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Presents benchmark data for calibrating constitutive models in dual-phase steel, highlighting implications for material behavior analysis.
An accurate and diverse set of experimental data is essential for characterizing material behavior across different length scales and for calibrating the respective constitutive models. An independent validation experiment, the MUC-Test, is presented to validate such constitutive models. The benchmark dataset provides raw experimental data that serves as the basis for calibrating constitutive models of varying complexity. The material investigated is a dual-phase steel (DP800HHE). The conducted microscale experiments investigate the material properties at the grain level. These experiments include nanoindentation, electron backscatter diffraction, and in-situ synchrotron measurements to capture the material’s microstructural behavior. These data serve as the basis for generating representative volume elements and for phase-specific calibration of the crystal plasticity models. On the macroscale, a wide range of experiments has been conducted, including tensile, tension-compression, plane-strain, shear, layer-compression, and cyclic tensile tests. This data can be used to calibrate flow curves and yield locus curves. Part I of this benchmark paper series details the experiments and provides data for calibrating both microscopic and macroscopic models. It also introduces the benchmark problem based on the MUC-Test for validation of these models. Dataset https://zenodo.org/records/18431261
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Maier et al. (2026) studied this question.
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