Reduced Low–Pressure Membrane Fouling by Inline Coagulation Pretreatment for a Colored River Water
Bibliographic record
Abstract
Drinking water treatment (DWT) using low-pressure membranes (LPM) has become increasingly popular due to their many reported advantages compared to conventional technologies. Productivity decline due to fouling has prevented LPMs from becoming the technology of choice in DWT, however, coagulation pretreatment either with or without particle separation mitigates fouling phenomena. The effectiveness of coagulation/flocculation/sedimentation (CF-S), coagulation/flocculation/dissolved air flotation (CF-DAF), and inline coagulation (CF-IN) as technologies for pretreatment of feed water has rarely been investigated using the same water source. In this study, CF-S, CF-DAF, and CF-IN are directly compared as pretreatment of a tubular multi-channeled ultrafiltration (UF) membrane using the same highly colored river water. Three-day long filtration tests were performed using an automated bench-scale filtration apparatus with an inside-out configuration. Although CF-DAF had the greatest removal of dissolved organic matter (DOM) and hydrophobic organics, CF-S pretreatment resulted in a similar level of total fouling. Compared to CF-DAF and CF-S, CF-IN pretreatment resulted in lower fouling. The hydraulic and chemical reversibility of CF-IN fouling was seen to be strongly influenced by the feed water zeta potential, suggesting the importance of floc electrostatic and morphological characteristics on inline coagulation performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".