8.1(Q1)
CiteScore
37
h-index

Computational Fluid Dynamics Guided Design of Antifouling Surface Patterned Membranes: A Review

Document Type : Review Article

Authors

1 Department of Chemical Engineering, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia

2 Laboratory of Polymer Science, Department of Chemical Engineering, Universitas of Syiah Kuala, Banda Aceh, Indonesia, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia

3 Graduate School of Environmental Management, Universitas Syiah Kuala, Jl. Tgk Chik Pante Kulu No. 5, Banda Aceh 23111, Darussalam, Indonesia

4 Department of Chemical Engineering, University of Brunei Darussalam, Jalan Tungku Link, Gadong BE1410, Brunei

5 Research Centre for Environmental and Natural Resources, Universitas Syiah Kuala, Jl. Hamzah Fansuri, No. 4, Darussalam, Banda Aceh 23111, Indonesia

6 Atsiri Research Center, Universitas Syiah Kuala, Jl. Syeh A. Rauf, Darussalam, Banda Aceh 23111, Indonesia

10.48309/jcr.2026.570067.1563
Abstract
Imposing feed turbulence flow in the membrane filtration system alleviates membrane fouling and enhances the overall membrane performance. Computational fluid dynamics (CFD) simulation provides easy access to visualizing the hydrodynamic performance of any design and technique employed for generating the membrane feed turbulence flow. Among several membrane feed turbulence flow generation techniques, membrane surface patterning and turbulence promoters are the most prominent. By patterning the surface of a membrane, the antifouling performance of the membrane improved by up to 58%. Moreover, by adjusting the operating velocity from 30 to 50 cm/s, the membrane hydraulic performance was enhanced by 20%. Furthermore, the antifouling performance of feed turbulence flow depends on operating parameters including the feed flow direction towards the turbulence generator. By reorienting the feed flow from parallel to perpendicular to the membrane surface patterns, the membrane lifespan improved by up to 14.4%. Therefore, for several decades many authors explored CFD to simulate the performance of the feed turbulence generation techniques prior to validation to save costs, time, and to obtain optimum design and operating parameters. Thus, many authors reviewed the CFD simulation results of the hydrodynamic performance of turbulence promoters while ignoring that of the surface patterning technique. This study aims to review the CFD simulation results of the hydrodynamic performance of membrane surface patterning by examining the patterns design and operating parameters performance and limitations as well as identifying the potential research avenues in the field.

Graphical Abstract

Computational Fluid Dynamics Guided Design of Antifouling Surface Patterned Membranes: A Review

Keywords

Subjects


Content

1. Introduction

2. Fundamentals of CFD Simulation for Surface Patterned Membranes

2.1 Governing equations and modeling assumptions

2.2 Boundary conditions and key hydrodynamic parameters

3. Hydrodynamic Performance of Surface Patterned Membranes: CFD Insights

3.1 Shear stress distribution and flow behavior over patterned membranes

3.2 Effect of operating conditions on hydrodynamic performance

3.3 Identification of fouling-prone regions

4. Effect of Surface Pattern Design Parameters on Antifouling Performance

4.1 Influence of pattern geometry

4.2 Effect of pattern dimensions and spacing

5. Influence of Foulant Characteristics and Operating Conditions

5.1 Effect of foulant size and physicochemical properties

5.2 Interaction between foulant characteristics and pattern scale

5.3 CFD-guided optimization under different operating conditions

6. Influence of Membrane Surface Patterning on the Filtration System Energy Consumption

7. Correlation between CFD Predictions and Experimental Validation

8. Performance of Surface Patterned Membranes in Various Membrane Processes

9. Conclusions and Future Perspectives

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Articles in Press, Accepted Manuscript
Available Online from 23 February 2026

  • Receive Date 01 January 2026
  • Revise Date 25 January 2026
  • Accept Date 17 February 2026