Characterization of Lightweight Mortars with Cork and Olive Stone Waste for Old Building Rehabilitation
Bibliographic record
Abstract
This paper investigates the potential of using cork and olive stone waste as lightweight aggregates in repointing mortars for the rehabilitation of old buildings.For this purpose, mortar blends were prepared like 1/3 mortar partly replacing ordinary sand with different percentages of cork or olive stones aggregates with a grain size of 0-4 mm.The partial substitution rates are: 5, 10, 15, 20, 25 and 30% respectively with a constant amount of binder (Portland cement CEM I 42.5R).All Specimens prepared were remolded after 24h then cured in potable water at 20±2° C until the date of the test.In course of this research, the mechanical and physical features were highlighted while taking into account certain parameters such as consistency, fresh density, mechanical performance (compressive strength, tensile strength), durability (absorption in immersion, capillary water absorption coefficient and chloride penetration).The results demonstrated that incorporating 30% olive stone waste as a sand replacement in the mortar resulted in improved durability and long-term performance compared to control blends.Additionally, all mortars containing lightweight aggregates were lighter than the control mortar.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".