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Record W4386325141 · doi:10.2166/ws.2023.227

How different regional approaches to the network design result in key differences in burst event severity and failure vulnerability

2023· article· en· W4386325141 on OpenAlexaff
John Gibson, Bryan Karney

Bibliographic record

VenueWater Science & Technology Water Supply · 2023
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntrusionFlooding (psychology)Environmental scienceFlexibility (engineering)Vulnerability (computing)Network planning and designKey (lock)Pipe network analysisComputer scienceComputer securityComputer networkGeology

Abstract

fetched live from OpenAlex

Abstract The pipe burst response of an innovative Dutch water distribution network is compared to a traditional looped North American network. Dutch networks focus on water quality and use smaller diameter pipes in branches. The branched network discharges much less water after a burst, which may reduce local flooding, traffic disruption, and product loss. In addition, high velocities and transient pressures are shown to be much localized in the branched Dutch network after a burst, reducing the risks associated with the intrusion of contaminants. However, despite improved water quality, less water loss, and more localized transients, the branched network cannot meet water demands downstream of the burst until the pipe is repaired, unlike a traditional looped network. For modern buildings that meet current design guidelines, the Dutch are content with much lower fire-flow requirements that provide the flexibility to improve water quality and reduce the consequences of pipe bursts, especially water loss.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.200
Teacher spread0.155 · 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 teacher head, not a consensus.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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