Analysis of Geo-Concrete Composite for Use as a Pavement Base Course for Low-Traffic Roads
Bibliographic record
Abstract
The present study concerns the improvement of the bearing capacity of a reddish clay lateritic gravel (GLAR) by adding a quantity of crushed granite 0/31.5 in order to use the mixture as a road base course. Geotechnical tests were carried out on natural GLAR, and Geo-concrete composite based on GLAR improved with 0/31.5 mm crushed granite stone at three mass ratios (20wt%, 30wt% and 40wt%). The results show a reduction in the Plasticity Index from 18.7% for the natural lateritic material, to 12.2%, 11.0% and 7.3% respectively at the 20wt%, 30wt% and 40wt% crushed granite amendment mass rates, representing a reduction from 34.76% to 60.96%. Analysis of the geo-concrete composite’s compactness showed that the dry density of the new composite increased by 2.81%, 4.75% and 17.36% with the introduction of Crushed granite 0/31.5 in the GLAR. Moreover, the 95% CBR bearing capacity of OPM has been improved by 2.94%, 5.88% and 27.94% respectively at 20wt%, 30wt% and 40wt% addition of crushed granite material. These results are in line with CEBTP 2014 specifications and indicate that these lateritic gravels reinforced with 0/31.5 mm crushed granite at rates of at least 20% can be used in road construction for the base course. Optimum mechanical stabilization or litho- stabilization is achieved with a 30% incorporation of crushed granite material in GLAR.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".