(341b) Design of Experiments and Uncertainty Quantification for Adsorptive CO2 Capture Systems
In this work, we perform design of experiments for a fixed-bed adsorptive CO2 capture process to characterize transport properties of these MOFs. A partial differential algebraic equation model couples mass and momentum transport phenomena with adsorption equilibria (isotherms) and kinetics. Specially, we perform least squares parameter estimation to infer a lumped transport rate constant and discern between possible isotherm models from both breakthrough and thermogravimetric analysis data. Optimization problems are implemented in the open-source Pyomo modeling environment and solved using Ipopt. Partial differential equations are discretized in both time and space resulting in over 20,000 sparse algebraic constraints for parameter estimation and design of experiments optimization problems. Directly exploiting the exact first a second derivatives, the so-called âglass boxâ approach, yields computationally efficient solutions in less than a minute. The ultimate goal of design of experiments is to reduce uncertainty in the fundamental adsorptive models which are inputs for detailed process design and techno economic evaluation of novel CO2 capture technologies such as rotary bed contactor designs.
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