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Simulation of NOM removal by capillary NF: A numerical method for full-scale plant design.

Authors :
Keucken, Alexander
Liu, Xuefei
Lian, Boyue
Wang, Yuan
Persson, Kenneth M.
Leslie, Greg
Source :
Journal of Membrane Science. Jun2018, Vol. 555, p229-236. 8p.
Publication Year :
2018

Abstract

The removal of natural organic matter (NOM) from boreal lake water by a novel capillary nanofiltration (NF) membrane was predicted using a computational fluid dynamics (CFD) modelling approach. The 2-dimensional axis-symmetric model was based on a 48 m 3 /day NF pilot plant operating in cross-flow mode on water containing 8 mg/L total organic carbon (TOC) at fluxes ranging from 10 to 25 L/m 2 /h and velocities ranging from 0.25 to 1.0 m/s. A “mass jump” source code developed using the solution diffusion model was used to simulate water flux and variations in NOM content as a function of axial and radial position in the capillary fibres. The model was validated within 3% inaccuracy using pilot data for filtrate TOC and UV254 absorbance and longitudinal pressure drop. The model was subsequently used to compare the effect of module length and number of stages on the design performance of a 110,000 m 3 /day NF plant. Simulations indicated that 1.5 m long modules operated in a double pass configuration removed 33% more NOM compared with 3.0 m long modules in a single pass. Moreover, the use of 1.5 m modules in the full-scale plant configured in a 10:5:3:2 four stage array achieved greater NOM removal than a 10:5:3 three stage at the same plant water recovery (90.5%) using lower recycle rates and lower net energy consumption. The paper demonstrates that the combination of experimental and numerical methods can be an effective tool for the design of nanofiltration plants for enhanced NOM removal. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03767388
Volume :
555
Database :
Academic Search Index
Journal :
Journal of Membrane Science
Publication Type :
Academic Journal
Accession number :
129206067
Full Text :
https://doi.org/10.1016/j.memsci.2018.03.016