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Punching Shear Strength of GFRP-RC Interior Slab–Column Connections Subjected to Moment Transfer

2015· article· en· W1521978948 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Composites for Construction · 2015
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSlabMaterials scienceStructural engineeringFibre-reinforced plasticReinforcementDeflection (physics)Composite materialPunchingReinforced concreteEngineering

Abstract

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This paper presents the test results of five full-scale reinforced concrete (RC) interior slab–column connections. Each specimen consisted of a 2,800-mm square slab with a thickness of 200 and 300-mm square central column stubs. Four slabs were reinforced with glass fiber–reinforced polymer (GFRP) bars and one reference slab was reinforced with steel bars. The connections were subjected to eccentric load with a moment-to-shear ratio equal to 0.15 m. The test parameters included the type and ratio of the reinforcement and concrete compressive strength. Test results revealed that increasing the GFRP reinforcement ratio or the concrete strength increased the connection capacity and decreased the deformation of the tested slabs. Moreover, the GFRP-RC connection that has similar reinforcement rigidity to the steel-RC one showed comparable capacity and deflection at failure. Test results were compared with different available models and design provisions including the Canadian standard, the American guideline, and the Japanese code. The Canadian standard and the Japanese code predicted the punching capacity of the test slabs with better accuracy compared with the American guideline.

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.

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 score0.069
Threshold uncertainty score0.701

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 head0.015
GPT teacher head0.238
Teacher spread0.223 · 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