Dynamic compression experiments in condensed matter are of interest in part because they provide opportunities to examine material response under extreme conditions; however, the inference of material behavior from dynamic experiments is challenging in the presence of phase transitions exhibiting kinetic processes. Demonstrating an approach to quantitative interpretation of such dynamic experiments, here we present a Bayesian model calibration of strength and phase transformation parameters to data drawn from pulsed power and gas gun shot experiments. The posterior predictions of the Bayesian model capture the experimental measurements and account for the various uncertainties in the experimental configurations. This holistic approach to model calibration utilizing multiple types of experimental data identifies important cross correlations among kinetics, strength, and the phase boundary. Improved insight into potential sources of current model form error is provided by comparing the differences between calibrations against different subsets of the experimental data.
Schill, William J., et al. "Inference of strength and phase transition kinetics in dynamically-compressed tin." Journal of Applied Physics, vol. 133, no. 24, Jun. 2023. https://doi.org/10.1063/5.0150749
Schill, William J., Schmidt, K. L., Austin, Ryan A., Anderson, William W., Belof, Jonathan L., Brown, Justin L., & Barton, Nathan R. (2023). Inference of strength and phase transition kinetics in dynamically-compressed tin. Journal of Applied Physics, 133(24). https://doi.org/10.1063/5.0150749
Schill, William J., Schmidt, K. L., Austin, Ryan A., et al., "Inference of strength and phase transition kinetics in dynamically-compressed tin," Journal of Applied Physics 133, no. 24 (2023), https://doi.org/10.1063/5.0150749
@article{osti_2204462,
author = {Schill, William J. and Schmidt, K. L. and Austin, Ryan A. and Anderson, William W. and Belof, Jonathan L. and Brown, Justin L. and Barton, Nathan R.},
title = {Inference of strength and phase transition kinetics in dynamically-compressed tin},
annote = {Dynamic compression experiments in condensed matter are of interest in part because they provide opportunities to examine material response under extreme conditions; however, the inference of material behavior from dynamic experiments is challenging in the presence of phase transitions exhibiting kinetic processes. Demonstrating an approach to quantitative interpretation of such dynamic experiments, here we present a Bayesian model calibration of strength and phase transformation parameters to data drawn from pulsed power and gas gun shot experiments. The posterior predictions of the Bayesian model capture the experimental measurements and account for the various uncertainties in the experimental configurations. This holistic approach to model calibration utilizing multiple types of experimental data identifies important cross correlations among kinetics, strength, and the phase boundary. Improved insight into potential sources of current model form error is provided by comparing the differences between calibrations against different subsets of the experimental data.},
doi = {10.1063/5.0150749},
url = {https://www.osti.gov/biblio/2204462},
journal = {Journal of Applied Physics},
issn = {ISSN 0021-8979},
number = {24},
volume = {133},
place = {United States},
publisher = {American Institute of Physics (AIP)},
year = {2023},
month = {06}}
Barton, Nathan R.; Austin, Ryan A.; Brown, Justin L.
SHOCK COMPRESSION OF CONDENSED MATTER - 2019: Proceedings of the Conference of the American Physical Society Topical Group on Shock Compression of Condensed Matter, AIP Conference Proceedingshttps://doi.org/10.1063/12.0000914