Effect of Inert and Pozzolanic Materials on Flow and Mechanical Properties of Self-Compacting Concrete
Bibliographic record
Abstract
This research investigates the fresh behaviour and mechanical properties of self-compacting concrete (SCC) containing high volume of limestone, metakaolin, silica fume, zeolite, and viscosity modifying admixture. Two fine aggregates with different fineness modulus were also utilized to evaluate the effect of sand’s gradation on the mechanical and flow properties of SCC containing inert and pozzolanic powder. Slump flow, V-funnel for fresh concrete and 5-minute-old concrete, J-ring, Orimet with and without J-ring, and L-box and U-box tests were performed on all 14 fresh concrete mixtures to examine the fresh properties of self-compacting concrete. Compressive strength of hardened specimens was measured at 7 and 35 days and tensile strength was also determined at the age of 28 days. The results show that sand grading significantly affects the fresh properties of SCC. It is also concluded that high volume of active powders including metakaolin, zeolite, and silica fume could not improve both the flow and mechanical properties of SCC at the same time. Limestone can be effectively used as filler in SCC in high volume content. A new set of limits for the L-box and U-box tests for SCC containing silica fume is also recommended as the existing criteria are not satisfactory.
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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".