Experimental study of influence of synthetic fibres on behaviour of cylindrical high-strength concrete columns
Bibliographic record
Abstract
This paper presents an experimental study of the behaviour of fibre-reinforced high-strength concrete columns under concentric loading. Twelve cylindrical columns having a length of 1400 mm and a diameter of 300 mm were built using concrete containing different volumes of synthetic fibres. The effects of the amount of synthetic fibres, amount of transverse reinforcement, and concrete compressive strength on the load-carrying behaviour of confined concrete columns were investigated. The results showed that the use of synthetic fibres can help the confining reinforcement to increase the peak strength and deformation of confined concrete. In particular, the use of up to 1% synthetic fibres by volume of concrete increased the load and strain at concrete spalling by 3% and 17%, respectively, when compared to identical concrete columns without fibres. This same addition of synthetic fibres resulted in an increase in the maximum confined concrete strength and corresponding strain by 16% and 29%, respectively. Under very large concrete deformations, however, the synthetic fibres did not significantly influence the post-peak behaviour of these concrete columns. It is concluded that the use of synthetic fibres in high-strength concrete columns allows the columns to reach their ultimate load capacities with lower risks of premature spalling of the concrete cover, thus improving column durability and helping the confining steel to further increase the strength and ductility of confined concrete, especially in seismic areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".