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Record W2084517135 · doi:10.1139/l06-171

Development of a new class of precast concrete pipes - an experimental evaluation

2007· article· en· W2084517135 on OpenAlexvenueaboutno aff
Hany El Naggar, E. N. Allouche, M. Hesham El Naggar

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsPrecast concreteElectrical conduitTrenchless technologyStructural engineeringCivil engineeringEngineeringPipeline transportMechanical engineering

Abstract

fetched live from OpenAlex

Concrete pipes represent the backbone of the municipal storm and wastewater collection systems of Ontario, Canada. Industry and academia partnered on a research effort that aimed at developing new precast-concrete pipe products that provide added value to the final user in comparison with existing products. This paper describes a full-scale experimental evaluation of the design, manufacturing, and performance aspects of a "cellular" concrete pipe, a precast concrete pipe in which multiple continuous conduits were incorporated within its wall. Two fully-instrumented prototype segments of the proposed cellular concrete pipe were manufactured using standard dry-cast manufacturing procedures. The pipe segments were subjected to a D-load test to evaluate their structural performance. The observed structural performance was found to be comparable to solid-wall specimens, particularly when a four-conduit configuration was used. Of the six materials used as conduits, PVC and aluminum were found to perform the best. The presence of the conduits appears to delay the on-set of major cracks, thus increasing the D-load value. Key words: precast, concrete, pipe, experimental, conduit system, trenchless construction 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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.017
GPT teacher head0.228
Teacher spread0.211 · 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
Published2007
Admission routes2
Has abstractyes

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