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Flow-Induced Clogging in Microfiltration Membranes: Numerical Modeling and Parametric Study

DOI: 10.4236/jwarp.2023.1512037, PP. 692-705

Keywords: Microfiltration Membrane, Parametric Study, Computational Fluid Dynamic (CFD), Discrete Element Method (DEM), CFD-DEM Modeling, Membrane Clogging, Pore Geometry, Numerical Modeling, Cake Layer, Clogging Indicator

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Abstract:

Microfiltration membrane technology has been widely used in various industries for solid-liquid separation. However, pore clogging remains a persistent challenge. This study employs (CFD) and discrete element method (DEM) models to enhance our understanding of microfiltration membrane clogging. The models were validated by comparing them to experimental data, demonstrating reasonable consistency. Subsequently, a parametric study was conducted on a cross-flow model, exploring the influence of key parameters on clogging. Findings show that clogging is a complex phenomenon affected by various factors. The mean inlet velocity and transmembrane flux were found to directly impact clogging, while the confinement ratio and cosine of the membrane pore entrance angle had an inverse relationship with it. Two clog types were identified: internal (inside the pore) and external (arching at the pore entrance), with the confinement ratio determining the type. This study introduced a dimensionless number as a quantitative clogging indicator based on transmembrane flux, Reynolds number, filtration time, entrance angle cosine, and confinement ratio. While this hypothesis held true in simulations, future studies should explore variations in clogging indicators, and improved modeling of clogging characteristics. Calibration between numerical and physical times and consideration of particle volume fraction will enhance understanding.

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