Optimization of Pressure Swing Adsorption via a Trust-Region Filter Algorithm and Equilibrium Theory

Abstract Optimization of pressure swing adsorption (PSA) remains a challenging task, as these are periodic dynamic systems governed by nonlinear PDE systems. This study develops an optimization strategy that incorporates reduced PSA models and also samples information from a high-fidelity ’truth’ model. The reduced model is based on equilibrium theory and can be applied to optimize a large variety of cyclic adsorption processes. The optimization is performed via a trust-region filter (TRF) method. The TRF method uses reduced models to minimize the information required from the high-fidelity adsorption model during mathematical optimization. Moreover, this method guarantees convergence to the optimum of the high-fidelity model. This approach is applied to optimize a 4 column pressure swing adsorption process, modeled by partial differential algebraic equations, for the separation of a CO 2 /CH 4 mixture. The results show that the reduced model significantly reduces the computational time of the method’s trust-region step compared to previous studies.