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Record W1973269748 · doi:10.1177/0731684415571191

Finite element modeling of fiber reinforced polymer bars embedded in prismatic concrete beams under high temperatures

2015· article· en· W1973269748 on OpenAlexaff
Ali Zaidi, Kaddour Mouattah, Radhouane Masmoudi, Brahim Hamdi

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2015
Typearticle
Languageen
FieldEngineering
TopicFire effects on concrete materials
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials scienceComposite materialAdinaCrackingFinite element methodConcrete coverFibre-reinforced plasticBar (unit)FiberThermalBeam (structure)Reinforced solidStructural engineeringTransverse planePolymerReinforced concrete

Abstract

fetched live from OpenAlex

Numerous experimental tests and analytical investigation were carried out on thermal effects on fiber reinforced polymer bars reinforced concrete structures. Nevertheless, the finite element modeling of thermal behavior of fiber reinforced polymer bars embedded in concrete was insufficiently analyzed, particularly, for asymmetric problems. This paper presents a nonlinear numerical study using ADINA finite element software to investigate the effect of the ratio of concrete cover thickness to fiber reinforced polymer bar diameter ( c/d b ) on the distribution of transverse thermal stresses and deformations in fiber reinforced polymer bars and concrete cover for an asymmetric problem using prismatic concrete beams reinforced with fiber reinforced polymer bars submitted to high temperatures up to + 60℃. Also, to predict the thermal loads ( ΔT cr ) that produce the first radial cracks within concrete and the thermal loads ( ΔT sp ) which cause the splitting failure of the concrete cover as a function of the ratio of concrete cover thickness to fiber reinforced polymer bar diameter for an asymmetric problem. Nonlinear numerical results in terms of cracking thermal loads, thermal deformations, and thermal stresses are compared to those evaluated from analytical models and experimental tests.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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 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

Citations3
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Reinforced Plastics and CompositesSame topicFire effects on concrete materialsFrench-language works237,207