Performance of Recycled Hot-Mix Asphalt Overlays in Rehabilitation of Flexible Pavements
Bibliographic record
Abstract
The most frequent application of recycling materials in pavements is the reuse of reclaimed asphalt pavement (RAP) to produce recycled hot-mix asphalt (HMA). When designed properly, RAP mixes have demonstrated quality comparable to virgin HMAs in laboratory tests. Despite all the information available about the quality of RAP mixes, obstacles still promote their more frequent use in pavement engineering. Short- and long-term field performance of RAP mixes was investigated compared with virgin HMA overlays used in flexible pavements. Data from the 18 Specific Pavement Studies-5 (SPS-5) sites from the Long-Term Pavement Performance program located across the United States and Canada were used. Performance data were collected during periods ranging from 8 to 17 years. Repeated measures analysis of variance was the statistical analysis tool chosen, pairing distress measurements with survey dates to compare performance and response. The results suggest that in the majority of scenarios RAP mixes have performance statistically equivalent to virgin HMA mixes. The statistical equivalency of deflections suggests that RAP overlays can provide structural improvement equivalent to virgin HMA overlays.
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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 | 0.001 | 0.001 |
| 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".