Simulation and Optimization of Pressure Swing Adsorption Systems Using Reduced-Order Modeling

Over the past three decades, pressure swing adsorption (PSA) processes have been widely used as energy-efficient gas separation techniques, especially for high purity hydrogen purification from refinery gases. Models for PSA processes are multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep fronts moving with time. As a result, the optimization of such systems represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. This study develops a reduced-order model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. The proposed method...