Integrated uncertainty quantification and sensitivity analysis of single-component dynamic column breakthrough experiments

We have carried out the traditional analysis of a set of dynamic breakthrough experiments on the CO2/He system adsorbing onto activated carbon by fitting a 1D dynamic column breakthrough model to the transient experimental profiles. We have quantified the uncertainties in the fitted model parameters using the techniques of Bayesian inference, and have propagated these parametric uncertainties through the dynamic model to assess the robustness of the modelling. We have found significant uncertainties in the outlet mole fraction profile, internal temperature profile and internal adsorption profiles of approximately +/- 15%. To assess routes to reduce these uncertainties we have applied a global variance-based sensitivity analysis to the dynamic model using the Sobol method. We have found that approximately 70% of the observed variability in the modelling outputs can be attributed to uncertainties in the adsorption isotherm parameters that describe its temperature dependence. We also make various recommendations for practitioners, using the developed Bayesian statistical tools, regarding the choice of the isotherm model, the choice of the fitting data for the extraction of system specific parameters and the simplification of the wall energy balance.

Automated summary

In this study, a traditional analysis was carried out on a set of dynamic breakthrough experiments of the CO2/He system adsorbing onto activated carbon by fitting a 1D dynamic column breakthrough model. Uncertainties in the fitted model parameters were quantified using Bayesian inference techniques, and the robustness of the modeling was assessed by propagating these uncertainties through the dynamic model. It was found that uncertainties in the adsorption isotherm parameters were the main cause of variability in the modeling outputs, and several recommendations were made for practitioners using Bayesian statistical tools.