Utilizing Reclaimed Asphalt Pavement (RAP) Materials in New Pavements - A Review
Why this work is in the frame
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Bibliographic record
Abstract
Recently, prices of asphalt pavement materials have been increasing tremendously, which led to attempts to find alternative cheap materials. In addition, more concerns are directed to preserving natural resources and reducing environmental impacts of using virgin asphalt binders, thus more attention is focused on the use of recycled materials in pavement designs. Transportation agencies worldwide are incorporating reclaimed asphalt pavement (RAP) materials in new pavement designs. RAP was used for the first time in 1973, however, with low percentages due to the lack of understanding of its effect on the performance of asphalt mixes. Currently, higher percentages (e.g. >50%) are being utilized to reduce costs and natural resources and make use of demolished old asphalt pavements. The main concern of combining RAP in new asphalt mixes is how it will affect the resistance of these mixes to permanent deformation (rutting), fatigue cracks, and thermal cracks, which are the main distresses that affect the performance of asphalt mixes. Many studies were conducted to evaluate the effects of RAP on asphalt mixes, and all results showed that RAP increased the stiffness of asphalt mixes, thus improving rutting resistance at high temperatures. On the other hand, results were in conflict with regard to fatigue and thermal cracking. Recently, the Department of Public Works and Services at Ras Al Khaimah, UAE started adopting RAP mixes in ongoing projects (e.g. Kadra-Shawka Road) with no clear guidelines, in hope of reducing costs and that these roads would have better performance. To address the concerns of the effects of RAP and to determine the correct RAP percentage for projects in Ras Al Khaimah, this study was initiated and as a first stage, a literature review was conducted and presented in this article.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it