|About this Abstract
||2020 TMS Annual Meeting & Exhibition
||Algorithm Development in Materials Science and Engineering
||L-14: Uncertainty Propagation in CalPhaD Calculations
||Nicholas Ury, Richard Otis, Vilupanur A. Ravi
|On-Site Speaker (Planned)
Calculation of Phase Diagrams (CalPhad) has proven to be a useful computational approach in reducing the time and resources required for the development of alloys. The next step to advancing this methodology is to account for the inconsistency or lack of data when assessing thermodynamic systems. As proof of concept, a generalized framework made in Python was implemented to perform equilibrium calculations and handle model uncertainty. This framework includes the storage and handling of elemental and phase data, and the implementation of Newton’s method to perform Gibbs free energy minimization to create step and phase diagrams and determine the confidence intervals of the results. The Mg-Si system was assessed using a Bayesian approach as a case study for this framework.
||Planned: Supplemental Proceedings volume