A New Metric for Assessing Resilience of Water Distribution Networks
Why this work is in the frame
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Bibliographic record
Abstract
Water distribution networks (WDNs) face various types of hazards during their extended life. Ensuring proper functioning of WDNs has always been a major concern for utility managers because of their impact on public health and safety. Resilience is an emerging concept that aims at maintaining functionality of the WDNs. Most of the previously developed resilience frameworks employed simulation methods to assess resilience of the WDNs, focusing only on the specific aspects of resilience. There is a need to develop a holistic approach to evaluate the resilience of WDNs considering various dimensions of resilience. This paper presents a new multi-attribute resilience metric based on the robustness and redundancy of the WDNs, which can be used to achieve the purpose. The developed metric is used to evaluate the resilience of a WDN in the city of London, Ontario. An optimization framework for enhancing the current resilience level is also presented. Resilience of the network is found to increase around 20% with a $500,000 investment. A hazard scenario is then analyzed to illustrate the practicality of using this metric in selecting effective restoration strategies. The proposed metric can be utilized by water agencies to evaluate and enhance the resilience of WDNs, as well as to optimize the recovery process after disruptive events.
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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 | 0.000 | 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 it