Design and optimization of pressure swing adsorption systems with parallel implementation

Over the past three decades, pressure swing adsorption (PSA) processes have gained increasing commercial acceptance as an energy efficient separation technique. These processes are distributed in nature, with spatial and temporal variations and are mathematically represented by partial differential equations (PDEs). After a start-up time, the system reaches cyclic steady state (CSS), at which the conditions in each bed at the start and end of each cycle are identical, revealing normal production. We implement a Newton-based approach with accurate sensitivities to directly determine cyclic steady states with design constraints. We also design optimal PSA processes by means of state-of-the-art SQP-based optimization algorithms. The simultaneous tailored approach can incorporate large-scale and detailed adsorption models and is more robust and efficient than competing optimization methodologies. In order to improve the computational efficiency, we parallelize sensitivity calculation and achieve a close-to-linear speed up rate. Applications of several non-isothermal industrial O2 VSA and H2 PSA processes are presented.