4.5 Article

Dynamic Modeling of Fouling in Reverse Osmosis Membranes

期刊

MEMBRANES
卷 11, 期 5, 页码 -

出版社

MDPI
DOI: 10.3390/membranes11050349

关键词

RO membrane; numerical model; OpenFoam

资金

  1. National Alliance for Water Innovation (NAWI) [1242861-12-SDGBM]
  2. National Science Foundation (NSF) [1533874]
  3. Div Of Chem, Bioeng, Env, & Transp Sys
  4. Directorate For Engineering [1533874] Funding Source: National Science Foundation

向作者/读者索取更多资源

Understanding the coupling between membrane shape, local flow field, and fouling is crucial for the comprehensive design and optimization of reverse osmosis systems. Current studies focus on simplified steady-state models, overlooking the dynamic coupling between fluid flow, solute transport, and foulant accumulation.
During reverse osmosis (RO) membrane filtration, performance is dramatically affected by fouling, which concurrently decreases the permeate flux while increasing the energy required to operate the system. Comprehensive design and optimization of RO systems are best served by an understanding of the coupling between membrane shape, local flow field, and fouling; however, current studies focus exclusively on simplified steady-state models that ignore the dynamic coupling between fluid flow, solute transport, and foulant accumulation. We developed a customized solver (SUMs: Stanford University Membrane Solver) under the open source finite volume simulator OpenFOAM to solve transient Navier-Stokes, advection-diffusion, and adsorption-desorption equations for foulant accumulation. We implemented two permeate flux reduction models at the membrane boundary: the resistance-in-series (RIS) model and the effective-pressure-drop (EPD) model. The two models were validated against filtration experiments by comparing the equilibrium flux, pressure drop, and fouling pattern on the membrane. Both models not only predict macroscopic quantities (e.g., permeate flux and pressure drop) but also the fouling pattern developed on the membrane, with a good match with experimental results. Furthermore, the models capture the temporal evolution of foulant accumulation and its coupling with flux reduction.

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