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Record W2176445269 · doi:10.1139/cjce-2014-0238

Shear strength of glass fiber reinforced polymer – reinforced concrete continuous beams without transverse reinforcement

2015· article· en· W2176445269 on OpenAlexafffundvenue
Karam Mahmoud, Ehab El-Salakawy

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Manitoba
KeywordsFibre-reinforced plasticReinforcementMaterials scienceShear (geology)Structural engineeringComposite materialTransverse planeReinforced concreteShear strength (soil)EngineeringGeology

Abstract

fetched live from OpenAlex

The shear behaviour of continuous concrete beams reinforced with glass fiber reinforced polymer (GFRP) bars without shear reinforcement has not been studied yet. However, the current codes and guidelines for FRP-reinforced concrete (RC) structures provide shear provisions that are applicable to both simple and continuous members. These provisions are based on test results of simple beams that do not account for the continuity of indeterminate structures. In this paper, the test results of large-scale GFRP-RC continuous beams without transverse reinforcement are presented. The test variables are the type and ratio of longitudinal reinforcement, and concrete strength aiming to evaluate the shear strength of such beams. The test results showed that moment and shear redistribution occurred. Also, the shear capacity of GFRP-RC continuous beams increased as both the longitudinal reinforcement and the concrete strength increased. Moreover, it was found that the continuity affected the concrete contribution to the shear strength where the ratio of experimental-to-predicted shear strength by different codes and guidelines was less than that of simply-supported beams.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.196
Teacher spread0.187 · 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 designSimulation or modeling
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
Published2015
Admission routes3
Has abstractyes

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