The mechanical properties of engineered cementitious composites containing limestone powder replaced by microsilica sand
Bibliographic record
Abstract
In this study, an experimental program is conducted to understand the effect of the limestone powder (LSP) content replaced by silica sand on the composite properties. For this purpose, five different engineered cementitious composite (ECC) mixtures were adopted: ECC mixture with only silica sand (SS) for control purposes and four ECC mixtures in which SS is partially replaced by four levels of replacements (25%, 50%, 75%, and 100% by weight of total SS) of LSP. The properties of ECC mixtures produced were investigated for the ages of 3, 28, and 90 days. It was concluded that the mechanical properties of the ECC mixtures with LSP were in general higher than the reference mixture with only SS for all curing ages. Increase in the LSP content had a positive effect on the performance of the compressive strength, fracture toughness, and flexural strength at the ages of 3 and 28 days while this was not valid at the age of 90 days when compared to the reference mixture. Also, the ductility of the ECC beams strongly depends on the LSP content and specimen age.
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 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".