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Record W2020671431 · doi:10.1142/s0219455412004641

PERFORMANCES OF CONCRETE-FILLED GFRP OR GFRP-STEEL CIRCULAR TUBES SUBJECTED TO FREEZE-THAW CYCLES

2012· article· en· W2020671431 on OpenAlexaff
Hui Li, Minglei Ma, Guijun Xian, Xin Yan, Jinping Ou

Bibliographic record

VenueInternational Journal of Structural Stability and Dynamics · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsFibre-reinforced plasticMaterials scienceComposite materialDuctility (Earth science)Tube (container)Glass fiberModulusStructural engineering

Abstract

fetched live from OpenAlex

This paper presents an experimental investigation of the performances of concrete-filled glass fiber-reinforced polymer (GFRP) and GFRP externally wound steel circular tubes, subjected to freeze-thaw cycles ranging from -18°C to 18°C. The variation in hoop strains of the tubes during the freeze-thaw cycles was monitored by embedded fiber Bragg Grating (FBG) strain sensors in GFRP layers or between GFRP and steel tube. The residual hoop strain after each freeze-thaw cycle indicates the possible degradation of GFRP materials, such as cracks, debonding of GFRP-concrete or GFRP-steel due to mismatch of the coefficient of thermal expansion, as well as water immersion. A synergistic effect of FRP and steel tubes on the confinement of inside concrete was revealed, resulting in well-improved ductility. After 56 freeze-thaw cycles, remarkable degradation were found in the axial strength, modulus, and strain for concrete-filled GFRP tubes. However, the GFRP-steel tube system showed a negligible reduction in the ultimate axial strain by the freeze-thaw cycles with less degradation in the axial strength and modulus.

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)0.0010.000
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)0.0010.000

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 head0.014
GPT teacher head0.250
Teacher spread0.237 · 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

Citations14
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Structural Stability and DynamicsSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207