USE ATYPICAL ASPHALT BINDERS FROM ALBERTA OILSAND SOURCES FOR THE EFFECTIVE RECYCLING OF ASPHALT PAVEMENT
Bibliographic record
Abstract
Utilization of Reclaimed Asphalt Pavement (RAP) and Reclaimed Asphalt Shingles (RAS) optimizes the use of natural resources by saving the cost for virgin asphalt binders and therefore reducing their environmental footprint. This thesis presents experimental results of using RAP and RAS with virgin asphalt binders from Alberta oil sands deposits. Virgin asphalt binder A from the Athabasca deposit and virgin asphalt binder C from the Cold Lake deposit were modified at two different RAP weight percentages (20 % and 40 % by weight of the total binder). Each blend was tested under four different aging conditions (Unaged, Rolling Thin Film Oven-aged (RTFO), Pressure Aging Vessel-aged (PAV) for 20 h (PAV-20) and 40 h (PAV-40)). The RAP sources used in this study came from rehabilitation contracts on Highway 7 and Highway 403, while tear-off shingles were used as a source of RAS binder. Fourier Transform Infrared (FTIR) spectrometry was used to monitor the degree of oxidation when binders were modified with RAP and RAS and subsequently aged in RTFO and PAV. Rheological properties of the modified binders after different aging protocols were assessed using a Dynamic Shear Rheometer (DSR). Hot Mixed Asphalt (HMA) tests were conducted for neat asphalt binders, 20 % RAP-modified binders and Polyethylene Terephthalate (PET)-modified binders using the Illinois Flexibility Index Test (I-FIT) at two different temperatures (room temperature and -10 °C). Rheological results showed that virgin binder A is the softer one and therefore accommodates more RAP than C. The results also reveal that 20 % RAP added to A can be used as a lower cost alternative for virgin C, as the two materials possess nearly the same rheological grade. According to the I-FIT results, using neat A with 20 % RAP gives higher flexibility than using neat C for HMA. Finally, using PET fibers with virgin binders drastically increases the flexibility of the HMA in the semi-circular bending test.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".