Effect of Silica Fume on High-strength Concrete Performance
Bibliographic record
Abstract
Concrete is one of the most widely used construction and building materials. To produce high-strength concrete (compressive strength higher than 40 MPa) water/cement ratio has to be reduced up to 0.4 and more. Mineral admixtures (supplementary cementitious materials) are used as alternative to the increase in cement content. They either partially replace cement or is added additionally. The conducted studies show that silica fume is superior to other admixtures. However, there is lack of knowledge on overall mechanical performance of concrete mixtures with silica fume in terms of compression, tension, bending and cyclic loading and dependency between these characteristics. In addition to this, controversial findings regarding the optimal amount of silica fume exist. Therefore, the objective of this research is to comprehensively determine the effect of silica fume on high-strength concrete, which could be used for road pavement construction, performance. Three, the same type, concrete mixtures with different amount of silica fume (0%, 7% and 10%), but the same water/cement ratio (0.4) were produced and tested in compression, tension, bending and cyclic loading. In addition to this, density was determined to identify the difference in concrete microstructure due to presence of silica fume. The results showed that silica fume significantly enhances the performance of high-strength concrete in terms of compression, tension, bending and cyclic loading and 7% is an optimal amount.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".