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Record W7081959663 · doi:10.11159/icceia25.114

Effective Technique to Prevent Failure of CFRP Confined Columns

2025· article· en· W7081959663 on OpenAlexfundvenueno aff

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsDeformation (meteorology)WeldingComponent (thermodynamics)Failure mode and effects analysisColumn (typography)

Abstract

fetched live from OpenAlex

The confinement of concrete columns has been the subject of several experimental investigations utilizing a variety of methodologies.An elliptical concrete column confined with externally bonded carbon is an effective technique to improve the behaviour of reinforced columns and is considered a superior choice for rehabilitation.The experimental program of the current study includes 20 tests conducted on elliptical concrete columns confined with externally bonded carbon fibre-reinforced polymer (EB-CFRP) laminates.The purpose of the study is to assess how confinement efficacy is affected by the elliptical aspect ratio (A/B) and confinement number of EB-FRP layers.The tests involved a series of unstrengthened control concrete columns, and three further strengthened series, corresponding to one, two, or three layers of EB-CFRP sheets, respectively.For each series, five elliptical aspect ratios (A/B) with values between 1.0 and 1.6 were considered.In order to quantify the confinement level with the number of EB-CFRP layers as a function of elliptical aspect ratio, the results of compressive concentric tests were studied till failure.The findings demonstrate significant improvements in the EB-CFRP confined columns' ductility and compressive strength.In addition, this enhancement improves with the number of EB-CFRP layers, suggesting a proportionate link between CFRP layer' number and compressive strength.However, the confined columns' ductility and compressive strength decreased as the elliptical aspect ratio increased.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.231
Teacher spread0.225 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the World Congress on New TechnologiesSame topicGeochemistry and Geologic MappingFrench-language works237,207