Flexural and shear behaviors of steel and synthetic fiber reinforced concretes under quasi-static and pseudo-dynamic loadings
Bibliographic record
Abstract
Concrete safety barriers used by the Quebec Ministry of Transportation (QMT) to delineate construction zones of traffic areas have an approximate service life of about 3–4 years. Utilization of fiber reinforced concrete (FRC) in barrier represents an economical alternative to delay crack initiation and propagation due to low velocity impacts occurring during their handling procedure. The objectives of this research project were to evaluate the impact of synthetic and steel fiber contents ranging from 0 to 1%-vol. on results of flexural and shear tests conducted under quasi-static and pseudo-dynamic conditions to select the appropriate FRC for the safety barrier. Adding steel fiber content from 0 to 1%-vol. to the reference concrete matrix increased the maximal quasi-static flexural (MOR) and shear (τmax) strengths up to 107% and 229%, respectively. Adding synthetic fiber content from 0 to 1%-vol. provided unsystematic trends, either a decrease of quasi-static MOR of 20% and an increase of τmax of 27%. Besides, higher loading rate improved the MOR values by around 20–35% for all concretes considered (without fiber, with steel fibers and with synthetic fibers), τmax was further increased up to 50–150%.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".