Performance Evaluation of Joint and Crack Sealants in Cold Climates Using DSR and BBR Tests
Bibliographic record
Abstract
Joint sealants are used widely in Canada to protect pavements from infiltration of water and incompressible materials. Sealants are typically selected based on field studies, which are commonly repeated on a 10-year cycle. This paper examines a laboratory evaluation method based on two laboratory tests that are commonly used for testing asphalt binders: dynamic shear rheometer (DSR) and bending beam rheometer (BBR). Creep stiffness, rate of change in creep stiffness, and rate of change in complex shear modulus with temperature were used to evaluate sealant performance in cold climates. A sealant ranking system was proposed based on the calculation of a sealant index, which combines the proposed evaluation criteria. This method can potentially provide a cost-effective and rapid alternative to field studies. Eight hot-pour sealants were evaluated using this method. Results were verified from an ongoing field study that started in 2004. A good correlation was found between the proposed simplified evaluation method and the existing method.
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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 | 0.002 | 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 | 0.001 |
| 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".