07-10, 11:25–11:55 (US/Pacific), Room 316
The CALculation of PHAse Diagram (CALPHAD) method coupled with uncertainty quantification and propagation (UQ & UP) calculations is a viable tool to predict thermodynamic properties in a multicomponent region at different temperatures and compositions with a confidence interval. These types of calculations provide upper and lower bounds of thermochemical property predictions when choosing the chemistry of candidate salt mixtures and therefore are vital for molten salt reactor engineering applications. The present work will study NaCl-KCl-MgCl2 salt mixture because of its high interest for molten salt applications with the aid of the ESPEI and PyCalphad open-source codes for UQ and UP calculations.
Research of thermodynamic properties of molten salts is an area of scientific interest due to its potential impact in the fields of nuclear and solar energy. The high heat capacity coupled with low melting point and vapor pressures of molten salt systems (all thermodynamic properties) make them a candidate for thermal energy storage, heat transfer liquids and coolant applications. However, a disadvantage of using molten salts is how corrosive they are in addition to the various fission products it will be exposed to if the salt systems are used for molten salt nuclear reactors, which ultimately changes the salt’s thermodynamic properties. Since experimental thermodynamic measurements of these chemical systems are inherently expensive and difficult to perform, computational techniques are necessary to give reasonable predictions of the property changes of these salts as they are exposed to impurities at different temperatures. Hence, the molten salt community applies the CALculation of PHAse Diagram (CALPHAD) methodology for thermodynamic predictions of multicomponent systems under different temperature and chemical conditions. The CALPHAD method involves the parameterization of the Gibbs energy of all relevant phases in a chemical system as a function of composition, temperature, and pressure. One can parameterize these functions with optimization techniques from experimental or computational thermodynamic data available. Model selection for the liquid phase is imperative when trying to describe the thermodynamic behavior in molten salts due to consistent existence of short-range ordering. The community decided that the best model to describe the chemical interactions in these systems is the modified quasi-chemical model in the quadruplet approximation (MQMQA) when developing thermodynamic models for molten salt systems.
A consistent drawback of applying the CALPHAD method is that its predictions are usually deterministic and do not incorporate the uncertainty in the data that the models are being optimized to. Uncertainty quantification (UQ) of model parameters through Bayesian inference is a methodology that has become more popular thanks to the growth in computational power over the years. When these uncertainties are propagated (UP) through the model in question, the predictions and error bounds can be more efficiently used for engineering applications. To the best of the author’s knowledge, the Extensible Self-Optimizing Phase Equilibria Infrastructure (ESPEI) python library is the only tool that that does Bayesian inference through Markov Chain Monte Carlo (MCMC) calculations specifically for CALPHAD model development. The code uses the PyCalphad python library as its thermodynamic engine when running MCMC calculations.
In the present work the author will go over their experience implementing the MQMQA model into PyCalphad so that a UQ and UP study of molten salt thermodynamic models could be possible using ESPEI. New features added to ESPEI, such as the ability to run MCMC calculations to thermochemical data of user defined endmembers and partial pressure of species of the NaCl-KCl-MgCl2 system will also be covered.
Links:
https://pycalphad.org
https://espei.org
Postdoctoral fellow at the University of South Carolina. Research interest are thermodynamic modeling, density functional theory, calorimety ,and molten salts.