ESPEI for efficient thermodynamic database development, modification, and uncertainty quantification: application to Cu-Mg [article]

Brandon Bocklund, Richard Otis, Aleksei Egorov, Abdulmonem Obaied, Irina Roslyakova, Zi-Kui Liu
2019 arXiv   pre-print
The software package ESPEI has been developed for efficient evaluation of thermodynamic model parameters within the CALPHAD method. ESPEI uses a linear fitting strategy to parameterize Gibbs energy functions of single phases based on their thermochemical data and refine the model parameters using phase equilibrium data through Bayesian optimization within a Markov Chain Monte Carlo machine learning approach. In this paper, the methodologies employed in ESPEI are discussed in detail and
more » ... ted for the Cu-Mg system down to 0 K using unary descriptions based on segmented regression. The model parameter uncertainties are quantified and propagated to the Gibbs energy functions.
arXiv:1902.01269v1 fatcat:2niz4ncizzd2zh4hmqzgy55jzi