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Record W2093828402 · doi:10.1016/j.proeng.2014.02.034

Predicting the Leakage Exponents of Elastically Deforming Cracks in Pipes

2014· article· en· W2093828402 on OpenAlexaff
A. M. Cassa, Van Zyl

Bibliographic record

VenueProcedia Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsLeakage (economics)Materials scienceStructural engineeringComposite materialForensic engineeringMechanicsEngineeringPhysics

Abstract

fetched live from OpenAlex

In this study, the relationship between the conventional power equation and the FAVAD (Fixed and Variable Discharges) equation for modelling leakage as a function of pressure is investigated. It is shown that different leakage exponent (or N1) values are obtained for the same leak when measured at different pressures. Analytical exploration of the two equations shows that N1 tends to 0.5 when the system pressure tends to zero and 1.5 when the system pressure tends to infinity. A new term called the dimensionless leakage number, NL, is defined as the ratio between the variable and fixed portions of a leak, and it is shown that a single function can be used to describe the relationship between NL and N1. This relationship is combined with previous work to predict the head-area slope for cracks in pipes to predict the leakage exponent for a range of crack widths and lengths in different pipe materials.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.003
GPT teacher head0.144
Teacher spread0.142 · 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
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

Citations28
Published2014
Admission routes1
Has abstractyes

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