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Bond Strength of Standard and High-Modulus GFRP Bars in High-Strength Concrete

2012· article· en· W2106985403 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsToronto Metropolitan UniversityBGC Engineering (Canada)
FundersMinistère des Transports
KeywordsFibre-reinforced plasticMaterials scienceComposite materialDurabilityBar (unit)Steel barModulusBond strengthStructural engineeringGlass fiberService lifeElastic modulusAdhesiveLayer (electronics)Engineering

Abstract

fetched live from OpenAlex

The use of glass fiber–reinforced polymer (GFRP) bars in high-strength concrete (HSC) can solve durability problems associated with conventional steel reinforced concrete (such as premature deterioration due to corrosion) and increase the service life of structures. Experimental investigations were conducted to evaluate the bond characteristics of GFRP bars in HSC. Ninety six pullout specimens that had variable parameters, namely, bar diameter (15.9 mm and 19.1 mm), bar surface condition (sand coated), GFRP bar types (standard low modulus and high modulus), and embedded length (3, 5, 7, and 10 times bar diameter) were tested. The influence of each of these parameters is analyzed to understand interface bond between GFRP bar and HSC. Load-slip characteristics and failure modes of the pullout specimens are described. The performance of various codes in predicting bond stress of both low-modulus and high-modulus GFRP bars embedded in HSC is described based on experimental results.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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