Evaluation of rheological behavior and performance to permanent deformation of nanomodified asphalt mixtures with carbon nanotubes
Bibliographic record
Abstract
Rutting is one of the most important issues associated with asphalt pavements. This defect leads to the accelerated degradation of the pavement and considerably reduces the level of road safety. This paper reports on the results obtained in the optimization of nanocomposite asphalt containing carbon nanotubes (CNTs) with regard to the resistance to permanent deformation. Nanocomposite asphalts were prepared with the addition of different proportions of CNTs. Based on a study on the empirical and rheological properties of the nanocomposites developed, optimization of the CNT content incorporated into the conventional asphalt binder was carried out. Then two asphalt mixtures were investigated, a reference mixture and a nanomodified mixture with CNTs (optimal content). The rheological evaluations were carried out on four-point fatigue equipment and the resistance to permanent deformation was tested in a traffic simulator (wheel tracking test). The results demonstrate the efficient contribution of the nanocomposite to the resistance to permanent deformation.
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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 | 0.001 |
| 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".