CFD-based genetic programming model for liquid entry pressure estimation of hydrophobic membranes

摘要

Wetting phenomenon inside the pore is a significant obstacle hindering membrane distillation (MD) from being fully industrialized. Herein, a new equation is provided for the users, using the combination of computational fluid dynamics (CFD) and genetic programming (GP) tools for estimation of liquid entry pressure (LEP), a parameter closely related to pore wetting. CFD was applied to model the wetting process inside the pore during the gradual increase in feed pressure at different scenarios in which contact angle, pore radius and membrane thickness were changed. Afterwards, GP as an intelligent method was employed to provide a computer program estimating LEP in the whole ranges in which CFD modeling was carried out. Moreover, validation was done using experimental data and then the influence of effective parameters on LEP was studied. This work provides an explicit formula for estimation of LEP in a closer agreement with the experimental data in comparison to the Young-Laplace equation. In addition, the influence of the membrane thickness was added to the equation, providing a more realistic formula for LEP estimation.