Effect of Limestone and Quartz Fillers in UHPC with Calcined Clay
Bibliographic record
Abstract
Ultra-high-performance concrete (UHPC) is a material developed to maximize the engineering characteristics of hydraulic concrete, in terms of durability and mechanical properties, but the adoption of this technology in practice has not turned out as desired, mainly due to the high amounts of cement and silica fume required for its production, and for its consequences on both economic and ecological costs. As an option to improve the impact of UHPC, both on costs and on sustainability, this work evaluates four UHPC series with metakaolin additions of 5%, 10%, 15% and 20%, and the substitution of 37.5% of the Portland cement volume by limestone or quartz filler. The compressive strength, the bulk electrical resistivity and a set of tests for microstructural characterization (TGA, XRD and quantitative EDS) were utilized to better understand the role of calcite on the hydration and pozzolanic reactions in ternary Portland cement-metakaolin-limestone filler. Results indicate that the reaction of calcite is scarce and should be considered as a mere filler, as no increase in AFm phases were found. Nevertheless, the ternary mixture with 15% of metakaolin in addition to cement, and with 37.5% of the Portland cement volume substituted by limestone filler, was the one that presented the best performance in terms of compressive strength and bulk electrical resistivity. The results of the microstructural characterization indicate that the high kaolin content in the metakaolin originated the most significant hydration and pozzolanic reactions development between the ages of 7 and 28 days, as between 28 and 91 the reaction remained dormant. In general, the whole set of results included in this work indicate that limestone filler doesn't act as a better filler than other kind of powders when used in ternary Portland cement-metakaolin- filler systems.
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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".