English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Fouling indices for evaluating fouling propensity of secondary effluents (SEF) as feed of ultrafiltration (UF) systems are important parameters for the design and operation of the UF process. However, limited fouling indices have been developed and applied for UF feedwater. This study (i) established a modified UF fouling index (MFI40) by raising operating pressure from 30 psi in a traditional MFI test to 40 psi. Standard deviation of MFI40 tests was lower than that of traditional MFI by 68.6%, indicating better stability and repeatability of MFI40. It (ii) investigated the combined effects of UF feedwater characteristics on MFI40. Biopolymers and turbidity played a dominant and secondary positive role in the MFI40, respectively. The effect of conductivity on MFI40 changed from positive to negative with a turbidity increase. It also (iii) validated the MFI40 in both laboratory- and pilot-scale UF membrane units, and UF fouling rates were linearly correlated to the MFI40 of their feeds, and (iv) explored the practical use of the MFI40. It was applied to determine the maximum allowable UF feedwater quality (MFI40max), which could be used to select an appropriate pre-treatment process. A fouling predicting model was established based on the feedwater MFI40 and the operating flux, with an average predicting error of 26.8%.

A modified fouling index (MFI40) and fouling predicting approach for ultrafiltration of secondary effluents