Rheological Comparison Between Blended Asphalt Binders and Extracted and Recovered Asphalt Binder From Rejuvenated Asphalt Mixture With Very High Rap Content
Bibliographic record
Abstract
Abstract Efficient rejuvenation of the RAP’s binder facilitates the use of higher RAP contents. Assessing the efficiency requires evaluating the right blend of the rejuvenator, new and old binder that represents the real binder blend inside the asphalt mixture. Extracted and recovered (E&R) binder from the rejuvenated asphalt mixtures containing RAP is the best practice to obtain the existing blend of the rejuvenator, new and old binder. However, Extraction and recovery is not a common practice to study rejuvenation efficiency since it is time-consuming and energy-demanding with exposure to hazardous chemicals. Instead, blending rejuvenator, new binder and the E&R binder from RAP under appropriate blending conditions limits the extraction and recovery to RAP, and minimizes efforts for studying rejuvenation efficiency. This study aims to find the blending conditions under which the blend of the rejuvenator, new and RAP binder resembles the E&R binder from asphalt mixture rheologically. The rheological properties of three binder blends prepared under intense (IB), medium (MB) and low blending (LB) conditions were compared with those of the E&R binder. Performance grade (PG), rutting potential, fatigue resistance and behavioral characteristics are the rheological properties for making comparison. It was found that IB and MB are good representative of the E&R binder with regard to PG and PG + designation. In addition to IB and MB, LB can be a surrogate for the PAV-aged E&R binder. Also, any blending conditions between MB and IB for rutting potential and characterization are recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".