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 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 | 0.000 |
| 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 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".