Influence of steel fibres on response of beams
Bibliographic record
Abstract
The following thesis presents the results of six full scale beams tests as part of a research program conducted at McGill University on the effect of steel fibres on the shear capacity of a beam with an aid ratio greater than 2.5. The test specimens had the following dimensions: 4400 mm long, 300 mm wide and 500 mm long. The beams had 4-25M bottom reinforcing bars and 2-20M top reinforcing bars. Two series were designed with different reinforcing details: the "BA" series contained transverse reinforcement spaced at 275 mm center to center while the "BB" series had no transverse reinforcement. The specimens were cast in three batches of two specimens from each series, with each batch containing concrete with respectively 0%, 0.5% and 1% fibres content by volume. The beams were simply supported and were tested with two equal point loads located at 500 mm from the centre of the beam. This research project demonstrated a clear improvement of the shear capacity resulting from the use of steel fibres for the beams without transverse reinforcement. For the beams with transverse reinforcement, displacement ductility was highly increased. This suggests that fibres have the potential to reduce the congestion of the reinforcement if fibres are designed to replace partially closely spaced transverse reinforcement. Also, it was noted that a redistribution of stresses occurred resulting in the formation of more well-controlled cracks. Finally, the strength predictions using the method developed by Aoude (Aoude, 2007) agree very well with the experimental results.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.005 | 0.001 |
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".