Blending and diffusion of reclaimed asphalt pavement and virgin asphalt binders
Bibliographic record
Abstract
An experimental study to understand the properties of reclaimed asphalt pavement (RAP), virgin binder and their respective blends was conducted. It was found that the current AASHTO (American Association of State Highway and Transportation Officials) M 323 specification recommendation to use one-grade softer performance graded asphalt at>15% RAP addition may not be justified. It is demonstrated that a binder grade change is not necessary up to 25% RAP in most blends. The ability of RAP and virgin binders to blend by diffusion at typical asphalt-mix production and placement temperatures and times was measured by a dynamic shear rheometer. A simulation showed that a complete binder blending in both hot-mix asphalt and warm-mix asphalt applications is reached within minutes after mixing. Nevertheless, binder layer thickness in the mix has a significant impact in these simulations and further understanding of binder film thickness in asphalt mix is necessary to accurately estimate degree of blending. Real mix data from Carpenter and Wolosick [(1980). Modifier influence in the characterization of hot-mix recycled material. Transportation Research Record, 777, 15–22] were successfully fitted with the diffusion model, demonstrating that the diffusion as measured for binders follows the same fundamental processes in the asphalt mix.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".