MétaCan
Menu
Back to cohort

Shear Strength of FRP Reinforced Concrete Members with Stirrups

2014· article· en· W2012447805 on OpenAlexafffundabout
A. Ghani Razaqpur, Saverio Spadea

Bibliographic record

VenueJournal of Composites for Construction · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFibre-reinforced plasticReinforcementMaterials scienceShear (geology)Structural engineeringReinforced concreteComposite materialShear strength (soil)EngineeringGeology

Abstract

fetched live from OpenAlex

The mechanisms of shear transfer in fiber-reinforced polymer (FRP) reinforced concrete members with shear reinforcement are discussed, and it is explained how these were used to derive the shear design provisions of the Canadian standard for design and construction of building structures with FRPs. Subsequently, the accuracy of these provisions and the validity of their underlying assumptions are assessed by comparing the predicted shear strengths of over three hundred FRP-reinforced beams with their corresponding experimental values. Although the focus of the paper is mainly on beams with FRP shear reinforcement, for completeness beams with and without shear reinforcement are analyzed. It is determined that the mean and standard deviation of the ratio of the test to predicted shear strength of the beams without shear reinforcement are 1.16 and 0.24, respectively, whereas those of beams with shear reinforcement are 1.15 and 0.23. The strengths of these beams are also computed using the recommendations and it is shown that overall recently proposed Canadian method yields more accurate and consistent results.

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 score0.007

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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

Citations119
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Composites for ConstructionSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207