Rama Rao Vemula

Lumped heat and mass transfer coefficient for simulation of a pressure swing adsorption process

ABSTRACT The practical implications of replacing various individual transport resistances such as gas-solid mass and heat transfer, and gas phase axial dispersions of mass and heat in a numerical model of a pressure swing adsorption (PSA) process by a single, empirical, lumped, effective mass transport coefficient were evaluated. A non-isothermal, adiabatic, four-step Skarstrom-like PSA process for production of pure helium from a binary helium-nitrogen mixture using 5A zeolite adsorbent was considered. It was found that the above-described model simplification was adequate to describe key process performances such as the bed size factor and the product recovery vis-a-vis a detailed model where the effects of all individual resistances were explicitly included.

Effect of adsorbent heterogeneity on performance of a PSA process for bulk gas separation: a parametric simulation

The effect of adsorbent heterogeneity on the performance of an adiabatic pressure swing adsorption (PSA) process for separation of bulk C2H4 from an inert gas (helium) using the BPL carbon as the adsorbent was numerically estimated employing a detailed mathematical model for the process. The heterogeneous Toth model was used to describe the equilibrium adsorption isotherms for C2H4 and a linear driving force model was used to describe the adsorbate mass transfer rate in the simulation. The variations in the isosteric heat of adsorption of C2H4 with adsorbate loading was included in the simulation. The study indicates that adsorbent heterogeneity negatively affects the key process performance variables by increasing the bed size factor and reducing the helium recovery. Actual performance data for a PSA process using a bench or pilot scale unit is required to reliably estimate the complexity introduced by adsorbent heterogeneity.

Multi-Model Predictive Control of a novel Rapid Pressure Swing Adsorption system

A Multi-Model Predictive Control (M-MPC) algorithm is developed for a novel Rapid Pressure Swing Adsorption (RSPSA) oxygen concentrator system. The RPSA uses a zeolite material to purify oxygen from ambient feed air, and was designed to produce ∼ 90% oxygen for medicinal therapies. A standard MPC algorithm was implement on the RPSA which rejects disturbances and improves set point tracking in the 90% operating range, but a RPSA can produce a wide range of oxygen purities. The proposed M-MPC algorithm uses a collection of linear models each of which corresponds to a different oxygen purity range. The linear models are identified around different operating points, and use Pseudo-Random Binary Signal (PRBS) simulation data in the identification process. With this improved control algorithm, the RPSA can produce a range of oxygen purities, and reject typical RPSA process disturbances. M-MPC switching rules, operating region boundary considerations and set point tracking cases are presented and discussed.