Use of chitosan in coagulation flocculation of raw water of Keddara and Beni Amrane dams
Bibliographic record
Abstract
The effectiveness of chitosan as a coagulant flocculant in surface water treatment has been studied. Tests were carried out in laboratory on treated and raw water. The treated water was mixed with high and low concentrations of bentonite to simulate turbid water. This treated water provides from water treatment plant of Algiers (Boudouaou site) which is supplied by both dams of Keddara and Beni Amrane. The raw water comes directly from these two dams. Chitosan with 85% degree of deacetylation and derived from crab chitin has been used. The performance of coagulation flocculation process has been assessed by measuring the supernatant turbidity for different doses of chitosan, initial turbidity, water quality and pH. The obtained results show that chitosan can be used in a large pH range. Chitosan is effective for coagulation of bentonite suspension and for raw water with high initial turbidity. Otherwise, chitosan is inefficient for raw water with very low initial turbidity. In this case, the use of chitosan as aid coagulant with aluminium sulfate (main coagulant) allows more effectiveness in removing turbidity.
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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 | 0.001 | 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) | 0.001 | 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".