Cross Correlation of Demands in Water Distribution Network Design
Why this work is in the frame
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Bibliographic record
Abstract
The aim of water distribution design is to size and configure a system so that it meets existing and future demands while providing pressures above a minimum level for service and fire protection. Extended period simulation (EPS) is used in design to determine network pressures under varied diurnal demand patterns. In EPS, diurnal demands are almost invariably assumed to change in unison, or in statistical terms, to be strongly correlated in space. This paper first tests this common assumption by investigating the extent to which cross correlation in demand affects the mean and standard deviation of pressure heads in water networks, and then investigates how cross correlated demands can influence capital costs in network design. Preliminary findings from two examples indicate that the standard deviation of pressure head and capital costs can be sensitive to the level of cross correlation between nodal demands. Thus a realistic assessment of cross correlation in demand can lead to a more economical design.
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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 | 0.001 | 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 it