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Thermal Compatibility and Bond Strength of FRP Reinforcement in Prestressed Concrete Applications

2007· article· en· W2067928255 on OpenAlexaff
Hugues Vogel, Dagmar Svecova

Bibliographic record

VenueJournal of Composites for Construction · 2007
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFibre-reinforced plasticMaterials scienceConcrete coverReinforcementComposite materialBond strengthUltimate tensile strengthPrestressed concreteStructural engineeringCorrosionAdhesiveLayer (electronics)Engineering

Abstract

fetched live from OpenAlex

Due to concerns with corrosion, the use of fiber-reinforced polymer (FRP) as a replacement to conventional steel reinforcement has greatly increased over the last decade. However, when considering thermal gradients, many researchers have identified differential swelling between FRP reinforcement and concrete. This can lead to the development of splitting tensile stresses within the concrete cover surrounding the reinforcing bar and deterioration of the bond between the materials. A total of ten beams were therefore tested in flexure to investigate bond strength deterioration arising from thermal cycles ranging between −40 and +40°C. Beams were cast at +20°C and prestressed with either glass FRP (GFRP) or carbon FRP (CFRP) tendons. Additionally, the level of damage expected in the concrete cover of the specimens was predicted on the basis of linear elastic and nonlinear finite element analyses of thermally induced stresses. Although damage was theoretically expected, experimental results showed excellent bond performance of GFRP and CFRP tendons in concrete based on material properties and concrete cover requirements adopted for the project.

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 score0.059
Threshold uncertainty score0.461

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 head0.008
GPT teacher head0.237
Teacher spread0.229 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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