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Record W2083711020 · doi:10.1139/l10-046

Fibre-reinforced polymer composite shear reinforcement: performance evaluation in concrete beams and code prediction

2010· article· en· W2083711020 on OpenAlexaffvenue
Ehab A. Ahmed, Ehab El-Salakawy, Brahim Benmokrane

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of ManitobaUniversité de Sherbrooke
Fundersnot available
KeywordsStirrupFibre-reinforced plasticStructural engineeringMaterials scienceReinforced concreteReinforcementBeam (structure)Shear (geology)Composite materialComposite numberShear strength (soil)Glass fiberCarbon fiber reinforced polymerEngineeringGeology

Abstract

fetched live from OpenAlex

This paper evaluates the performance of carbon and glass fibre-reinforced polymer (FRP) stirrups and the accuracy of the shear design provisions incorporated in the currently available design codes and guidelines. A total of seven large-scale T-beams were constructed and tested: three reinforced with carbon fibre-reinforced polymer (CFRP) stirrups, three reinforced with glass fibre-reinforced polymer (GFRP) stirrups, and one reinforced with a steel stirrup for comparison, when applicable. The test results revealed that the design strength of the tested beams is not affected by the reduced strength of FRP stirrups at bend locations. Also, the recent CAN/CSA-S6 update is capable of adequately predicting the shear strength of the beam specimens reinforced with FRP stirrups. The software, Response-2000, which is based on the modified compression field theory (MCFT), predicted well the shear strength and the average strain in the stirrups of the tested beams; however, it overestimated the shear crack width.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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

Citations8
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207