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Leaks and Water Use Representation in Water Distribution System Models: Finding a Working Equivalence

2009· article· en· W2099469522 on OpenAlexafffund
Andrew F. Colombo, Bryan Karney

Bibliographic record

VenueJournal of Hydraulic Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLeakEquivalence (formal languages)Leakage (economics)Representation (politics)Pipe network analysisEnvironmental scienceComputer scienceDemand managementMathematical optimizationPetroleum engineeringEnvironmental engineeringEngineeringMathematicsEconomicsMechanics

Abstract

fetched live from OpenAlex

The challenge of water demand representation in water distribution systems is revisited with a brief exploration of the relationship between a pressure-dependent leak and a fixed legitimate demand. Specifically, the idea that a leak can be modeled as an increment to legitimate demand in such a way that it entails an equivalent impact on both water loss and energy consumption is explored. Conversely, the representation of demands as leaks is briefly considered. The effectiveness of pressure reduction and demand curtailment as leak management schemes are compared for a single pipe system. The influence of pipe resistance on this relationship is assessed, suggesting that such schemes are more important in rougher pipes. In general, the notion that leakage and demand analysis/management are two sides of the same coin, and that pressure/demand management is essentially conservation, is put forth.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.008
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.023
GPT teacher head0.207
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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".

Quick stats

Citations7
Published2009
Admission routes2
Has abstractyes

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