Abstract
In regions with limited potable water availability, membrane desalination is being employed to filter water using a pressure-driven approach. Because of the high energy consumption required to produce the pressure differential needed for this method, researchers have been trying different geometric designs of spacer filaments to enhance the amount of permeate flux in terms of energy utilization. The purpose of spacer filaments is to support membranes structurally and induce turbulent mixing in spiral wound membrane desalination. In this paper, the improvement of mass transfer in desalination driven by reverse osmosis has been studied using Computational Fluid Dynamics (CFD) with the introduction of spiral wound membranes that are lined with spacer filaments in a zig-zag formation having alternating diameters for strands. The fluid flow characteristics for a 2-dimensional geometric model were resolved using the open-source program OpenFOAM by changing the Reynolds number to just before the inception of instabilities. Ratios of alternate strand diameters were also varied between one and two. Based on a detailed analysis of velocity contours, pressure distribution, wall shear stresses, and steady-state vortex systems, the research findings offer guidance for employing alternating strand design in zig-zag formation for optimum mass transfer and minimal pressure drop when accounting for concentration polarization.
MeSH 主题词
Biofouling
Drinking Water
Membranes, Artificial
Osmosis
Water Purification/methods
化学物质
Drinking Water
Membranes, Artificial
作者与单位
共 7 位作者,点击展开单位 / ORCID
Shoukat Gohar
School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan. | Unit A2, Nutgrove Office Park, Rathfarnham, Gavin and Doherty Geosolutions (GDG), D14 X627, Dublin, Ireland.
Idrees Hassaan
School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan. | Artificial Intelligence for Mechanical Systems (AIMS) Lab, School of Interdisciplinary and Engineering Sciences (SINES), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Sajid Muhammad
School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
[email protected]. | Artificial Intelligence for Mechanical Systems (AIMS) Lab, School of Interdisciplinary and Engineering Sciences (SINES), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
[email protected].
Ali Sara
School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan. | Artificial Intelligence for Mechanical Systems (AIMS) Lab, School of Interdisciplinary and Engineering Sciences (SINES), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan. | Human-Robot Interaction (HRI) Lab, School of Interdisciplinary Engineering & Science (SINES), National University of Sciences and Technology (NUST), 44000, Islamabad, Pakistan.
Ayaz Yasar
School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan. | National Center of Artificial Intelligence (NCAI), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Nawaz Raheel
Staffordshire University, Stoke-On-Trent, ST4 2DE, UK.
Ansari A R
Department of Mathematics and Natural Sciences, Centre for Applied Mathematics and Bioinformatics, Gulf University for Science and Technology, 73F2+GV4, Mubarak Al-Abdullah, Kuwait.