Application of a multiphase CFD modelling approach to improve ozone residual monitoring and tracer testing strategies for full-scale drinking water ozone disinfection processes
Bibliographic record
Abstract
A multiphase computational fluid dynamics (CFD) model has been developed to address the major components of ozone disinfection processes: contactor hydraulics, ozone decay and mass transfer. The model was applied to simulate ozone profiles and tracer residence time distributions of ozone contactors at the DesBaillets Water Treatment Plant (WTP) in Montreal, Canada. The modelling results showed that ozone residuals at the cross-section of the outlet of each chamber in the ozone contactors were very sensitive to monitoring point selection. The optimum locations were significantly affected by multiple operational parameters including water/gas flow rates, ozone dosage and baffling conditions. The modelling results suggested that multiple monitoring points should be used to obtain more representative ozone residuals. The CFD model was also used to study the factors affecting tracer residence time distribution (RTD). It was observed that the method of tracer injection could slightly affect tracer RTD results while sampling location had a significant influence on tracer RTD prediction or measurement. Therefore, it is suggested that multiple sampling points should be employed during tracer tests if possible.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".