Rheological Properties Of Self-Consolidating Concrete Incorporating Natural And Industrial Pozzolans
Bibliographic record
Abstract
Self-consolidation concrete (SCC) is the latest version of high performance concrete with excellent workability and high resistance to segregation and bleeding. The main objective of this project is to study the rheological properties of SCC incorporating natural and industrial pozzolans (silica fume and metakaolin, repectively) as supplementary cementing materials (SCMs). Use of such pozzolanic materials in the development of environmentally friendly and cost effective SCC can lead to sustainable construction. In this project eleven SCC mixtures are developed by incorporating different percentages of silica fume (SF) and metakaolin (MK) as replacement of cement. However, the water cement ratio of all SCC mixtures are optimized so that all mixtures satisfied the requirements of SCC in terms of fresh properties such as workability, stability, passing ability, bleeding and segregation resistance. This study particularly concentrates on evaluation of the rheological properties such as viscosity and yield stress of developed silica fume and metakaolin based SCC mixtures. The influence of SF and MK dosages on viscosity and yield stress of SCC mixtures are evaluated. Correlations among fresh and rheological properties are developed and critically reviewed to make recommendations.
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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 | 0.000 | 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".