Effect of aging kinetics on the fatigue behavior of asphalt mixtures incorporating various RAP contents
Bibliographic record
Abstract
• New method proposed to assess RAP binder mobilization. • RAP addition reduces thermal susceptibility during aging compared to virgin mixes. • As aging progresses, the stiffness modulus of AC containing RAP reaches a plateau. • Using RAP at appropriate content enhances the fatigue behavior of AC. • AC with RAP needs a higher compression load to reach the same strain as virgin AC. Aging significantly impacts the mechanical performance of asphalt mixtures, particularly in terms of fatigue resistance. Although several studies have investigated the fatigue behavior of asphalt mixtures with and without reclaimed asphalt pavement (RAP), limited research has studied the effect of aging kinetics on the fatigue resistance of asphalt mixtures containing RAP. This study investigates the impact of aging kinetics on the fatigue performance of asphalt concrete (AC) incorporating various RAP contents (0%, 20%, and 40%). All asphalt mixtures were subjected to short-term (STA) and long-term aging (LTA). The stiffness of asphalt mixtures was measured at 15°C and 20°C using the Indirect Tensile Stiffness Modulus (ITSM) test. The effect of aging on the stiffness was evaluated through the Aging Modulus Ratio (AMR). Fatigue performance was estimated using the Indirect Tensile Fatigue Test (ITFT) at 20°C. Recovered binders from AC were characterized using penetration, softening point, and Dynamic Shear Rheometer tests. A new method, comparing mixing rule predictions with real measured binder properties, confirmed full blending between virgin and RAP binders. The mechanical results indicate that the stiffness modulus increased significantly after both short and long-term aging for all mixtures, irrespective of RAP content. Additionally, reclaimed asphalt pavement addition increased the asphalt mixture stiffness for a given aging level. The asphalt mixture with 40% RAP showed greater resistance to aging based on AMR values. Furthermore, reclaimed asphalt pavement addition improved the fatigue performance of asphalt mixtures.
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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) | 0.001 | 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 | 0.001 |
| 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".