Floc Size Distributions in Dissolved Air Flotation of Winnipeg Tap Water
Bibliographic record
Abstract
A bench-scale continuous flow dissolved air flotation (DAF) system was operated using Winnipeg tap water. Three different dosages of alum were applied: 41.7 mg l(-1), 25.5 mg l(-1) and 15.5 mg l(-1). Floc size distributions formed at different coagulant dosages were analyzed to identify characteristics of floc size distribution optimal for flotation. Alum dose of 25.5 mg l(-1) was found to be optimal for the bench scale DAF unit in this study. At this dosage, the DAF effluent achieved a turbidity of 0.25 NTU and color of 3.8 TCU, significantly lower than that for the tap water. The optimum floc size distribution at the dose of 25 mg l(-1) had the logarithmic mean size of 27 microm which was close to the size of air bubbles produced by the saturator in this study (30 microm). The results of this study suggest that the DAF treatment process is optimized when the logarithmic mean floc size and bubble size are equal.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".