Assessing the Effect of Coarse Aggregate Size on Self-Compacting Fibre Reinforced Concrete Mix
Bibliographic record
Abstract
Steel fibres increase inhomogeneity and alter rheological and hardened characteristics of self-compacting concrete. To investigate the rheological behaviour and hardened characteristics of self-compacting concrete (SCC) and selfcompacting steel fibre reinforced concrete (SCSFRC), a wide range of normal strength self-compacting concrete mixes containing steel fibres and coarse aggregates (of size 10 mm, 20 mm) with target cube compressive strengths between 30 to 70 MPa were prepared in the laboratory. The plastic viscosity of these concrete mixes were estimated to be in the range between 20-50 Pa s , and the slump flow time t500 of each mix was recorded to ensure that the flow and passing ability for workability of the mixes satisfy the recommended British and European standards. This work mainly focuses on the properties of fibre reinforced self-compacting concrete containing 0.5% and 1% (by volume fraction) steel fibres and the effect of coarse aggregates on their rheological behaviour and flow characteristics. The effect of steel fibre content on the strength of hardened concrete is also investigated. In addition, comparison of flow behaviour between SCC and SCSFRC is also presented.
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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".