Quantification of the Relative Importance of Factors Contributing to Intrusion in a Distribution System Using a Full Factorial Design
Bibliographic record
Abstract
Transient analysis of a pump trip event was conducted on a full-scale distribution system (∼16,000 nodes) equipped with high speed pressure transient data loggers at the outlet of the water treatment plant (WTP) and at several distribution system (DS) sites. A calibrated transient model was used to perform intrusion volume computations considering two possible intrusion pathways: leakage orifices and submerged air vacuum valves (AVVs). For this pump trip event, a full 3-level 4-factor factorial design (34–0) with 82 runs was completed to understand the relative impact of the following factors on the total intrusion volume: (1) the external head of untreated water on leakage orifices, (2) the external head of untreated water on the outlet orifice of submerged AVVs, (3) the leakage rate (which translates into orifice size), and, (4) the diameter of AVVs' outlet orifice. Although some of these factors may be highly uncertain, fieldwork (including installation of piezometers and visits of air valve vaults) is currently being conducted, and realistic values were assigned to these factors. The analysis showed that the factors and interactions associated with AVVs had a significant effect on the total intrusion volume. The importance of the external head on AVVs' orifice on the total intrusion volume was highlighted in a plot of marginal means. When intrusion through both pathways occurs concurrently, the interactions between these intrusion flows influence the total intrusion volume. The latter can even decrease when the external head on leakage orifices increases creating surge dampening effects large enough to significantly reduce intrusion through submerged AVVs.
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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 | 0.000 | 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 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".