A Multi-phase Equation of State for Magnesium with Uncertainty Quantification

There are several sources of uncertainty involved in the calibration of an equation of state (EOS) model: calibration data will in general have some error, and there might be degeneracy where multiple parameters sets might produce essentially identical output. Uncertainty quantification allows for the determination of an ensemble of statistically weighted parameter sets that are consistent with the calibration data. These distributions can be used to determine a range of outcomes in downstream applications of the EOS model. In this talk, we describe a Bayesian approach to uncertainty quantification for a multi-phase EOS for the HCP, BCC, and liquid phases of Magnesium over a large range of temperatures and densities.