Performance Evaluation of High Modulus Asphalt Concrete (HMAC) Prepared Using Asphaltenes-Modified Binders
Bibliographic record
Abstract
Abstract High strength, extended fatigue life, and improvement in rutting resistance are the main advantages of using high modulus asphalt concrete as a base course material in the pavement structure. The primary goal of this paper was to investigate the performance properties of the high modulus base course using different asphaltenes-modified binders. A crude oil binder and two different asphalt binders from Alberta oil sands sources were used to prepare the mixtures. To prepare hard-grade asphalt binders, all binders were modified using asphaltenes, a waste byproduct of the deasphalting of Alberta oil sands. The performance grades of the modified and unmodified binders were determined, and a mix design was developed for the high modulus asphalt concrete mixes. To evaluate the performance properties of high modulus asphalt concrete mixes composed of unmodified and asphaltenes-modified binders, Hamburg wheel tracking, dynamic modulus and flow number, and indirect tensile strength at low temperature were conducted. The high-temperature performance test results, including Hamburg wheel tracking and flow number tests, indicated that asphaltenes-modified mixtures show higher resistance to permanent deformation. However, the indirect tensile strength test results at low temperature showed higher tensile strength and lower fracture energy for the asphaltenes-modified mixtures compared with the unmodified samples. Moreover, according to the dynamic modulus test results, the asphaltenes-modified mixtures exhibited higher modulus values (stiffness) than the unmodified samples at different loading frequencies compared with the unmodified samples.
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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) | 0.001 | 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 | 0.000 |
| 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".