Ultrafiltration Fouling: Impact of Backwash Frequency and Air Sparging
Bibliographic record
Abstract
A bench-scale study was performed to optimize backwash frequency and air sparging conditions during ultrafiltration (UF) for drinking water treatment in order to minimize hydraulically irreversible fouling as well as operating and maintenance costs. Surface shear stress representing different air sparging conditions (continuous coarse bubble, intermittent coarse bubble, and large pulse bubble) was applied in combination with various backwash frequencies (0.5, 2, and 6 hours) during UF of two natural surface waters. Results indicated that air sparging during permeation with intermittent coarse or large pulse bubbles significantly reduced the rate of irreversible fouling. This allowed for longer permeation times (up to 6 hours) between backwashing, when compared to a baseline condition which assumed a 0.5 h-backwash frequency with no air sparging during permeation. As a result, operation and maintenance cost savings estimated at > $350,000/year for a 29 MLD membrane train could be realized. This study demonstrates that optimized air sparging could serve as a cost-effective UF fouling control strategy for drinking water production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".