Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7019916 | Journal of Membrane Science | 2018 | 8 Pages |
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 48â¯m3/day NF pilot plant operating in cross-flow mode on water containing 8â¯mg/L total organic carbon (TOC) at fluxes ranging from 10 to 25â¯L/m2/h and velocities ranging from 0.25 to 1.0â¯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 110,000â¯m3/day NF plant. Simulations indicated that 1.5â¯m long modules operated in a double pass configuration removed 33% more NOM compared with 3.0â¯m long modules in a single pass. Moreover, the use of 1.5â¯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.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Filtration and Separation
Authors
Alexander Keucken, Xuefei Liu, Boyue Lian, Yuan Wang, Kenneth M. Persson, Greg Leslie,