Application of an equation-oriented framework to formulate and estimate parameters of chemical looping reaction models

Accurate, predictive reaction models are critical for the design and optimization of chemical looping combustion (CLC) reactors. The formulation and estimation of kinetic parameters for these reaction models using a first-principles equation-oriented (EO) approach is particularly beneficial as large amounts of experimental data spanning process-relevant conditions can be used to estimate parameters in a computationally tractable way. This work demonstrates the application of a novel EO framework to develop reduction reaction kinetic models of an iron-based CLC oxygen carrier (OC). An optimization problem is formulated to estimate kinetic parameters that provide the best fit to the experimental data. The model predicts the state of the OC with mean square error values of 2.5%-4.4% across the full range of validation data, including multiple reduction cycles.