Effect of media volume on mixing of biological aerated filters
Bibliographic record
Abstract
Effect of reduced media volume on the mixing of biological aerated filters (BAF) was quantitatively determined. The degree of mixing was evaluated based on Reynolds numbers (Re) while the nonideality of the flow was assessed from information of residence time distribution. At HRTs of 1411, 1111, 781 and 581 min and their, respectively, approximate OLRs of 2, 3, 4, and 6 kg COD·m –3 ·d –1 , the Re in the partial-bed were 40300, 36100, 25500, and 40400, respectively, whilst those of the full-bed were 19500, 20500, 11700, and 26400. Porosity of the BAF is a bed characteristic resulting from the balance between the effect of biomass accumulation due to growth and biomass loss due to shear stress, arising from increased organic loadings, gas flow, and increased upflow velocity. The number of tanks, calculated from the residence time distribution data, is either 1 or 2 (rounded up to an integer). This indicates the occurrence of a completely mixed pattern inside both reactors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".