The rheological behavior and high-low temperature performance of warm SBS/rubber asphalt
Bibliographic record
Abstract
Rubber asphalt pavement has the performance advantages of noise reduction, anti-rutting, and anti-cracking. In this paper, the deformation recovery ability, stress sensitivity, dynamic mechanical performance, and chemical components of a warm mix styrene-butadiene-styrene (SBS)/rubber asphalt before and after aging were analyzed. The results showed that the high-low temperature performance of the asphalt was improved, and the ratio of the viscoelastic component was changed by adding the LKW-II warm mix additive to the asphalt. The high-temperature performance of the warm mix SBS/rubber asphalt was improved after short-term aging. At a proportion of the warm mix additive of 0.1%, the high-temperature rheological performance was substantially improved, the anti-rutting ability was enhanced, and the stress sensitivity was the lowest. At high temperatures, the improvements were relatively small at warm mix additive proportions of 0.3% and 0.5%. The low-temperature performance was significantly improved at a proportion of 0.3%. The Burgers model was used to evaluate the low-temperature mechanical behavior and confirmed the low-temperature performance results. The Fourier transform infrared spectroscopy results showed that no new substances were produced after adding the LKW-II warm mix additive to the SBS/rubber asphalt, and the viscosity was reduced by changing the intermolecular force.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".