A parametric study was carried out to improve the cyclic performance of the three-bed pressure−vacuum swing adsorption (PVSA) process, which consisted of two zeolite 10X beds for equilibrium separation and one carbon molecular sieve (CMS) bed for kinetic separation. Since the adsorption pressure and the feed flow rate of the zeolite 10X bed affected the concentration wave front of each component in the steps of removing impurities in the CMS bed, they played an important role in the final purity and recovery of the air separation. The pertinent step times in the nonisobaric steps, such as the pressurization and the pressure equalization steps of the zeolite 10X bed, contributed to the improvement of both O2 purity and recovery. In addition, the pressurization and the adsorption steps of the CMS bed served as key steps to purify the oxygen-rich feeds from the zeolite 10X bed. The increased pressurization step time leads to an increased adsorption pressure in the CMS bed, and the increased adsorption time implies the prolonged step of removing impurities in terms of kinetic separation in the CMS bed. Therefore, high O2 purity with high recovery and productivity could be obtained from the low quality product of the zeolite 10X bed by the increased step times in these two steps. However, increase of these step times might lead to a decrease in final O2 purity because the breakthrough of impurities occurred through the extended adsorption step time of the zeolite 10X bed. The effect of these step times on the final O2 purity from the CMS bed was, however, less sensitive than that from the zeolite 10X bed. Furthermore, the recovery and the productivity could be increased simultaneously with a decrease in purity in the variation of pressurization step time. Consequently, O2 of 97+% purity with high recovery of 75+% and productivity of 5.8 × 10-5 cm3/g·s, was produced at a well-tuned operating condition.

The application of control tools to complex flows frequently requires approximations, such as reduced-order models and/or simplified forcing assumptions, where these may be considered low rank or defined in terms of simplified statistics (e.g. white noise). In this work we propose a resolvent-based control methodology with causality imposed via a Wiener–Hopf formalism. Linear optimal causal estimation and control laws are obtained directly from full-rank, globally stable systems with arbitrary disturbance statistics, circumventing many drawbacks of alternative methods. We use efficient, matrix-free methods to construct the matrix Wiener–Hopf problem, and we implement a tailored method to solve the problem numerically. The approach naturally handles forcing terms with space–time colour; it allows inexpensive parametric investigation of sensor/actuator placement in scenarios where disturbances/targets are low rank; it is directly applicable to complex flows disturbed by high-rank forcing; it has lower cost in comparison to standard methods; it can be used in scenarios where an adjoint solver is not available; or it can be based exclusively on experimental data. The method is particularly well suited for the control of amplifier flows, for which optimal control approaches are typically robust. Validation of the approach is performed using the linearized Ginzburg–Landau equation. Flow over a backward-facing step perturbed by high-rank forcing is then considered. Sensor and actuator placement are investigated for this case, and we show that while the flow response downstream of the step is dominated by the Kelvin–Helmholtz mechanism, it has a complex, high-rank receptivity to incoming upstream perturbations, requiring multiple sensors for control.

No abstract

No abstract

No abstract

No abstract

No abstract

No abstract