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Effect of Prestressing on the Performance of GFRP-Reinforced Concrete Slab Bridge Strips

2012· article· en· W2025231116 on OpenAlexafffund
Martin Noël, Khaled Soudki

Bibliographic record

VenueJournal of Composites for Construction · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaKing Saud University
KeywordsServiceability (structure)Fibre-reinforced plasticReinforcementMaterials scienceSlabStructural engineeringPrestressed concreteComposite materialReinforced concreteSTRIPSEngineering

Abstract

fetched live from OpenAlex

Deterioration of reinforced concrete structures caused by corrosion of steel reinforcement is currently a major concern affecting the safety and functionality of our infrastructure. Fiber-reinforced polymer (FRP) materials have shown tremendous potential as an alternative reinforcement for reinforced and prestressed concrete structures. FRPs have been used in a wide variety of structural applications, from reinforced concrete deck slabs to posttensioned parking garages. However, one promising application for FRP reinforcing bars which has yet to be investigated thoroughly is their use in reinforced concrete slab bridges. This paper presents the results of an experimental study on 10 full-scale glass FRP (GFRP)-reinforced slab bridge strips posttensioned with 0, 2, or 4 carbon FRP (CFRP) tendons with and without shear reinforcement. The tendons were either fully bonded or fully nonbonded to evaluate the effect of bond on the serviceability and ultimate performance of the slabs, particularly in terms of their deformability. Based on the test results, the addition of prestressed CFRP tendons resulted in significantly improved serviceability and ultimate load-carrying capacity with good deformability.

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 score0.018
Threshold uncertainty score0.501

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 communication0.0000.000
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 head0.010
GPT teacher head0.233
Teacher spread0.224 · 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

Citations28
Published2012
Admission routes2
Has abstractyes

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Same venueJournal of Composites for ConstructionSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207