Optimization of High Rate DAF Process for Removal of Algae in WaterTreatment Plant
Bibliographic record
Abstract
In recent years there have been large increases in the hydraulic loading rates used to design dissolved air flotation (DAF) facilities for drinking water applications.High rate DAF processes are now available at loading rates of 20 to 40 m3/m2•h.This research evaluated dissolved air flotation as a separation method for algae and organic compounds from water treatment plants.During the service period of 2016. 5. to 2017.6., DAF pilot plants (500 m3/day) process has shown a constantly sound performance for the treatment of raw water, yielding a significantly low level of turbidity (DAF treated water, 0.21 ~ 1.56 NTU).As a result of analyzing the algae cell counts in the influent source, it was expressed at 100-120 cells/mL.In DAF treated water, the removal efficient of algae cell counts was found to be up to 90%.The stable turbidity and algae removal were confirmed by operating the high rate DAF process under the condition of the surface loading rate of 30 m3/m2•hr.The number of algae in the DAF treated water has been analyzed to be less than 100 cells/mL.These results indicated that the DAF process is effective in removing the algae.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".