Evaluation of warm mix asphalt performance incorporating high RAP content
Bibliographic record
Abstract
Using reclaimed asphalt pavement (RAP) increases the sustainability benefits and can enhance the performance of warm mix asphalt (WMA) compared to traditional hot mix asphalt (HMA). However, the RAP content is generally limited in WMA because adding high RAP content may reduce the performance of WMA. In this paper, the authors studied the possibility of incorporating high RAP content from 25 to 70% by mass of WMA by using Evotherm as an additive. Laboratory performance of WMA–RAP mixtures was characterized and compared to a control HMA in terms of moisture susceptibility, rutting resistance, and fatigue characterization. Test results showed that Evotherm greatly improved the moisture resistance of WMA–RAP mixtures compared to HMA. Increasing RAP content made WMA–RAP mixtures stiffer and enhanced the rutting resistance, but decreased the fatigue resistance of the mixtures. Therefore, the maximum RAP content needs to be determined to ensure balance between the fatigue and rutting characteristics of asphalt mixtures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".