Impact of incomplete mixing in the prediction of chlorine residuals in municipal water distribution systems
Bibliographic record
Abstract
This paper investigates the mixing phenomena in pipe junctions in water distribution systems. Network simulation models frequently assume that mixing at pipe junctions is complete and instantaneous. In the present study, a series of experiments using tee and cross junctions with varying inflows and free chlorine concentrations were carried out in the Hydraulic Laboratory of the Institute of Engineering at the National Autonomous University of Mexico. Numerical simulations of these experiments were also performed using EPANET-BAM. Experimental results from this study showed that mixing is not complete in most of the cases; intersecting flows tend to bifurcate rather than mix completely. Numerical simulations indicated good agreement between calculated and measured values. The model was also tested using data from the water distribution system of Duberger-Les Saules, in Quebec City, Canada. A larger vulnerability zone was identified due to the impact of the incomplete mixing at the cross junction in the prediction of chlorine residual in a water distribution network.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".