A one-dimensional two-phase approach to modeling graded density impact experiments
POSTER
Abstract
Here, we present a straightforward one-dimensional, two-phase methodology for modeling gas-gun-driven graded density impact (GDI) experiments. GDI experiments have the potential to probe a much larger range of thermodynamic space than single Hugoniot impact experiments. Previous modeling efforts (Aslam, McBride, Rai, Hooks, Stull and Jensen, Journal of Applied Physics, 2022) have demonstrated the potential of this approach for simulating atomically mixed GDI experiments. In that work, pressure and temperature equilibrium between the metallic phases was found to be a valid approximation, given the nanosecond timescales typical of modern diagnostics such as photon Doppler velocimetry (PDV). However, as length scales increase—such as in the bed-of-nails-type experiment (Goff, Lang, Markland, Aslam and Whitworth, AIP Conference Proceedings, vol. 2844, no. 1, 2023)—the timescales for thermal equilibrium lengthen, potentially invalidating previous assumptions. Additionally, prior work assumed that condensed-phase materials exhibited negligible strength within the studied range of impact velocities. In this study, we examine the implications of these modeling considerations and evaluate the two-phase modeling paradigm by validating it against experimental results.
*This work was supported by the US Department of Energy through the Los Alamos National Laboratory. Los Alamos National Laboratory is operated by Triad National Security, LLC, for the National Nuclear Security Administration of U.S Department of Energy (Contract No. 89233218CNA000001). This research was supported by the Advanced Simulation and Computing Program (ASC) and the Dynamic Materials Properties Campaign (C2) under DOE-NNSA. Work was performed, in part, at the Center for Integrated Nanotechnologies, an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science.
Presenters
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Tariq D Aslam
- Los Alamos National Laboratory (LANL)
- Los Alamos National Laboratory