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10:19
Three-Dimensionally Printed Microfluidic Cross-flow System for Ultrafiltration/Nanofiltration Membrane Performance Testing
Published on: February 13, 2016
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Predicting the performance of pressure filtration processes by coupling computational fluid dynamics and discrete
Boyang Li1, Kerianne M Dobosz1, Haitao Zhang2
1Department of Chemical Engineering and the Institute for Applied Life Sciences, University of Massachusetts, Amherst, MA 01003, USA.
Chemical Engineering Science
|October 4, 2019
Summary
This study developed a computational fluid dynamics and discrete element method model to understand pressure filtration. The model predicts how particle size, fines, liquid viscosity, and cake compression impact filtration performance.
Area of Science:
- Chemical Engineering
- Particle Technology
- Fluid Dynamics
Background:
- Pressure filtration is crucial in various industrial processes.
- Understanding factors influencing filtration performance is essential for optimization.
- Existing models may not fully capture complex particle-fluid interactions.
Purpose of the Study:
- To develop and validate a coupled computational fluid dynamics (CFD) and discrete element method (DEM) model.
- To investigate the impact of various parameters on pressure filtration performance.
- To provide a fundamental understanding of filtration mechanisms.
Main Methods:
- Coupled CFD-DEM modeling approach.
- Validation using experimental data from filtering glass beads and deionized water.
- Numerical experiments exploring particle, liquid, and operating condition effects.
Main Results:
- Filtrate flow rate is significantly influenced by mean particle size and the presence of fines.
- Liquid viscosity and particle deformation (cake compression) are key factors affecting filtration.
- The CFD-DEM model accurately predicted filtration performance.
Conclusions:
- CFD-DEM modeling is a powerful tool for analyzing cake filtration.
- The model aids in predicting and optimizing filtration performance.
- This approach enhances the fundamental understanding of filtration processes.
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