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Record W2014422376 · doi:10.1177/0731684409345619

Flexural Strengthening of Reinforced Concrete Beams with Steel-reinforced Polymer Composites: Analytical and Computational Investigations

2009· article· en· W2014422376 on OpenAlexaff
Yail J. Kim, Amir Fam, Mark F. Green

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2009
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaterials scienceComposite materialDeflection (physics)Flexural strengthStiffnessUltimate tensile strengthCrackingComposite numberFinite element methodStructural engineeringBeam (structure)Shear (geology)

Abstract

fetched live from OpenAlex

This article presents analytical and computational models for reinforced concrete beams strengthened in flexure using an emerging composite material, steel-reinforced polymer (SRP). The SRP composite consists of unidirectional high-carbon steel fabric embedded in a polymeric resin, providing high strength and stiffness at a reasonable cost. The models developed and examined include finite element analysis, strain compatibility analysis, and closed-form equations reported in the literature and design codes. The study focuses on the load—deflection and load—strain responses, strain variation along the SRP sheets, shear stress distributions and concentrations near the cut-off points of SRP sheets, and cracking behavior. In general, the study shows that flexural strength and deflection at service loads can be well predicted using the models. The shear stress concentration near the cut-off points of SRP sheets may be approximated to 10% of the resin tensile strength just prior to SRP delamination. Confining effects by the adequate end-anchorage effectively redistribute the applied stress in the strengthened beam.

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 categoriesMeta-epidemiology (narrow)
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 score0.064
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.217
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.

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

Citations9
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Reinforced Plastics and CompositesSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207