Recommendation of RILEM TC 264 RAP on the evaluation of asphalt recycling agents for hot mix asphalt
Bibliographic record
Abstract
Abstract This recommendation is based on the results of an inter-laboratory study organised by the RILEM technical committee TC 264-RAP "Asphalt Pavement Recycling"—Task Group 3 (TG3) focusing on Asphalt Binder for Recycled Asphalt Mixture. The TG3 aimed to evaluate the effect of a specific family of materials known as asphalt recycling agent (ARA) on the aged binder under different configurations. Even though ageing is an irreversible phenomenon, effective ARA must have the capability to improve the flexibility of the bituminous materials and their resistance against cracking susceptibility with no adverse effect on the rutting resistance of pavements containing reclaimed asphalt. A total of 17 participating laboratories analysed the properties of binder blends composed of aged binder from reclaimed asphalt in three different contents (60, 80, 100%), ARA and virgin binder. The physical properties of the blends were thoroughly evaluated through traditional and rheological binder testing. This recommendation proposes to restore the original material properties at low and intermediate temperatures (i.e. cracking resistance) while balancing the high-temperature characteristics (i.e. rutting susceptibility) with durable impact throughout the progression of ageing phenomena. Therefore, useing of the Dynamic Shear Rheometer is foreseen as a more suitable and sustainable means to evaluate binder blends containing an asphalt recycling agent. Compared with conventional testing, the proposed approach requires fewer materials while resulting in a faster experimental procedure with one single test.
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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 | 0.020 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.014 | 0.003 |
| Insufficient payload (model declined to judge) | 0.037 | 0.073 |
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".