PERFORMANCE OF A HIGH‐RATE/HIGH‐SHEAR ACTIVATED SLUDGE BIOREACTOR TREATING BIODEGRADABLE WASTEWATER
Bibliographic record
Abstract
A high-rate activated sludge (HRAS) bioreactor with high shear venturi aeration was operated in the laboratory at various organic loading rates to evaluate chemical oxygen demand (COD) removal efficiency and sludge production. Organic loading rates two orders of magnitude higher than conventional activated sludge loading were investigated in the modified HRAS reactor for a period of 41 weeks. Filtered COD removal efficiency varied from 81 to 92 % for organic loading rates of 3 to 85 kg COD m(-3) d(-1). Observed sludge yield was determined to be 0.10-0.25 g TSS produced g(-1) COD removed, under hydraulic and solids retention times (SRTs) approaching less than two hours and two days, respectively. Observed sludge yield actually declined as loading increased and SRT decreased. It was concluded that high-shear forces created in the reactor due to intense aeration at high volumetric organic loading rates increased substrate utilization rate, improved filtered COD removal efficiency, and kept sludge yields relatively low (despite the very low operating SRTs).
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".