6. Conclusions
In this work, a new Equilibrium Theory PSA cycle solver (Esim) has been introduced. Esim allows the estimation of the equilibrium limiting performance for a given adsorption process and the identification of a set of high separation efficiency configurations by just using the isotherm equilibrium function as input data. The simplifications associated with the Equilibrium Theory and the fact of considering axial dispersion to be negligible convert the mass and the energy balances in an adsorption column into a system of hyperbolic equations. A conservative variable change is defined enabling the use of the Godunov numerical flux. This removes the need of imposing a numerical entropy condition or of calculating the characteristics in each cell. Esim results have been validated by comparison against simulations using gPROMS in which simulations were undertaken by using micropore equilibrium and macropore LDF model. The assumption of the Equilibrium Theory has been emulated by employing very large values for the kLDF constant and very small values for the axial dispersion coefficients. It can also be observed that Esim manages to properly track shocks and smooth transitions since the first order momentfor the breakthrough curves generated by Esim are equalto the ones corresponding to the curves produced by the gPROMS based solver; showing the correct implementation of the novel tool. The convergence to CSS for the new solver has been demonstrated by simulating a non-isothermal non trace binary adsorption equilibrium based system under conditions of interest in CO2 post combustion capture technology. Cyclic pressure, CO2 mole fraction and temperature evolution have been compared against the ones producedby the gPROMS basedcode andconfirmthe correctimplementation ofthe new solver to the simulation offull PSAcycles. This comparison also shows that the ET solver requires fewer cycles to reach CSS in comparison with full governing equations thus it indicates that ET simulator can in principle be used for the efficient determination of the limiting Pareto fronts for the optimization of equilibrium based PSA separations.