Modeling Tool for Air Stripping and Carbon Adsorbers to Remove Trace Organic Contaminants
Bibliographic record
Abstract
Removal of trace organic contaminants from aqueous solutions by air strippers (AS) and fixed bed carbon adsorper (FBCA) has been studied.A trace organic treatment tool has been developed to capture and adapt the best-known design procedures and to have all regulated trace organics, their physical and chemical properties, and the corresponding maximum concentration limits.Outputs include the selected treatment method and the final design parameters of air stripper or fixed bed carbon adsorber.Running the model shows that water temperature is a very important factor in designing AS and FBA.It also shows that the best air pressure values, in AS, ranged between 150 -200 ATM.And there is a big relation between the column size and the packing material.On the other hand, it shows that FBA diameter has an obvious effect on the needed volume, and the best values ranged between 1.2 -2.5 m.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".