Can steady-state momentum equations be used in modelling pressurization of adsorption beds?

Modelling of adsorption technologies for controlling indoor air quality

Technologies for control of indoor air quality are very important to ensure that health and comfort conditions are attained in closed environments. The indoor air quality market is fertile ground for adsorption technologies, both at larger industrial scale and for residential uses. The common strategy to design adsorption technologies considers constant inlet conditions, while for most indoor air control applications, the inlet conditions will change because of the partial removal of the contaminant. This work presents a generic modelling approach, where the adsorption technology is coupled with the indoor environment to be controlled. This approach enables a tailored and more accurate process design and additionally, it can also assist in the physical location of the removal unit and sensors to control its operation. Two different examples of application of this methodology are provided: control of CO2 in tightly closed environments and "peak shaving" of water vapor in bathrooms.

Dynamic simulation of high-purity twin-bed N2-PSA plants

At present, nitrogen production from air by pressure swing adsorption (PSA) is simulated almost exclusively at low product purity levels (< 99% N2). However, with increasing global demand for highly purified gases provided by energy-efficient separation processes the requirement for either extensive experimental research in the high-purity range or predictive computer simulations arises. This paper presents a mathematical model of a twin-bed PSA plant equipped with a carbon molecular sieve (Shirasagi MSC CT-350) for the generation of high-purity nitrogen (99.9–99.999% N2). The model is implemented in the process simulator Aspen Adsorption™. The influence of operating conditions as well as the cycle organisation on the process performance is validated, especially the influence of pressure, temperature, half-cycle time, purge flow rate, and cutting time. The precision of the performance prediction by numerical simulations is critically discussed. Based on the new insights efficiency improvement strategies with a focus on reduced energy consumption are introduced and discussed by means of radar charts.