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Fiber-Element Model for Slender HSS Columns Retrofitted with Bonded High-Modulus Composites

2006· article· en· W2020080248 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Structural Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite materialBucklingStructural engineeringStiffnessRetrofittingFibre-reinforced plasticCarbon fiber reinforced polymerModulusReinforced concreteEngineering

Abstract

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This paper presents an analytical model developed to predict the behavior of concentrically loaded cold-formed square hollow structural section (HSS) slender columns, strengthened with high-modulus carbon fiber reinforced polymer (CFRP) sheets. The model predicts the load versus axial and lateral displacements, and accounts for plasticity of steel, the built-in through-thickness residual stresses, geometric nonlinearity, initial out-of-straightness imperfection, and the contribution of CFRP sheets. The model was verified using test results. Since the gains in strength due to CFRP retrofitting of the tested columns were found to be sensitive to the inherent out-of-straightness, the model was used to uncouple the effects of out-of-straightness and CFRP reinforcement ratio. It was shown that axial strength and stiffness of HSS columns could be increased substantially when retrofitted with longitudinal CFRP sheets, due to reduction of the lateral displacement induced by buckling. It was also shown that CFRP effectiveness increases for columns with larger out-of-straightness deficiencies and columns of higher slenderness ratios.

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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 score0.041
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 communication0.0000.000
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 head0.004
GPT teacher head0.177
Teacher spread0.173 · 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