Characterisation of retention tank water quality: particle settling velocity distribution and retention time
Bibliographic record
Abstract
Retention tanks (RTs) are commonly used to reduce combined sewer overflows, management of which is an important way of reducing the impacts of urban development on receiving waters. However, overflow characteristics and the processes affecting them are not yet fully understood. In a context of integrated urban wastewater systems, the management of RTs is mainly done to satisfy hydraulic constraints even if the idea behind such structures is to limit the discharge of pollutants to the environment. This study reports new insights in the settling processes and the pollutant behaviour occurring in an off-line RT. The authors first focus on the total suspended solids (TSS) and the total chemical oxygen demand (CODt) dynamics at the inlet and the outlet of a RT. Secondly, they focus on the possible relationship between the variation of the particle settling velocity distribution of particles and the TSS concentration dynamics. Finally, analyses of the TSS and CODt concentration evolution during tank emptying give information on the interaction between wastewater retention time and the settling performance.
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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 | 0.010 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".