Application of the International Water Association activated sludge models to describe aerobic sludge digestion
Bibliographic record
Abstract
Batch and semi-continuous flow aerobic digesters were used to stabilize thickened waste-activated sludge at different initial conditions and mean solids retention times. Under dynamic conditions, total suspended solids, volatile suspended solids (VSS) and total and particulate chemical oxygen demand (COD and PCOD) were monitored in the batch reactors and effluent from the semi-continuous flow reactors. Activated Sludge Model (ASM) no. 1 and ASM no. 3 were applied to measured data (calibration data set) to evaluate the consistency and performances of models at different flow regimes for digester COD and VSS modelling. The results indicated that both ASM1 and ASM3 predicted digester COD, VSS and PCOD concentrations well (R2, Ra2 > or = 0.93). Parameter estimation concluded that compared to ASM1, ASM3 parameters were more consistent across different batch and semi-continuous flow runs with different operating conditions. Model validation on a data set independent from the calibration data successfully predicted digester COD (R2 = 0.88) and VSS (R2 = 0.94) concentrations by ASM3, while ASM1 overestimated both reactor COD (R2 = 0.74) and VSS concentrations (R2 = 0.79) after 15 days of aerobic batch digestion.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".