Impact of Coagulation Agents on the Performance of Flotation Unit for the Treatment of Industrial Waste Water
Bibliographic record
Abstract
The performance of a batch laboratory scale induced air flotation (IAF) unit in controlling fat, oil, and Grease (FOG) and five days biological oxygen demand (BOD5) in effluents of a meats processing & packing industry, was tested using two types of coagulation agents (Alum and Bentonite clay) and three air flow rates. Prior to coagulation, air flow rates of 3 and 5 l/min were the best for having FOG removal efficiencies of 60% and 62%, respectively. Significant improvements in these were measured (94.5% and 96.2% for the mentioned air flow rates respectively) after the addition of 0.5 g/l Alum, while extra 0.2 g/l bentonite clay as coagulation aid had achieved efficiencies of 96.3% and 99.3% for these air flow rates respectively. Also, the addition of 0.5 g/l Alum had improved the BOD5 reduction efficiency from 54% to 65% and from 63% to 71%, for air flow rates of 3 l/min and 5 l/min respectively, as compared with no Alum cases. Higher BOD5 removal efficiencies of 73% and 78% were measured for the two air flow rates respectively, by aiding the coagulation with 0.2 g/l bentonite clay. At least 25% saving of flotation time was proved by the addition of bentonite clay to achieve final results, similar to these with Alum only for both FOG and BOD5, which in turn may save part of the operational costs.Author would like to acknowledge the logistic and technical support of the Ins. of International Education IIE, Scholars Rescue Fund SRF and Russ College of Eng. / OU.
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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 | 0.000 | 0.001 |
| 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 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".