Unraveling the Implications of Finite Specimen Size on the Interpretation of Dynamic Experiments for Polycrystalline Metals through Numerical Simulations

Normal and Pressure-shear plate impact (NPI and PSPI) experiments are popular techniques for studying the mean-field macroscopic behavior of polycrystalline metals under high rate loading. However, since both configurations rely upon geometry for imposing high rates, these experiments often involve a limited specimen size. Moreover, because of inherent heterogeneities present within polycrystalline metals, it is difficult to ascertain when the size of the sample is large enough for making representative inferences from free surface point velocity measurements. In the present study, we quantify the expected measurement variability on observable point measurements in NPI and PSPI experiments by carrying out direct numerical simulations (DNS) of statistically representative polycrystalline microstructures subjected to dynamic compression and compression-shear loading. In particular, we consider the role of specific material heterogeneities (e.g. grain size, morphology, the grain-to-grain difference in crystal orientation) on dispersion in the normal and transverse particle velocity records and on local fluctuations in key state variables (e.g. stress, temperature, accumulated plastic strain) by incorporating these effects directly into a synthetic microstructure geometry and crystalline description of a represetative FCC metal. Our analysis demonstrates that the grain size correlates directly with the variation in point measurements, showing a decrease in variation to zero (i.e. point velocity measurements approach a mean-field value) with decreasing grain size. The reasoning for the scatter in particle velocity due to the heterogeneous microstructure is demonstrated to be dependent on the mechanisms for accommodating deformation and on the interaction of flow occurring at various length scales within the microstrcuture. Lastly, we summarize the results into a framework for assessing the required number of grains per characteristic length for minimizing scatter in NPI/PSPI.