Application of carbon dioxide stripping for struvite crystallization — I: Development of a carbon dioxide stripper model to predict CO<sub>2</sub> removal and pH changes
Bibliographic record
Abstract
This research investigated the feasibility of stripping CO2 from the digester supernatant to raise the pH, thereby reducing the caustic chemical usage. In this study, a cascade CO2 stripper was first designed and tested, with three different synthetic solutions in a struvite recovery, crystal reactor: (1) tap water saturated with CO2, (2) NaHCO3 solution saturated with CO2, and (3) NaHCO3 + NH4Cl solution saturated with CO2. It was found that the removal efficiency of the CO2 stripper was dependant on several parameters, such as the characteristics of the influent, including total alkalinity, temperature, and initial concentration of dissolved CO2 gas, influent flow rate, effluent recycle rate, aeration rate, and baffle numbers in the stripper. Based on the performance of the stripper on the three synthetic solutions, a CO2 stripping model was developed using these parameters. This model was subsequently tested in a pilot-scale facility, to predict the amount of CO2 removal possible.
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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 | 0.000 | 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) | 0.001 | 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".