Prediction of Leak Rates Through Porous Materials Using Analytical and Numerical Approaches

Characterizing the permeation performance of nano-porous material is an initial step towards predicting micro-flows and achieving acceptable designs in sealing and filtration applications. The present study deals with analytical, numerical, and experimental studies of gaseous leaks through soft packing materials. The paper presents a new analytical model to accurately predict and correlate gaseous leak rates through nano-porous materials. The analytical prediction is done with a model of fluid flow through capillaries of an exponentially varying section. Based on Navier-Stokes equations with different flow regimes, the analytical model is used to predict gaseous flow rates through soft packing materials. In addition, for comparison, computational fluid dynamic modelling using CFX software is used to estimate the flow rate of compression packing ring materials assuming the fluid flow to follow Darcy’s law. Helium gas is used as a reference gas to characterize the porosity parameters. The analytical and CFX numerical leak predictions are compared to leak rates measured experimentally using different gas types (Helium, Nitrogen, Air, and Argon) at different pressures and gland stresses. The packing material is subjected to different compression stress levels in order to change its porosity.