A numerical study of a two property catalyst/sorbent pellet design for the sorption-enhanced steam-methane reforming process: Modeling complexity and parameter sensitivity study

摘要

In this study the performance of a combined catalyst/sorbent pellet design for the sorption-enhanced steam-methane reforming process has been investigated. Different mathematical model complexities have been studied and parameter sensitivity analyses have been performed. The mathematical pellet model formulated for the process describes the evolution of species mole fractions, pressure, total concentration, temperature, fluxes, and convection within the voids of the porous pellet. The effective diffusivites are described according to the parallel pore and random pore models, and the mass diffusion fluxes are described according to the Maxwell-Stefan and dusty gas models. Moreover, models proposed in the literature for void fraction changes, product layer diffusion resistance, and degeneration due to multiple carbonation/calcination cycles are employed. The simulated pellet effectiveness factor is a convenient parameter frequently used in modeling and simulations of chemical reactors indicating the relative importance of diffusion and reaction limitations. Thus, in this study, the effectiveness factor behavior due to different mathematical modeling assumptions and model parameter values is elucidated. The combined pellet performance is promising compared to the conventional two-pellet design. For further improved modeling and simulations of the pellet, the characterizing of the pore size distribution is important because of the Knudsen diffusion mechanism. Moreover, the reduction in void fraction with the CaO conversion, product layer growth, and degeneration due to multiple cycles are all important effects in the SE-SMR process because these mechanisms influence on the cycle life time, reaction rate, and capture capacity. For industrial applications, the pellet is only of interest in the capture kinetic controlling step, i.e. before the process becomes controlled by the product layer diffusion resistance.