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Data from EXACT -Experiment and Analysis of Aluminum Cup Drawing Test, the first ESAFORM benchmark G. Vincze, A. Santos, M.C. Oliveira, A. B. Lopes, T. Kuwabara, A-M.Habraken, O. Cazacu, F. Barlat Thesedata are the basis of the Benchmark Exact, the first benchmark of the European Scientific Association for material FORMing – ESAFORM, and support the article entitled “Analysis of ESAFORM 2021 cup drawing benchmark of an Al alloy, critical factors for accuracy and efficiency of FE simulations”, published in the International Journal of Material Forming, Special Issue ESAFORM 25 YEARS ON,https://doi.org/10.1007/s12289-022-01672-w How to cite the data If you publish any work using thesedata, please cite theHabrakenet. al., (2022)articleaboveas well asthe dataset in the following recommended format: Vincze et al(2022);Dataof TheFirst ESAFORM benchmark EXACT,10.5281/zenodo.6874577 Benchmark motivation: Numerical simulations are powerful predictive tools for virtual forming process design and contribute to the significant reduction of trial-and-error time and cost in the development of new products. However, realistic numerical predictions are achieved only with a careful consideration of all the model input.In particular, a key ingredient is the choice of consistent constitutive models for the elasto-plastic behavior, identified using sound procedures from reliable and repeatable data sets. At present, the information provided in most benchmarks consists of the hardening law coefficients, along with limited experimental data such as, r-values, yield stresses and ultimate strengths extracted from uniaxial tension in certain loading directions, and possibly the coefficients of certain yield functions available in the material libraries of most commercial software. The identification of constitutive models is usually not included in the work requested to participants. Generally, there is no information provided concerning the experimental scatter because the “raw” data are not made available. While the behavior in tensile tests is essential, other loading paths (e.g. biaxial tension, uniaxial compression) may also be important for certain forming processes. Moreover, other types of data describing the initial material anisotropy and that induced by the deformation process, i.e. initial and post-test texture data, are rarely provided. For example, in a simple case of cup drawing, if the final cup test results are “blind data” describing the final geometry, the participants do not have the opportunity to analyze the quality/performance of their simulation results. In addition, if the tests are done in a single laboratory, the experimental scattering is limited to material variability but not to the characterization method nor to the raw data analysis procedure. This benchmark is a unique opportunity at providing an exhaustive analysis of the characterization and modeling of the elasto-plastic behavior of a sheet metal and its influence on the final virtual product. Specifically, the goal of the EXACT data is to generate in-depth discussions regarding the initial and final states of the material, methods of characterization, modelingand earing prediction in cup drawing. File organization Please, read the file “Identification of the files and folders”&nbsp

In this study, numerical simulations of deep drawing of a cylindrical cup are considered. The utilized blank materials are all virtual, they are assumed to be isotropic with strength differential effect i. e. with different yield stress in tension and in compression. The aim is to understand the impact of the strength differential effect on the final cup geometry. The numerical model uses the yield criterion proposed by Cazacu et al. (2006) which allows describing the strength differential effect based solely on the ratio between the yield stresses in tension and in compression. Moreover, it reduces to the von Mises criterion for materials without the strength differential effect, enabling a direct comparison. Numerical simulations are performed considering different values for the ratio between the yield stresses in tension and in compression, in order to evaluate its impact on the thickness distribution and cup height. The analysis of the stress and strain paths, for material points initially located in the flange, is also performed. This enables correlating the predicted thickness distributions with the plastic strain ratios that can be obtained analytically for biaxial loadings, using the yield function and the normality rule.