Mortar Based on Dune Sand and Substitute Wood Sawdust: Physico-Mechanical Characterization and Relationship Between Properties in Young Age
Bibliographic record
Abstract
The South of Algeria is known for these immense sand dunes, which cover part of its territory (Sahara). The main objective of this study is the recovery of sands dune and wood waste (sawdust). The latter, which constitutes a potential source of several environmental and economic problems. The objective of this present work is to characterize the physico-mechanical properties at a young age of a dune sand-based mortar lightened by wood waste and to examine the suitability of using it for various applications in the construction of buildings. The improvement of the characteristics of these sands, which essentially formed of sand untapped to date and with the sole aim of enhancing this national sand wealth. The formulation of the mixtures is based on the substitution of dune sand by sawdust, at different weight contents 0, 10, 20 and 30%. The quantity of cement is fixed at 450 g. The results obtained show firstly that the introduction of sawdust improves the characteristics of the mixture (grain size tends to be spread out, reduction in densities), and secondly the physico-mechanical characteristics, especially at 30% substitution (reduction absorption by total immersion of 20.50%, porosity of 28.32%, wet density of 1.73% and dry density of 14.94% and increase in tensile strength of 61.43% and in compression of 63.87%). The effect of sawdust on the relationships between the properties of mortars was clearly noted either for the relationships between early strengths or between compressive and tensile strengths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".