel D.,Vincze Gabriela

Abstract

AbstractThis 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.

Publisher

Springer Science and Business Media LLC

Subject

General Materials Science

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