Development of a High-Performance Asphalt Concrete with Enhanced Low-Temperature Performance
Bibliographic record
Abstract
This study aims to develop a high-performance asphalt concrete (HPAC) by using waste asphaltenes to modify the binder and incorporating polyethylene terephthalate (PET) fibres to enhance the performance of asphalt mix at low temperature. As such, a method is proposed to reduce the cracking potential of HPAC mixtures composed of asphaltenes-modified binders by the addition of PET fibres. First, performance properties of a crude oil binder modified with 12% asphaltenes are evaluated by artificially short-term and long-term ageing of the binder using rolling thin-film oven (RTFO) and pressure aging vessel (PAV) procedures, respectively. Superpave binder tests are conducted on the binders through a rotational viscometer, dynamic shear rheometer, and bending beam rheometer. For modifying the HPAC mixture, 6 mm long PET fibres are used at a concentration of 0.15% where it is first tested for compactibility, reflecting field practical considerations. Then, two performance tests, namely dynamic modulus and indirect tensile strength test at low temperatures (−20°C, −10°C, and 0°C), are conducted for an effective mechanical evaluation of the mixture modifications. The results of binder performance grading tests reveal that when the base binder, with continuous PG 70.2-25.9, is modified with 12% asphaltenes, it achieves a continuous PG 82.9-21.8 with a high PG that is suitable for demanding asphalt applications. Although the addition of asphaltenes increases binder stiffness, resulting in a decrease in low-temperature grading, the overall improvement in high-temperature performance outweighs this drawback. Additionally, compactibility tests demonstrate that mixes with 0.15% PET fibres exhibit acceptable compactibility and meet the prescribed air void requirements of a maximum 6%. Furthermore, the incorporation of PET fibres in HPAC mixes increase stiffness by 63% at a 15°C and 10 Hz loading frequency, with no negative impact on the anticipated response. Compared to control mixes where no asphaltenes or fibres are used, the asphaltenes modification and PET fibre incorporation increase fracture energy by up to 27% at −10°C, indicating lower cracking potential and improved low-temperature performance. Moreover, tensile strength is enhanced by up to 18% at 0°C, demonstrating an efficient combined effect of both modifications.
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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 | 0.001 |
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".