A general predictive model for sweeping gas membrane distillation

Among the configurations of membrane distillation processes, sweeping gas membrane distillation (SGMD) remains one of the less studied. In spite of an increasing number of publications, generally the modeling of SGMD has been carried out by fitting heat and mass transfer coefficients and with the use of empirical correlations. In this work, a general predictive model based on computational fluid dynamics (CFD) is presented. This model allows simulating hollow fiber and flat sheet configurations under wide range of process conditions; with a minimum number of input data and without requiring empirical parameters or laboratory experiments. For this purpose, the momentum, mass and heat balances of the process are described by partial differential equations, algebraic and ordinary differential equations. The model has been validated with experimental results available in the literature. Indeed, the influence of operating conditions and membrane geometric characteristics on the process performance was investigated. The conducted studies prove that the proposed model would be potentially applied for the optimization of process conditions, design of membrane modules as well as for the further cost estimation of the process.