CALPHAD Uncertainty Quantification and TDBX

CALPHAD uncertainty quantification (UQ) is the foundation of materials design with quantified confidence. We report a framework and software packages to enable CALPHAD UQ assessment and calculation using commercial CALPHAD software (Thermo-Calc). This Bayesian inference framework is coupled with a M...

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Vydáno v:	JOM (1989) Ročník 73; číslo 1; s. 116 - 125
Hlavní autoři:	Lin, Yu, Saboo, Abhinav, Frey, Ramón, Sorkin, Sam, Gong, Jiadong, Olson, Gregory B., Li, Meng, Niu, Changning
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.01.2021 Springer Nature B.V
Témata:	Algorithms Augmenting Physics-based Models in ICME with Machine Learning and Uncertainty Quantification Bayesian analysis Chemistry/Food Science Data points Design parameters Earth Sciences Engineering Enthalpy Environment Expected values Ground truth Hypothesis testing Markov analysis Markov chains Physics Software packages Solidification Source code Statistical inference Thermodynamics Uncertainty
ISSN:	1047-4838, 1543-1851
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Abstract	CALPHAD uncertainty quantification (UQ) is the foundation of materials design with quantified confidence. We report a framework and software packages to enable CALPHAD UQ assessment and calculation using commercial CALPHAD software (Thermo-Calc). This Bayesian inference framework is coupled with a Markov chain Monte Carlo algorithm to establish uncertainty traces with a given thermodynamic database file (TDB) and corresponding experimental data points. This general framework is demonstrated with the Ni–Cr binary system. The algorithm is firstly validated on synthetic data with known ground truth. Then it is applied to real experimental data to generate posterior traces. We develop a file format named TDBX, which provides a single source of truth by combining the original TDB content and the traces for each assessed Gibbs energy parameter. CALPHAD UQ calculations are performed based on the TDBX file, from which uncertainties for phase boundaries, enthalpy curves, and solidification range are collected as examples of basic design parameters. This TDBX file with corresponding scripts are made open-source. The combination of CALPHAD UQ assessments and calculations connected by TDBX supports uncertainty-assisted modeling, enabling the integrated application of modern design with uncertainty methodologies to computational materials design.
AbstractList	CALPHAD uncertainty quantification (UQ) is the foundation of materials design with quantified confidence. We report a framework and software packages to enable CALPHAD UQ assessment and calculation using commercial CALPHAD software (Thermo-Calc). This Bayesian inference framework is coupled with a Markov chain Monte Carlo algorithm to establish uncertainty traces with a given thermodynamic database file (TDB) and corresponding experimental data points. This general framework is demonstrated with the Ni–Cr binary system. The algorithm is firstly validated on synthetic data with known ground truth. Then it is applied to real experimental data to generate posterior traces. We develop a file format named TDBX, which provides a single source of truth by combining the original TDB content and the traces for each assessed Gibbs energy parameter. CALPHAD UQ calculations are performed based on the TDBX file, from which uncertainties for phase boundaries, enthalpy curves, and solidification range are collected as examples of basic design parameters. This TDBX file with corresponding scripts are made open-source. The combination of CALPHAD UQ assessments and calculations connected by TDBX supports uncertainty-assisted modeling, enabling the integrated application of modern design with uncertainty methodologies to computational materials design.
Author	Sorkin, Sam Gong, Jiadong Li, Meng Lin, Yu Olson, Gregory B. Niu, Changning Frey, Ramón Saboo, Abhinav
Author_xml	– sequence: 1 givenname: Yu surname: Lin fullname: Lin, Yu organization: QuesTek Innovations LLC – sequence: 2 givenname: Abhinav surname: Saboo fullname: Saboo, Abhinav organization: QuesTek Innovations LLC – sequence: 3 givenname: Ramón surname: Frey fullname: Frey, Ramón organization: QuesTek Innovations LLC, ETH Zurich – sequence: 4 givenname: Sam surname: Sorkin fullname: Sorkin, Sam organization: QuesTek Innovations LLC – sequence: 5 givenname: Jiadong surname: Gong fullname: Gong, Jiadong organization: QuesTek Innovations LLC – sequence: 6 givenname: Gregory B. surname: Olson fullname: Olson, Gregory B. organization: QuesTek Innovations LLC – sequence: 7 givenname: Meng surname: Li fullname: Li, Meng organization: Department of Statistics, Rice University – sequence: 8 givenname: Changning orcidid: 0000-0002-9864-0553 surname: Niu fullname: Niu, Changning email: cniu@questek.com organization: QuesTek Innovations LLC
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Snippet	CALPHAD uncertainty quantification (UQ) is the foundation of materials design with quantified confidence. We report a framework and software packages to enable...
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SubjectTerms	Algorithms Augmenting Physics-based Models in ICME with Machine Learning and Uncertainty Quantification Bayesian analysis Chemistry/Food Science Data points Design parameters Earth Sciences Engineering Enthalpy Environment Expected values Ground truth Hypothesis testing Markov analysis Markov chains Physics Software packages Solidification Source code Statistical inference Thermodynamics Uncertainty
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Title	CALPHAD Uncertainty Quantification and TDBX
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