Optimizing Membrane Distillation Performance through Flow Channel Modification with Baffles: Experimental and Computational Study
Abstract
:1. Introduction
2. Experimental Section
2.1. Membrane Distillation Module
2.2. Porous Membranes
2.3. Preparation of the Baffles in the Flow Channels
2.4. AGMD Tests
3. CFD Simulations
3.1. Geometry Model
3.2. Mesh Generation
3.3. Assumptions and Governing Equations
3.4. Boundary Conditions
3.5. Algorithm and Turbulence Model
4. Results and Discussion
4.1. Flow Disturbance near Membrane Surface by Baffles in the Flow Channel
4.2. Influence of Multiple Baffles in the Flow Channel
4.3. Influence of Baffle Geometry
4.3.1. Velocity in the Flow Channel
4.3.2. Effect on the Wall Shear Stress of Membrane Surface
4.4. Effect on Pressure Drop in the Flow
4.4.1. Influence of the Size of the Gap between the Baffle and the Membrane
4.4.2. Influence of Baffle Geometric Structure
4.5. MD Performance
4.5.1. Influence of Baffle Height on Transmembrane Flux
4.5.2. Influence of Baffle Geometric Structure on Transmembrane Flux
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Nomenclature
A | wetted surface area of the computational domain (m2) |
cp | specific heat (J/kg/K) |
dh | hydraulic diameter (m) |
g | gravitational acceleration (m/s2) |
h1 | height of the baffle (m) |
h2 | distance between the baffle and the membrane surface (m) |
H | height of the computational domain (m) |
J | transmembrane flux (kg/m2/h) |
k | thermal conductivity (W/m/K) |
L | length of computational domain (m) |
P | pressure (Pa) |
Tf | feed temperature (°C) |
uav | mean velocity along the flow direction (m/s) |
ui | inlet velocity of the CFD simulation (m/s) |
u, v, w | velocity component along x, y, z (m/s) |
V | volume of computational domain (m3) |
W | width of computational domain (m) |
x, y, z | cartesian coordinates (m) |
Re | Reynolds number |
Greek letters | |
μ | dynamic viscosity (Pa·s) |
ν | kinematic viscosity (m2/s) |
ρ | density (kg/m3) |
ΔP | pressure drop along the flow direction (kPa) |
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Case | Number of Cells | ui (m/s) | Re | ΔP/L (Pa/m) |
---|---|---|---|---|
Case 1 | 280,000 | 0.1 | 2392 | 77 |
Case 2 | 560,000 | 0.1 | 2392 | 78 |
Case 3 | 1,740,000 | 0.1 | 2392 | 78 |
Fluid | ρ (kg/m3) | cp (J/(kg·K)) | k (W/(m·K)) | μ (Pa·s) |
---|---|---|---|---|
Pure water | 998.2 | 4182.1 | 0.613 | 1.003 × 10−3 |
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Zhang, Y.; Mu, X.; Sun, J.; Guo, F. Optimizing Membrane Distillation Performance through Flow Channel Modification with Baffles: Experimental and Computational Study. Separations 2023, 10, 485. https://doi.org/10.3390/separations10090485
Zhang Y, Mu X, Sun J, Guo F. Optimizing Membrane Distillation Performance through Flow Channel Modification with Baffles: Experimental and Computational Study. Separations. 2023; 10(9):485. https://doi.org/10.3390/separations10090485
Chicago/Turabian StyleZhang, Yaoling, Xingsen Mu, Jiaqi Sun, and Fei Guo. 2023. "Optimizing Membrane Distillation Performance through Flow Channel Modification with Baffles: Experimental and Computational Study" Separations 10, no. 9: 485. https://doi.org/10.3390/separations10090485
APA StyleZhang, Y., Mu, X., Sun, J., & Guo, F. (2023). Optimizing Membrane Distillation Performance through Flow Channel Modification with Baffles: Experimental and Computational Study. Separations, 10(9), 485. https://doi.org/10.3390/separations10090485