Semi-parametric Modeling of the Equation of State of Dissociating Materials

Music City Center 

Modeling the equation of state (EOS) of chemically dissociating materials at extreme temperature and density conditions is necessary to predict their thermodynamic behavior in simulations and experiments. However, this task is challenging due to sparse experimental and theoretical data needed to calibrate the parameters of the equation of state model, such as the latent molar mass surface. In this work, we adopt semi-parametric models for the latent molar mass of the material and its corresponding free energy surface. Our method employs basis representations of the latent surfaces with regularization to address challenges in basis selection and prevent overfitting. We show with an example involving carbon dioxide that our method improves model fit over simpler representations of the molar mass surface while preserving low computational overhead. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-872125

Semi-Parametric

Uncertainty Quantification

Inverse Problem

Material Science 

Section on Statistics in Defense and National Security