Water pipe renewal using a multiobjective optimization approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Water utilities ensure the delivery of water to consumers through a pressured network composed of several hydraulic components: reservoirs, pipes, valves, and pumps. A right maintenance policy that takes into consideration both technical and economic factors must be applied to enhance the hydraulic performance and reliability of the water network. With the help of a multiobjective approach based on a Pareto ranking and a modified genetic algorithm, we propose a decision support model that ensures the scheduling of pipe renewal according to available financial resources. The model is based on forecasting pipe failures and evaluating future maintenance costs. Two indexes are used to measure the hydraulic deficiency in the water network after a failure occurrence. They measure the undelivered water quantity and the number of unsupplied nodes when a considered pipe is unavailable during the peak demand period. Both indices permit classification of pipes and help identify critical ones. Feasible solutions are assessed according to economic and technical objectives. The model proposes solutions that enhance the reliability of a water distribution network and reduce failure occurrences, thus giving better satisfaction to consumers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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