Effects of Thermo-Reversible Aging on the Cracking Resistance of Asphalt Mixtures in the Semi-Circular Bend Test
Bibliographic record
Abstract
The semi-circular bend (SCB) test has been widely used to evaluate the cracking resistance of asphalt mixtures. However, uncertainty has arisen with respect to the accuracy of the test method in cold regions where thermo-reversible aging of the asphalt binder plays a significant role in determining the cracking resistance of asphalt pavement. This study aimed to optimize the current SCB protocol by including an evaluation of thermo-reversible aging phenomena. Asphalt mixtures were collected from different regions in North America. Two groups of SCB samples were prepared, with one tested at 0°C after 2 h of conditioning at the test temperature, and the other tested at the same temperature after 72 h of conditioning at −20°C. The SCB tests were conducted at 50 mm/min and the force was recorded versus both the vertical load line displacement and horizontal crack mouth opening displacement (CMOD). To quantify the effects of thermo-reversible aging on cracking resistance, indicators including the flexibility index (FI), fracture energy (FE), cracking resistance index (CRI), balanced cracking index (BCI), and cracking initiation index (CII) were calculated. The results show that the FI and BCI are greatly affected by cold conditioning, decreasing by 34.6 % and 22.3 %, respectively. The post-peak slope of the force–CMOD curve deteriorates to varying degrees, which provides guidance for optimizing the current SCB protocol to better rank the low-temperature cracking resistance of asphalt mixtures. In contrast, the CII is affected to only a minor degree by thermo-reversible aging and is also a preferred indicator from a repeatability perspective. Important variations in stress relaxation ability (e.g., m-value, phase angle), and how these respond to cold conditioning, are missed in rapid SCB mixture tests and therefore best determined on recovered asphalt binder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".