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Meeting 2019 TMS Annual Meeting & Exhibition
Symposium Computational Approaches for Big Data, Artificial Intelligence and Uncertainty Quantification in Computational Materials Science
Presentation Title Evaluation and Representation of Uncertainty in Thermodynamic Phase Diagrams
Author(s) Noah H. Paulson, Brandon J Bocklund, Zi-Kui Liu, Marius Stan
On-Site Speaker (Planned) Noah H. Paulson
Abstract Scope Thermodynamic phase diagrams are a critical component in materials discovery and design efforts. Unfortunately, due to the scarcity of experimental and computational data, these diagrams may be misleading in some regions of composition, temperature and pressure space – especially for systems with many components. In recent years, this challenge has driven the development of uncertainty quantification approaches for the calculation of thermodynamic phase diagrams. These approaches are still in their infancy, and thus far little attention has been paid to the representation of the uncertainties. In this work, we present several promising methods to effectively represent uncertainties in thermodynamic phase diagrams with multiple components. These techniques produce uncertainty intervals for phase boundaries, probabilities of phase stability and probability distributions for the phase compositions. The results include representation of uncertainty for example binary and ternary systems.
Proceedings Inclusion? Planned: Supplemental Proceedings volume

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Bayesian CALPHAD: From Uncertainty Quantification to Model Fusion
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