Effect of RAP Source on Compactability and Behavior of Cold-Recycled Mixtures in the Small Strain Domain
Bibliographic record
Abstract
Cold recycled materials (CRMs) are products of modern recycling techniques that are used in maintenance and rehabilitation of pavement structures with significant economical and environmental benefits. CRM mixes are produced at ambient temperature using bitumen emulsion or foamed bitumen as a binding agent, and the aggregate phase is composed mainly of reclaimed asphalt pavement (RAP). This paper investigated the compactability of two RAP sources and their effects on the behavior of CRM mixtures tested in the small strain domain. The compactability was studied using experimental results and the compressible packing model (CPM). Complex modulus tests of CRM mixtures were conducted, and the results were modeled using the Di Benedetto–Neifar (DBN) model. Findings showed that in CRM mixtures with the same gradation and formulation, one RAP source required almost half of the compaction energy of the other source to reach the design air voids content. The rheological analysis results highlighted the impact of the RAP source on the behavior of the CRM mixes in the small strain domain.
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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 | 0.001 |
| 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".