Laboratory evaluation of asphalt mixtures reinforced with aramid fibres coated with bituminous oils
Bibliographic record
Abstract
Adding additives such as fibres to asphalt mixtures is believed to improve the overall performance of hot mix asphalt (HMA). Unlike previous studies, this research investigates the performance of HMA modified with oil-coated aramid fibers, exploring its potential to enhance rutting resistance, fatigue behavior, and low-temperature cracking. The fibers were utilized at various dosages (110, 138, and 164 g/tonne) and lengths (13, 20, and 25 mm). Comprehensive evaluations were conducted using the Hamburg wheel tracking device, four-point bending fatigue test, and thermal stress restrained specimen test to assess the impact of these modifications on HMA properties. The results found that 25 mm long aramid fibres, at all dosages, improved the rutting resistance by up to 65% compared to the control mixture. However, the fatigue behaviour and low-temperature cracking resistance were not as good as the rutting performance. Therefore, and based on this study, it was concluded that the addition of the newly developed bituminous oil-coated aramid fibres has no positive impact as a reinforcement of the asphalt mixture.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".