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Record W1996096115 · doi:10.1520/jai103836

Bond Strength Between Cast-in-Place Ultra-High-Performance- Concrete and Glass Fibre Reinforced Polymer Plates Using Epoxy Bonded Coarse Silica Sand

2012· article· en· W1996096115 on OpenAlexaff
Donna A. Chen, Raafat El‐Hacha

Bibliographic record

VenueJournal of ASTM International · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEpoxyMaterials scienceAdhesiveComposite materialFibre-reinforced plasticGlass fiberComposite numberPolymerBond strengthLayer (electronics)

Abstract

fetched live from OpenAlex

Abstract A significant amount of attention has been directed toward the use of fibre reinforced polymer (FRP) materials in structural applications, particularly as main components in hybrid structural members. As a result, the need for an effective connection mechanism that can maintain full composite action at the interface between adjacent dissimilar materials is critical in order to achieve optimum performance of the hybrid structural members. The objective of this experimental program was to investigate the bond performance between glass fibre reinforced polymer (GFRP) plates and cast-in-place Ultra-High-Performance- Concrete (UHPC) using epoxy bonded coarse silica sand aggregates at the bond interface. Both shear and tension tests were conducted using three different types of epoxy adhesives. The general effectiveness of the connection mechanism at the bond interface as well as the relative performance of each epoxy adhesive used were investigated. Analysis showed that, of the three epoxy adhesives tested, the specimens bonded at the interface between the UHPC and GFRP plates using the moisture tolerant epoxy adhesive intended for bonding of hardened concrete and steel performed the best.

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 score0.095
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

Explore more

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