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Record W2321421286 · doi:10.1061/40994(321)110

Effect of Over-Insertion and Over-Deflection on the Integrity of PVC Pressure Pipe: Numerical and Experimental Analysis

2008· article· en· W2321421286 on OpenAlexaff
Sébastien Gauthier, Richard St-Aubin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversité du Québec à MontréalRoyal Bank of Canada
Fundersnot available
KeywordsPipingInstallationDeflection (physics)Structural engineeringStructural integrityEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Gasketed joints are the most popular method for joining PVC pressure pipes for buried applications. While this method has proven to be very reliable over the years, it can be susceptible to installers "over-inserting" the spigot end of the pipe into the bells, which can introduce stresses into that area of the pipe. This is particularly common when mechanical means (such as backhoes) are used to assemble the pipe joints in the field. While the pipes are made with clear maximum insertion indications, installers often have trouble controlling the insertion depth, or are not properly trained to avoid over-insertion. These stresses, combined with excessive joint deflection (usually from installers trying to eliminate fittings), have been identified as a source of concern, therefore a research program, combining experimental testing and numerical simulations, was initiated to determine the magnitude and potential effect of these stresses on a typical PVC pipe installation. The FE results correlated with the experimental results showing that it is practically impossible to bring a PVC pipe to failure at the installation. Further, the results showed that only grossly inadequate installation procedures could have an effect on the long term integrity of the piping system. A design change to the bell end of the pipe was found very effective in reducing the risks of over-insertion and hence reducing further the risks of premature failure due to inappropriate installation methods.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.230
Teacher spread0.224 · 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 designBench or experimental
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

Citations3
Published2008
Admission routes1
Has abstractyes

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