Investigation of the Impact Response of Bi‐Continuous Nanoporous Solids via the Material Point Method: Verification Against Molecular Dynamics Predictions

ABSTRACT Molecular dynamics (MD) and the material point method (MPM) are both particle methods in spatial discretization. Molecular dynamics is a discrete particle method that is widely applied to predict fundamental physical properties and dynamic materials behaviors at nanoscale. The MPM is a continuum‐based particle method that was proposed about three decades ago to simulate large‐deformation problems involving multiphase interaction and failure evolution beyond the nanoscale. However, it is still a challenging task to validate MD responses against the experimental data due to the spatial limitation in impact and/or shock tests. The objective of this investigation is therefore to compare the MPM and MD solutions for the impact responses of porous solids at nanoscale. Since the governing equations for MD and explicit MPM are similar in temporal domain with different spatial discretization schemes, the MPM solutions could be verified against the MD ones, and the MD solutions might then be indirectly validated against the MPM ones as validated beyond the nanoscale. Since both MD forcing functions and MPM constitutive modeling are well‐formulated for metallic solids, we report a comprehensive comparative study of porous and non‐porous gold cubic targets impacted by full density non‐porous gold cubic flyers using the MPM and MD, respectively. The overall deformation patterns and particle‐velocity histories are demonstrated and analyzed, as obtained with the two particle methods. It appears that the MD and MPM solutions are consistent in capturing the physical responses, which shows the potential of using the MPM for multiscale simulations of extreme events involving porous solids, such as underground penetration and space exploration. In addition, MD solutions might be indirectly validated against the MPM ones for evaluating geological responses to extreme loadings, which provides an alternative route for multiscale verification and validation.