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Record W2801086090 · doi:10.1177/0021998318774833

A comparative study of the thermophysical and mechanical properties of the glass fiber reinforced polymer bars with different cure ratios

2018· article· en· W2801086090 on OpenAlexaff
Claude Nazair, Brahim Benmokrane, Marc-Antoine Loranger, Mathieu Robert, Allan Manalo

Bibliographic record

VenueJournal of Composite Materials · 2018
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversité de SherbrookeMinistry of Transportation of Ontario
Fundersnot available
KeywordsMaterials scienceComposite materialGlass fiberGlass transitionPolymerUltimate tensile strengthMicrostructureFibre-reinforced plasticFiber

Abstract

fetched live from OpenAlex

Cure ratio is a key property for the acceptance and use of glass fiber reinforced polymer bars in civil engineering infrastructure. Yet, there have been no reported studies investigating the effect of cure ratio on the physical, thermal, and mechanical properties of the fiber reinforced polymer bars. This paper presents an interlaboratory test program involving four laboratories to evaluate the cure ratio and glass transition temperature of glass fiber reinforced polymer bars from different production lots. The effect of cure ratio on the physical, mechanical, and microstructure of the glass fiber reinforced polymer bars was also evaluated. The results of this study show that the cure ratio significantly affected the glass transition temperature ( T g ) of the glass fiber reinforced polymer bars tested. The results also show that interlaminar shear strength of the glass fiber reinforced polymer bars was affected by the cure ratio but not the physical and tensile properties, microstructure, or chemical composition. The fully cured glass fiber reinforced polymer bars had interlaminar shear strength up to 8% higher than the partially cured bars. Nonetheless, the glass fiber reinforced polymer bars with a cure ratio of only 96% still had properties well above the minimum prescribed physical and mechanical properties for the reinforcing materials in concrete structures.

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 score0.003
Threshold uncertainty score0.329

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

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