Thermomechanical Characterization of Hollow Concrete Brick with Sheep Wool
Bibliographic record
Abstract
The use of ecological materials is a promising solution for reducing the environmental footprint in the building sector.Recently, several composites based on organic additions are studied to improve the properties of building materials.This work proposes the study and development of a concrete brick with an organic sheep wool additive for the loadbearing walls of the structure or building envelope.First, a study of the physicochemical properties of the sheep wool additive was conducted.SEM tests were carried out to determine the impact of the treatment of sheep wool fibers with a lower rate ratio (1% NaOH solution).Subsequently, a series of thermomechanical characterization tests of the composite allowed the study of thermal conductivity, compressive and bending resistances according to different volume fractions of sheep wool (1%, 2%, 3%, and 5%) by sand replacement method.The results indicate that the chemical treatment permits the improvement of the surface roughness of the fiber by eliminating lipid contamination deposits, a gain of 42% on the thermal conductivity, and interesting values of the compressive strength for the composite, respectively 2% and 3% in order to obtain 24.33 MPa and 23.35 MPa.Thus, an analysis of the dimensionless coefficients was carried out to determine the optimal fraction of sheep wool with good thermal and mechanical properties.For the valorization of this composite, the manufacture of a brick based on this formulation was proposed.The results of the study showed interesting thermal and mechanical properties for a percentage of 2% of sheep wool fiber and also confirm the significant effect of processing on this improvement.
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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 | 0.000 |
| 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".