Effect of crumb rubber aggregate on the performance of cementitious composites: A review
Bibliographic record
Abstract
Abstract The increasing use of cementitious composites for different infrastructure constructions has led to an increase in the consumption of raw materials such as aggregate which is a major component in cementitious components. In order to reduce the huge strain posed on the natural sources of aggregate, and continually meet the increasing demand of aggregates to produce cementitious composites; the use of recycled products such as crumb rubber as aggregate in these composites is a viable alternative. However, as the properties of crumb rubber differ from those of conventional aggregate, it is paramount to understand how the incorporation of crumb rubber affects the performance of the cementitious composites. Therefore, this paper presents an overview of how the use of crumb rubber as aggregate affects the performance of cementitious composites in terms of its mechanical, durability, thermal and insulation properties. Conclusions from this paper showed that crumb rubber content in cementitious composites can be optimized to achieve desired properties. Also, the use of crumb rubber as aggregates in cementitious composites reduce significantly the embodied carbon and cost of the composite.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".