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Record W2003622171 · doi:10.1139/l06-107

Mechanics of fibre-reinforced polymer - concrete interfaces

2007· article· en· W2003622171 on OpenAlexfundvenueno aff
Usama Ebead, K.W. Neale

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUtah Agricultural Experiment Station
KeywordsFibre-reinforced plasticTrussMaterials scienceFinite element methodStructural engineeringAdhesiveComposite materialNonlinear systemSlip (aerodynamics)Composite numberStress (linguistics)EngineeringLayer (electronics)

Abstract

fetched live from OpenAlex

A finite element model is developed for analyzing the interfacial behaviour for fibre-reinforced polymer (FRP) laminates externally bonded to concrete prisms and subjected to direct shear. The element sizes of the FRP, adhesive, and concrete at the interface were chosen to be very small (0.25–0.5 mm) so that the debonding behaviour could be properly captured. The behaviour at the interface between the FRP composite and the concrete is modelled using truss elements connecting the FRP laminate to the concrete block. The truss elements incorporate a nonlinear bond stress-slip relationship controlled by several parameters related to the characteristics of the FRP composite, adhesive, and concrete. Results are given in terms of the load capacity of the joint and the stress and strain distributions in the FRP, at the interface, and in the concrete. In addition, the transfer lengths, as well as the force transfer between the FRP laminate and the concrete block, are investigated. Comparisons between the finite element results and available experimental data are presented.Key words: nonlinear finite element analysis, FRP-to-concrete bonded joints, interface elements, debonding, interfacial behaviour, transfer lengths.

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 score0.245
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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

Citations24
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207