Modeling Chlorine Residual in a Ground Water Supply Tank for a Small Community in Cold Conditions
Bibliographic record
Abstract
A small municipality in cold region with relatively low consumption results in a longer residence time of treated water in a storage tank. Field measurements of chlorine residual over a summer identified low chlorine residual while in a winter period the water was beginning to freeze. A few remedial geometrical alteration options were proposed, including a plug-flow configuration in the tank. However, the effectiveness of each option cannot be verified easily because there are many confounding factors. CFD (computational fluid dynamics) software ANSYS CFX is utilized to model conditions of flow, temperature, and chlorine residual in the tank under three geometries. For the no-alteration option and stepped spillway configuration, the model showed that there were pockets of stagnant water with low chlorine residual during the summer. Flow channels were created to achieve a plug-flow option and the residual was found consistent. The latter geometric option is considered the best for freeze avoidance and maintaining optimum chlorine concentration. One of the drawbacks of the CFD modeling was the excessive duration of computational time running on regular desktop computers.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".