Influence of steel fibers on the shear and flexural performance of high-strength concrete beams tested under blast loads
Bibliographic record
Abstract
This paper presents the results of a study examining the effect of steel fibres on the blast behaviour of high-strength concrete beams. As part of the study, a series of three large-scale beams built with high-strength concrete and steel fibres are tested under simulated blast loading using the shock-tube testing facility at the University of Ottawa. The specimens include two beams built with conventional high-strength concrete (HSC) and one beam built with high-strength concrete and steel fibres (HSFRC). The effect of steel fibres on the blast behaviour is examined by comparing the failure mode, mid-span displacements and, overall blast resistance of the specimens. The results show that the addition of steel fibres in high-strength concrete beams can prevent shear failure and substitute for shear reinforcement if added in sufficient quantity. Moreover, the use of steel fibres improves flexural response under blast loading by reducing displacements and increasing blast capacity. Finally, the provision of steel fibres is found to improve the fragmentation resistance of high-strength concrete under blast loads.
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 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) | 0.002 | 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".