Structural behaviour of reinforced concrete beams containing crumb rubber and steel fibres
Bibliographic record
Abstract
This paper presents experimental work to investigate the strength and cracking characteristics of optimised self-consolidating and vibrated rubberised concrete mixtures with/without steel fibres (SFs) using large-scale reinforced concrete beams. The test beams were cast with varying percentages of crumb rubber (CR) (0 to 35%), SF volume fractions (0, 0·35 and 1%) and SF lengths (35 and 60 mm). The performance of some design codes and published empirical equations was evaluated in predicting the shear capacity and first cracking moment of the tested beams. The results showed that the inclusion of SFs could alleviate the reduction in the shear capacity and first cracking moment that resulted from the addition of CR. In addition, combining CR and SFs contributed to developing sustainable concrete beams with high deformability, reduced self-weight and improved shear capacity. The composite effect of CR and SFs also helped to narrow the developed cracks and change the failure mode from brittle shear failure into ductile flexural failure, particularly for the SF volume of 1% (35 mm length). Comparisons of the predicted and experimental results indicate that most of the proposed equations can satisfactorily estimate the shear strength, but overestimate the first cracking moment.
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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 | 0.000 |
| 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".