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Record W2799501186 · doi:10.1139/cjce-2017-0439

Finite element analysis of intermediate crack debonding in fibre reinforced polymer strengthened reinforced concrete beams

2018· article· en· W2799501186 on OpenAlexaffvenue
Michael Cohen, Agostino Monteleone, S. Potapenko

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsDiscovery Air (Canada)University of Waterloo
Fundersnot available
KeywordsMaterials scienceStructural engineeringFibre-reinforced plasticFracture mechanicsFinite element methodReinforcementSofteningSlip (aerodynamics)Reinforced solidCrack closureComposite materialBilinear interpolationComputer scienceEngineering

Abstract

fetched live from OpenAlex

The performance of the fibre reinforced polymer (FRP) to reinforced concrete (RC) interface is vital to ensure desired design capacity. Without proper understanding of the interfacial behaviour it is impossible to develop an effective, efficient, and rational bonding technique. This paper presents the results of a comprehensive numerical investigation aimed to assess and better understand the debonding behaviour caused by different types of intermediate flexural crack distributions in FRP–RC strengthened beams. The model is based on damage mechanics modelling of concrete, a bilinear bond–slip relationship with softening to represent the interface, and a discrete crack approach to simulate crack propagation. The model also highlights how crack propagation and debonding is affected by the rate of change of moment. It is shown that the variation of crack spacing and rate of change of moment can significantly affect debonding crack propagation and strain development in the internal and external reinforcement, which directly influences debonding load.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.205
Teacher spread0.197 · 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 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

Citations6
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil Engineering→Same topicStructural Behavior of Reinforced Concrete→French-language works237,207→