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Record W7064362602

Behaviour of concrete corbels reinforced with GFRP bent bars

2023· dissertation· en· W7064362602 on OpenAlexfundaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsReinforcementPrecast concreteCrackingFibre-reinforced plasticReinforced concreteGirderTrussShear (geology)
DOInot available

Abstract

fetched live from OpenAlex

Steel-reinforced concrete (RC) corbels are one of the significant components in the precast buildings and superstructure of bridges, and they are used for load transfer from girders or slabs to columns. In North America, such elements are exposed to harsh weather, which makes them more susceptible to corrosion problems. This study focused on the behaviour and performance of reinforced concrete corbels using non-corrodible glass fibre reinforced polymer (GFRP). The study involved constructing and testing fourteen large-scale concrete double-sided corbel specimens to failure. Twelve out of the fourteen corbels were reinforced with GFRP bent bars, and the remaining two were reinforced with steel reinforcement as control specimens. Four out of the twelve GFRP-RC corbels were cast using high-strength concrete (HSC), while the remaining eight were constructed using normal-strength concrete (NSC). The corbel was tapered with cross-sectional dimensions of 450 mm deep × 300 mm wide at the corbel-column interface and 300 deep × 300 mm wide at the free edge. The overall length of each corbel, measured from the corbel-column interface, was 600 mm. All corbels were tested in an inverted position under displacement-controlled monotonic loading. The test variables were the shear span-to-depth ratio, main reinforcement ratio, crack-control horizontal reinforcement ratio, and concrete strength. The test results were presented in terms of the cracking and ultimate capacities, deflection and strains in reinforcement and were compared to predicted values by relevant Canadian Standards and American Codes. The test results indicated the formation of the strut-and-tie-model (STM) and showed that increasing the concrete strength and main reinforcement ratio increased the stiffness and load-carrying capacity of the corbel to a large extent. Increasing the shear span-to-depth ratio and decreasing the crack-control horizontal reinforcement ratio led to a significant decrease in the load-carrying capacity of the corbel. Overall, this study contributes to a better understanding of the behaviour and performance of the non-corrodible GFRP reinforcement in concrete corbels. The results can lead to the development of design guidelines and standards for corbels, especially in North America, where harsh weather makes such components more susceptible to corrosion problems.

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)0.000
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
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0010.000
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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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