The existence of trace amounts of moisture in process gases could adversely affect the fabrication of semiconductor devices. One important and practical challenge in transporting ultra-high-purity (UHP) gases from the point-of-storage (POS) to the point-of-use (POU) is the susceptibility of the gas distribution systems to molecular contaminants, especially moisture. In modern micro/nanoelectronic manufacturing plants, the moisture content at the POU has to satisfy very stringent specifications. Once a distribution system is contaminated, a significant amount of purge time is required to recover the system background due to the strong interactions between moisture molecules and the inner surfaces of the components in a gas distribution system. Because of the very high cost of UHP gases and factory downtime, it is critical for high-volume semiconductor manufacturers to reduce purge gas usage as well as purge time during the dry-down process. In the present work, a combination of experimental investigation and process simulations is used to compare the traditional steady-state purge (SSP), which typically is operated at constant pressure and flow rate, with the pressure-cycle purge (PCP) process in which the pressure and flow rate are cycled at a controlled frequency and interval. The results show that under certain conditions the new PCP process has significant advantages over the SSP process; for example, it reduces the purge time and gas usage when the gas purity at POU is the principal concern. This conclusion was confirmed by the experimental investigation on lab-scale gas distribution test beds as well as by the simulation of industrial scale systems. The process model developed and used in this work couples gas phase transport processes with surface adsorption/desorption and the purge schedule introduced by pressure variation in the system. This model is then validated using experimental results under various operating conditions. The process simulator is a useful tool for industrial applications in parametric studies and purge process optimization. The effect of key operational parameters, such as start time of PCP process as well as choice of PCP patterns in the PCP process, are presented.