Battle of the Water Networks District Metered Areas
Bibliographic record
Abstract
The Battle of Water Networks District Metered Areas (BWNDMA) was the latest of the Battle of Water Networks competition series held at the 18th Water Distribution Systems Analysis Conference (WDSA 2016) as part of ASCE’s Environmental and Water Resources Institute (EWRI) stand-alone conferences in Cartagena, Colombia in July 2016. In these competitions, the main objective was to address a specific problem related to water distribution systems (WDS) regarding how to optimize the design and operation of the system’s main components. This time, the competition was focused on the challenge of WDS network sectorization, that is, determination of the new district metered areas (DMAs) for an existing network. Design requirements involved constraints related to costs, pressure uniformity, and water quality. Changes in valve and pump operations were needed to supply demands at adequate pressures and acceptable water quality for the given supply scenarios: a wet season and a dry season with water shortages. Seven teams from different parts of the world participated in the BWNDMA and presented their solutions at a special session during the 18th WDSA. This article summarizes the BWNDMA teams’ approaches, outcomes, and learned lessons for solving the challenging stated problem. An analysis of some of the decisions that were taken is presented; for instance, some teams ignored the demand similarity criterion, the water age criterion, the pressure restrictions, or the constraints in the water rate that could be extracted from sources. The approaches developed in the BWNDMA represent the state-of-the-art with respect to the analysis of hydraulic conditions in DMAs of real-world water distribution networks for which it is mandatory to make efficient use of available water resources.
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.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".