Liquid Distribution and its Effect on the Organic Removal in a Trickle Bed Bioreactor
Bibliographic record
Abstract
Propylene glycol methyl ether was removed from wastewater in a trickling bed bioreactor under different liquid distribution conditions. A 0.3 m diameter column filled with two heights of 0.7 m and 1.4 m with 2 cm plastic spheres were used. The wastewater flow rate varied from 0.184 to .0918 kg/m₂.s. The effect of the initial liquid distribution was examined using two types of liquid distributors: a multipoint liquid distributor and a central single point liquid distributor. Over 96 hours of treatment period, the BOD₅ was reduced by 85% and 65% under the most uniform liquid distribution condition and the poor liquid distribution condition, respectively, achieved in this study. Increasing the liquid flow rate from 0.184 to 0.198 kg/m₂.s, it increased the dynamic liquid holdup by 53% and the apparent BOD₅ removal rate constant by 23% at 1.4 m bed height using the multipoint liquid distributor. Moreover, with the use of the multipoint liquid distributor, the apparent reaction when the liquid flow rate was increased from 0.184kg/m₂.s to 0.918 kg/m₂.s. In addition, it was found that the effect of an increase in the bed height on the percentage BOD₅ removal was not significant when initial liquid distribution was uniform. Under the uniform initial condition, only 4% increase in the percentage BOD₅ removal was observed when the bed height increased from 0.7 to 1.4 m whereas when the initial distribution was extremely non-uniform, the percentage of BOD₅ removal was increased by 20% with increasing bed height. The local distribution of the BOD₅ removal was not uniform across the bed cross-section and it was affected by the liquid flow distribution across the bed cross-section.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".