Compartmental anaerobic baffled reactor kinetic model for treatment of dilute aircraft deicing fluid
Bibliographic record
Abstract
A four-compartment, anaerobic baffled reactor (ABR) incorporating granular sludge biomass (GSB) was operated at different hydraulic retention times (HRTs) in the range of 3 to 24 hours using dilute aircraft deicing fluid (ADF) with different chemical oxygen demand (COD) concentrations (300, 500 and 750 mg/L) at organic loading rates (OLRs) between 0.3 and 6 kg COD/m3/d. A total of 15 experimental runs conducted in continuous mode achieved COD removal efficiencies ranging from 61 to 93%. Better COD removal efficiencies were achieved at the highest concentration of ADF and HRTs over 6 hrs. For a shorter HRT of 3 hrs, removal efficiency was still acceptable, but additional treatment would be necessary to satisfy effluent discharge standards. Methane production was close to the theoretical value of 0.39 L CH4/g COD removed at 35°C. Low biomass yield and low endogenous decay coefficient were observed. Application of a first-order kinetic empirical compartment model was developed to describe performance of the GSB-ABR. The model predicted response (COD removal efficiency) was not in good agreement with the observed experimental results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".