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Record W4401783613 · doi:10.1061/jccof2.cceng-4516

GFRP Stirrups as Shear Friction Reinforcement for Different Concrete Interfaces

2024· article· en· W4401783613 on OpenAlexaffabout
Basel H. Aljada, Amr El-Ragaby, Ehab El-Salakawy

Bibliographic record

VenueJournal of Composites for Construction · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMaterials scienceReinforcementComposite materialFibre-reinforced plasticShear (geology)Structural engineeringEngineering

Abstract

fetched live from OpenAlex

Glass fiber–reinforced polymer (GFRP) reinforcements can be used as shear friction connectors at the interface of concrete composite elements to maintain structural integrity. However, the shear friction mechanism at the interface greatly depends on the interface condition and the stiffness of the reinforcement crossing the interface plane. A total of 18 GFRP-reinforced concrete (RC) push-off specimens were constructed and tested until failure under monotonic load. The test parameters included the shear plane condition (roughened or not roughened, cold joints and monolithic), type (steel and GFRP), and ratio (0.24%–0.47%) of reinforcement crossing the shear plane. Roughening the interface had a little effect on the overall behavior and shear capacity of the specimen. Conversely, the monolithic specimens carried approximately 60% higher load than their cold-joint counterparts; nevertheless, the failure was more brittle. The capacity prediction by the Canadian Highway Bridge Design Code showed conservative results. By contrast, the predictions of the American Concrete Institute’s model for steel-RC elements overestimated the test results for cold-joint and monolithic specimens with reinforcement ratios of 0.43% or higher.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.257
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.250
Teacher spread0.239 · 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 teacher head, 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

Citations7
Published2024
Admission routes2
Has abstractyes

Explore more

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