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Record W4396242163 · doi:10.3390/buildings14051251

Investigation of Key Parameters Influencing Shear Behavior in Glass-Fiber-Reinforced Polymer (GFRP)-Reinforced Concrete (RC) Interior Slab–Column Connections

2024· article· en· W4396242163 on OpenAlexaffabout
Loai Alkhattabi, Nehal M. Ayash, Mohamed Hassan, Ahmed Gouda

Bibliographic record

VenueBuildings · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsFibre-reinforced plasticSlabMaterials scienceStructural engineeringShear (geology)Reinforced concreteComposite materialColumn (typography)EngineeringConnection (principal bundle)

Abstract

fetched live from OpenAlex

This article explores the punching shear behavior of GFRP-RC interior slab–column connections. The parameters tested included the column–aspect ratio (1.0, 2.0, 3.0, 4.0, and 5.0), perimeter-to-depth ratio for square column stubs with side lengths of 0.3, 0.4, 0.5, 0.6, and 0.7 m, and span-to-depth ratios of 4, 6, 8, 10, and 12. A review of the literature revealed that no previous study has investigated the effect of these parameters or their interactions on this type of connection. Numerically, twenty-five slabs were created using finite element (FE) software (V3), each with square dimensions of 2.5 m and a constant thickness of 0.2 m. The central column extended 0.3 m from the top and bottom of the slab. All four sides of the slabs were supported, and the specimens underwent pure static shear load testing. The test results demonstrated that all slabs failed due to punching shear. Increasing any parameter value reduced the punching shear stresses. Additionally, the results indicated that Canadian (CSA-S806-12) and Japanese (JSCE-97) standards for FRP-RC materials generally provided the closest predictions of punching shear capacity compared to the American guideline, ACI 440.1R-22. However, all standards exhibited shortcomings and require enhancement and modifications, particularly to consider the impact of the span-to-depth ratio. Therefore, three equations were developed to predict the shear strength of the connections, yielding better results than those prescribed by the North American and Japanese standards.

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 categoriesMeta-epidemiology (narrow)
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 score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.234
Teacher spread0.220 · 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.

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
Published2024
Admission routes2
Has abstractyes

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