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Energy and Costs of Leaky Pipes: Toward Comprehensive Picture

2002· article· en· W2133256626 on OpenAlexaff
Andrew F. Colombo, Bryan Karney

Bibliographic record

VenueJournal of Water Resources Planning and Management · 2002
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnergy (signal processing)Dimensionless quantityLeakEnvironmental scienceResidence time (fluid dynamics)Pipe network analysisComputer scienceEnvironmental engineeringSimulationPetroleum engineeringMechanicsEngineeringMathematicsStatisticsGeotechnical engineeringPhysics

Abstract

fetched live from OpenAlex

Leaky distribution systems are costly in terms of lost water, potentially adverse water quality effects, and the energy consumed in supplying the leaks. To characterize the energy effectiveness of a leaky segment in a single pipe, several dimensionless parameters are analytically derived, which relate the leak size and location to its associated energy burden and water loss. The computer program EPANET is used to simulate the energy costs of leaks on representative distribution networks. In particular, analysis is performed to illustrate the influence of total system demand, leak location, and topological complexity. Furthermore, the connection between water loss and energy costs illustrates the potential importance of energy costs when pipes are leaky. The impact of leaks on water age is also evaluated through simulation and via a dimensionless expression relating leak size and location to residence time.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.007
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.189
Teacher spread0.175 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations249
Published2002
Admission routes1
Has abstractyes

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