Investigation on use of recycled asphalt shingles in Ontario hot mix asphalt: a Canadian case study
Bibliographic record
Abstract
The usage of recycled asphalt shingles (RAS) in hot mix asphalt (HMA) pavements provides many benefits as long as they are properly engineered into the various HMA mixes. Contractors, consultants, and Departments of Transportation have evaluated the performance of these various materials, although they are still only used in a limited number of areas. Alternatively, recycled asphalt pavement (RAP) is recognized as a high value recycled material and is actually the most recycled material in North America. In Ontario, RAP is successfully used in most HMA. Related studies on HMA containing RAS and RAP are limited in Canada although recently studies and field trials on effectively using RAS in HMA in Ontario have been completed by the Centre of Pavement and Transportation Technology (CPATT) at University of Waterloo in partnership with Miller Paving Ltd and the Ontario Centre of Excellence. This paper presents key findings from a comprehensive laboratory investigation and analysis of six asphalt mixes with RAS and RAP in Ontario through dynamic modulus, resilient modulus, thermal stress restrained specimen, and flexural fatigue testing. Using RAS alone or combining with RAP makes the asphalt stiffer at high and low temperatures respectively. Lowering the low temperature performance grade of the asphalt binder by 6 °C and incorporating 3% RAS or less with RAP in HMA mix design can result in meeting the appropriate specification. While field testing of RAS pavements demonstrated that surface friction properties are in good condition in various environmental and loading conditions, the laboratory test results and field performances indicate that RAS can be a useful additive to asphalt mixes in Ontario hot mix pavement through reasonable mix design.
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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 | 0.001 | 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 | 0.001 |
| 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".