Comparison of Pressures Simulated Using Transient Analysis with Field Data from a Full-Scale Distribution System
Bibliographic record
Abstract
Negative pressures were measured in a full-scale distribution system following low pressure events at a water treatment plant. Transient analysis was used to model three downsurge events and compare the simulated pressure profiles with field measurement data. The objective of this work is to assess the source of uncertainty and variability associated with the estimation of intrusion volumes calculated by a transient analysis model. This assessment was conducted by comparing actual field pressure measurements and model outputs under various model settings (e.g., cavitation head, wave speed). For the three downsurge events, the modeled pressure profiles matched reasonably well with the measured pressures, as long as the pressures remained positive at a site. When the pressures reached negative values, the amplitude of the modeled pressures was larger than that of the recorded pressures. The difference between measured and modeled pressure is strongly related to a greater energy dissipation in the real distribution system, which is affected by the uncertain presence of air in pipes, the level of network skeletonization, and the allocation of demand. The estimation of intrusion volumes and risk for public health is directly affected by the pressure results obtained using transient analysis. Comparison to field data is therefore important to evaluate the accuracy of such a process.
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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".