Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH4, CO, and H2 for chemical looping combustion

Ostace, Anca; Chen, Yu-Yen; Parker, Robert; Mebane, David S.; Okoli, Chinedu O.; Lee, Andrew; Tong, Andrew; Fan, Liang-Shih; Biegler, Lorenz T.; Burgard, Anthony P.; Miller, David C.; Bhattacharyya, Debangsu

doi:10.1016/j.ces.2022.117512

Title: Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH₄, CO, and H₂ for chemical looping combustion

Journal Article · 15 February 2022 · Chemical Engineering Science

DOI: https://doi.org/10.1016/j.ces.2022.117512 · OSTI ID:1880067

Ostace, Anca ^[1]; Chen, Yu-Yen ^[2]; Parker, Robert ^[3]; Mebane, David S. ^[1]; Okoli, Chinedu O. ^[4]; Lee, Andrew ^[4]; Tong, Andrew ^[2]; Fan, Liang-Shih ^[2]; Biegler, Lorenz T. ^[3]; Burgard, Anthony P. ^[4]; Miller, David C. ^[4]; Bhattacharyya, Debangsu ^[1]

West Virginia Univ., Morgantown, WV (United States)
The Ohio State Univ., Columbus, OH (United States)
Carnegie Mellon Univ., Pittsburgh, PA (United States)
National Energy Technology Lab. (NETL), Pittsburgh, PA (United States)

In this work, three kinetic models are developed and calibrated for the complete multi-step reduction of an Fe-based oxygen carrier (OC) particle with CH₄, CO, and H₂, using data from thermogravimetric analysis. The complete reduction rate profiles exhibit complex dynamics whose trajectory is significantly different depending on the reducing gas. A Bayesian model building and parameter estimation framework is applied for simultaneous parameter and model structure uncertainty quantification. The final models show excellent agreement between model predictions and calibration data, as well as new data not used for calibration (for the reduction of the OC with CH₄). Parameter uncertainty is quantified by determining joint posterior distribution, and model structure uncertainty is addressed by incorporating Gaussian process stochastic functions (represented by Bayesian smoothing splines) into the kinetic models. The final kinetic models with discrepancy functions are readily employable in equation-oriented simulation and optimization platforms.

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Research Organization:: National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy (FE)

Grant/Contract Number:: FE0025912

OSTI ID:: 1880067

Journal Information:: Chemical Engineering Science, Journal Name: Chemical Engineering Science Journal Issue: 28 Vol. 252; ISSN 0009-2509

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
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Title: Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH4, CO, and H2 for chemical looping combustion

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Title: Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH₄, CO, and H₂ for chemical looping combustion