Quality and Durability of Warm Rubberized Asphalt Cement in Ontario, Canada
Bibliographic record
Abstract
This paper documents and discusses an investigation of performance-based testing of asphalt cement (AC), AC modified with warm-mix technology additives (warm AC), rubberized asphalt cement (RAC), and warm RAC. A number of control, warm, and RAC binders from Ontario, Canada, construction contracts were investigated for their compliance with conventional Superpave ® as well as additional specification criteria. It was found that all samples passed the Superpave requirements but only one satisfied the additional Ontario criteria. One warm AC and two field-blended RAC samples showed high levels of physical hardening, which can lead to early cracking. The warm AC lost 8°C when stored isothermally for 3 days at low temperatures according to Ontario's extended bending beam rheometer protocol (LS-308). The two RAC samples lost 10°C and 12°C following the same conditioning. Many of the investigated samples showed deficient strain tolerance as measured in Ontario's double-edge-notched tension test (LS-299). In an effort to formulate warm RAC with improved properties, a number of compositions were prepared with soft Cold Lake AC and a small quantity of naphthenic oil. These binders showed little chemical and physical hardening and reasonable critical crack tip opening displacements. Strain tolerance was much improved by coblending with a high vinyl-type styrene–butadiene–styrene polymer and a small amount of sulfur. The Ministry of Transportation of Ontario is interested in using the developed formulations in future pavement trials with expected improvements in pavement performance.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".