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  • Thermodynamic modeling and uncertainty quantification of CO
    Thermodynamic modeling and uncertainty quantification of CO2-loaded aqueous MEA solutions Joshua C Morgan a , Anderson Soares Chinen a , Benjamin Omell b , Debangsu Bhattacharyya a, Charles Tong c , David C Miller b Show more Add to Mendeley
  • High-Throughput Thermodynamic Modeling and Uncertainty Quantification . . .
    High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME Published: 23 March 2017 Volume 69, pages 886–892, (2017) Cite this article Download PDF Save article Richard A Otis Zi-Kui Liu
  • Uncertainty Quantification for Thermodynamic Simulations with High . . .
    The assessment of the future thermodynamics performance of a retrofitted heat and power production unit is prone to many uncertainties due to the large number of parameters involved in the modeling of all its components To carry out uncertainty quantification analysis, alternatives to the traditional Monte Carlo method must be used due to the large stochastic dimension of the problem In this
  • Quantified Uncertainty in Thermodynamic Modeling for Materials Design
    R A Otis and Z -K Liu, “High-Throughput Thermodynamic Modeling and Uncertainty Quantification for IME,” JOM, vol 69, no 5, pp 886–892, May 2017 [6] D V Malakhov, “ onfidence intervals of calculated phase boundaries,” Calphad, vol 21, no 3, pp 391–400, 1997 [7] E
  • Thermodynamic modeling with uncertainty quantification using the . . .
    Thermodynamic modeling with uncertainty quantification using the modified quasichemical model in quadruplet approximation: Implementation into PyCalphad and ESPEI Calphad ( IF 1 9 ) Pub Date : 2023-09-19 , DOI: 10 1016 j calphad 2023 102618 Jorge Paz Soldan Palma 1 , Rushi Gong 1 , Brandon J Bocklund 1, 2 , Richard Otis 3 , Max Poschmann 4 , Markus Piro 4 , Shayan Shahbazi 5 , Tatiana G
  • ESPEI Documentation – ESPEI
    Otis, Richard, and Zi-Kui Liu 2017 “High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME ” Jom 69 (5): 886–92 https: doi org doi:10 1007 s11837-017-2318-6 Shang, Shun Li, Yi Wang, and Zi Kui Liu 2010 “ESPEI: Extensible, Self-Optimizing Phase Equilibrium Infrastructure for Magnesium Alloys ”
  • Uncertainty reduction and quantification in computational . . .
    View PDF View article View in Scopus Google Scholar [43] R A Otis, Z -K Liu High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME JOM , 69 (2017), pp 886 - 892, 10 1007 s11837-017-2318-6 View in Scopus Google Scholar [44]
  • Quantified Uncertainty in Thermodynamic Modeling for Materials Design
    [5] R A Otis and Z -K Liu, “High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME,” JOM, vol 69, no 5, pp 886–892, May 2017 [6] D V Malakhov, “Confidence intervals of calculated phase boundaries,” Calphad, vol 21, no 3, pp 391–400, 1997
  • CALPHAD Uncertainty Quantification and TDBX - Springer
    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
  • High-Throughput Thermodynamic Modeling and Uncertainty Quantification . . .
    Request PDF | High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME | One foundational component of the integrated computational materials engineering (ICME) and





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