Fatigue Performance of Asphalt Mixtures Prepared with RAP and Recycling Agents: A Study at the Fine Aggregate Matrix Scale
Bibliographic record
Abstract
A fine aggregate matrix (FAM) has been used as a tool to evaluate the effects of reclaimed asphalt pavements (RAP) on the fatigue performance of asphalt mixtures. This study evaluated the fatigue performance of FAMs produced with RAP by comparing their strain tolerance at the same number of loading cycles. Three failure criteria were adopted to calculate the mixture strain tolerance: GR, Cf, and DR. The FAMs were prepared with RAP at 0%, 20%, and 40%, a PG 64-22 binder, a bio-oil, and a petroleum-based aromatic oil. The addition of RAP increased the stiffness and reduced the relaxation rate of the mixtures, resulting in FAMs that are stiffer and more susceptible to damage. The findings showed consistent conclusions among the three fatigue failure criteria. The addition of the petroleum-based oil proved to be promising by increasing the strain tolerance of the mixtures containing 20% RAP, while adding the bio-oil was the best option to increase the strain tolerance of the mixtures containing higher RAP proportions (40%).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".