Impact of Tufa Stone Powder as a Partial Replacement of Aggregate on the Mechanical Performance and Durability of Repair Mortar
Bibliographic record
Abstract
The rehabilitation and reconstruction works are usually performed with a view to conserving these landmarks and maintaining them culturally, architecturally and structurally. From this perspective, the mortars utilized in these repairs must be suitable, physiochemically and mechanically, to the ancient materials used in these buildings. Accordingly, it was proposed to evaluate tufa stone powder, a waste product of one of the most widely found stones in the Loire Valley in France, as an ingredient in repair-work mortar mixtures (M1, M2) through partially replacing the fine aggregate it contains with different amounts of this powder (37%, 42%) by weight of mix. Additionally, a third manufacturing mortar (M3) was utilized with both prepared mortars (M1, M2) for comparison with the tufa stone. The mechanical properties (including flexural, compressive and shear strengths, and ultrasonic pulse velocity) and the durability properties (total porosity, thermal dilation and conductivity, capillary absorption, and water and gas permeability) of the three mortars were examined in addition to those of the tufa stone. The results revealed that the prepared mortar, M2, (having lower binder content and a higher amount of substitution with tufa stone powder) has the lowest mechanical performance in comparison with the other mortars, indicating that this mortar is more supple and loose than the authentic tufa masonry. The thermal and durability properties are comparable to that of the tufa stone existent in ancient monuments. Consequently, the prepared mortar (M2) is the most appropriate mortar, for utilization in repairing old landmarks in the Loire Valley in France.
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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 | 0.001 | 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".