Performance Evaluation of Stabilized Base Course using Asphalt Emulsion and Asphaltenes Derived from Alberta Oil Sands
Bibliographic record
Abstract
Stabilization of the pavement base course using asphalt emulsion is one of the strategies that improves the layer’s strength and, consequently, enhances the pavement performance. In this study, to improve the performance of the asphalt-emulsion-stabilized base course, asphaltenes derived from Alberta oil sands bitumen are added to the mix. Asphaltenes are a byproduct of the deasphalting process of oil sand bitumen and have no significant value in the asphalt industry. The modified mixes are prepared by adding different amounts of asphaltenes in powder form to the mix at ambient temperatures. Marshall stability and indirect tensile strength of the mixtures are evaluated using different contents of asphalt emulsion and asphaltenes. The low-temperature performance properties of the selected mixtures are investigated using an indirect tensile test and for the high-temperature properties a wheel-tracking test is conducted. The results of this study indicate that the addition of asphaltenes to the emulsion-stabilized mix significantly improves rutting resistance, with a slight increase in moisture sensitivity. However, the indirect tensile test results also reveal that modified mixes are slightly more prone to low-temperature cracking than are unmodified ones.
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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 | 0.000 | 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) | 0.001 | 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".