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Record W2143955155

Retrofit of RC Frames Using FRP Jacketing or Steel Bracing

2005· article· en· W2143955155 on OpenAlexaff
T. El-Amoury, A. Ghobarah

Bibliographic record

VenueJournal of seismology and earthquake engineering · 2005
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBracingStructural engineeringJoint (building)BrittlenessDuctility (Earth science)Fibre-reinforced plasticSeismic retrofitStructural loadStiffnessSeismic loadingDeformation (meteorology)Reinforced concreteGeotechnical engineeringEngineeringMaterials scienceComposite materialBrace
DOInot available

Abstract

fetched live from OpenAlex

During recent seismic events, non-ductile failure modes of many existing structures occurred. Retrofit of these structures before the earthquake provides a feasible cost-effective approach to reduce the hazard to occupants' safety and owners' investment. The response of two reinforced concrete frames was examined under seismic excitation. The 9-storey and 18-storey frames are part of the lateral load resisting system in two office buildings that were designed according to the 1960s code provisions. The frames were analyzed assuming flexible joint response by considering the joint shear deformation or assuming traditional rigid joints. Two rehabilitation techniques were proposed to improve the dynamic response of these frames. Fibre reinforced polymer (FRP) jackets were used as a local rehabilitation technique to enhance the joint shear strength and ductility. As another option, X-steel braces were installed in the middle bay of the frame along its height as an alternate lateral load resisting system. For each frame, failure sequence and interstorey drift were examined. It was found that FRP wrapping eliminated the brittle failure modes without significant change in the structural response. However, steel bracing significantly contributed to the structural stiffness and reduced the maximum interstorey drift of the frames.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.703

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 integrity0.0000.001
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 head0.013
GPT teacher head0.226
Teacher spread0.212 · 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 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

Citations7
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of seismology and earthquake engineeringSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207