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Record W2023762700 · doi:10.1680/macr.2007.59.10.757

Tie-confined fibre-reinforced high-strength concrete short columns

2007· article· en· W2023762700 on OpenAlexaff
Umesh Kumar Sharma, Pradeep Bhargava, Shamim A. Sheikh

Bibliographic record

VenueMagazine of Concrete Research · 2007
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceSpallDuctility (Earth science)Composite materialConcentricAspect ratio (aeronautics)Compressive strengthConcrete coverReinforcementVolume fractionCompression (physics)Yield (engineering)Structural engineeringCreep

Abstract

fetched live from OpenAlex

An experimental study was carried out to investigate the behaviour of steel fibre-reinforced high-strength concrete (HSC) short columns confined by square ties under monotonically increasing concentric compression. A total of 72 confined and 24 unconfined specimens were tested in this test programme. The test variables included aspect ratio and volume fraction of crimped steel fibres, volumetric ratio, yield strength and configuration of transverse tie reinforcement and concrete strength. The effects of these variables on the uniaxial behaviour of HSC short columns are presented and discussed. The results indicate that the addition of fibres to the HSC mix prevented the early spalling of the cover and increased the load-carrying capacity and ductility of the specimens over that of comparable non-fibre columns. The effect of mixed aspect ratio of fibres on the stress–strain behaviour of confined HSC was also studied by blending the short and long fibres. It is shown that a higher gain in column strength can be affected by the addition of shorter fibres, and longer fibres can provide better enhancements in the post-peak deformability.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
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 head0.028
GPT teacher head0.302
Teacher spread0.274 · 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

Citations27
Published2007
Admission routes1
Has abstractyes

Explore more

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