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Record W2117739907 · doi:10.1061/41016(314)114

Steel Reinforced Polymers Enhance Strength and Ductility of Beam-Column Joints under Seismic Loads

2008· article· en· W2117739907 on OpenAlexafffund
Ridvan Izi, Mamdouh El‐Badry, Hatem Ibrahim

Bibliographic record

VenueStructures Congress 2008 · 2008
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaDeutscher Akademischer Austauschdienst
KeywordsMaterials scienceDuctility (Earth science)Joint (building)Structural engineeringBeam (structure)DissipationComposite materialShear (geology)Reinforced concreteShear strength (soil)Column (typography)Ultimate loadFinite element methodGeologyEngineeringConnection (principal bundle)

Abstract

fetched live from OpenAlex

The results of an experimental investigation into the application of steel-reinforced polymer (SRP) composites for strengthening shear-deficient exterior beam-column joints in reinforced concrete frames subjected to seismic loads are presented. Four frac12;-scale beam-column joint specimens were tested under a quasi-static cyclic load applied at the beam tip to simulate high levels of inelastic deformations similar to those experienced during a severe earthquake. The first specimen was tested without strengthening and used as control specimen for comparison purposes. The remaining three specimens were strengthened before testing using SRP sheets bonded externally to the joint region in three different arrangements. The SRP sheets selected for this investigation consist of unidirectional twisted high strength steel cords impregnated with polymeric resin. The strengthening technique proved to be efficient in upgrading the capacity and enhancing the ductility and energy dissipation ability of shear-deficient beam-column joints.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.226
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2008
Admission routes2
Has abstractyes

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Same venueStructures Congress 2008Same topicStructural Behavior of Reinforced ConcreteFrench-language works237,207