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Record W2133928237 · doi:10.1139/l03-042

Seismic repair and rehabilitation of a shear-failure damaged circular bridge column using carbon fiber reinforced plastic jacketing

2003· article· en· W2133928237 on OpenAlexvenueno aff
Yeou-Fong Li, Y. C. Sung

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsStructural engineeringMaterials scienceShrinkageDuctility (Earth science)Shear (geology)Fibre-reinforced plasticComposite materialEngineeringCreep

Abstract

fetched live from OpenAlex

In this paper, the analytical and experimental results of tests on a benchmark and a damaged circular bridge column are presented. The benchmark column is a 40% scale reinforced concrete circular bridge column damaged as a result of shear failure during a cyclic-loading test; the benchmark column was then repaired by epoxy and non-shrinkage mortar and rehabilitated by carbon fiber reinforced plastic (CFRP) after the cyclic-loading test. The benchmark bridge column is tested under a cyclic-loading test with constant axial load. The result shows that the column suffered shear failure at low displacement ductility. Non-shrinkage mortar with high-pressure epoxy injection was used to repair the damaged bridge column, and then three-layer CFRP was used to rehabilitate the shear strength of the bridge column. The test result shows that the repaired and rehabilitated column develops significantly improved hys ter etic responses at high displacement ductility. The analytical lateral force – displacement relationship of the bridge columns can accurately predict the experimental result, especially in the nonlinear region.Key words: carbon fiber reinforced plastic, repair and rehabilitation, bridge column.

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)0.001
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 score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.007
GPT teacher head0.185
Teacher spread0.179 · 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

Citations23
Published2003
Admission routes1
Has abstractyes

Explore more

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