Use of binder stress relaxation parameters and mixture IDEAL-CT for the control of pavement cracking: A case study from a Highway 655 trial in northeastern Ontario, Canada
Bibliographic record
Abstract
• Aging reduces binder stress relaxation, varying by composition. • Polymer-modified mixtures resist cracking when unaged but degrade after aging. • PET fibers counter aging effects via crack-deflection and bridging. • IDEAL-CT poorly ranks field resistance but helps identify weak designs. The longevity of asphalt pavements in cold regions is primarily determined by their resistance to cracking which ultimately causes structural failure. Accurately controlling this distress through laboratory tests on binders and mixtures remains a significant challenge. This study aims to analyze asphalt binder and mixture test feasibility in predicting and ranking asphalt pavement trial section cracking performance. Seven binders used in adjacent trial sections were assessed for phase angle master curves and stress relaxation attributes, while the indirect tensile asphalt cracking test (IDEAL-CT) was performed on corresponding mixtures. Accelerated aging in the laboratory reduces stress relaxation ability in major ways depending on binder composition. Unaged polymer modified mixtures demonstrated good cracking resistance in the IDEAL-CT at intermediate temperatures. However, their performance decreased considerably after irreversible oxidative and thermo-reversible aging at low temperatures. In contrast, polyethylene terephthalate (PET) fibers were able to largely offset the negative effects of binder aging through crack-deflection and crack-bridging mechanisms in mixtures made with straight Cold Lake, Alberta binder. While the IDEAL-CT did poorly at ranking field cracking resistance, practical mixture cracking tests remain useful for identifying and rejecting inferior designs with low benefit/cost ratios. This study highlights the importance of comprehensive testing to ensure long lives and sustainability for asphalt pavements in cold regions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".