Reliability analysis of water distribution networks using minimum cut set approach
Bibliographic record
Abstract
Canadian Water and Wastewater Association (CWWA) estimated the cost to replace 112,000 km of water mains in Canada to be 34 billion Canadian Dollars. Reliability analysis of water distribution networks (WDNs) is an important aspect in planning and operation of a WDN and hence plays an important role in the efficient use of allocated budget. In general, reliability analysis is classified into mechanical reliability and hydraulic reliability. Mechanical reliability is defined as the ability to function even when some components are out of service or there is any mechanical break. Hydraulic reliability is concerned with delivery of the specified quantity of water to a specific location at the required time under the desired pressure. This paper introduces a methodology for evaluating mechanical reliability of WDNs using the minimum cut set approach. The methodology involves the computation of mechanical reliability at the component (pipe, hydrant etc.), segment (collection of pipes and components) and network levels. An illustrative example is worked out to demonstrate the use of the developed methodology.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".