Evaluation of Loss Factor of Styrene-Butadiene-Styrene Modified Asphalt under Wide Temperature Range and Aging
Bibliographic record
Abstract
ABSTRACT The damping property of asphalt is essential in reducing pavement vibration and noise. This study mainly presents the damping property of the styrene-butadiene-styrene (SBS) modified asphalt under a wide temperature range and aging. The materials used 11 total combinations of the base asphalt, three modifiers (SBS, crumb rubber [CR], and polythene), and three additives (hydrotalcite, crosslinker, and plasticizer). The loss factor (LF) was first measured by the dynamic shear rheometer. Then, the four parameters, namely glass transition temperature (Tg), the maximum loss factor (LFmax), effective temperature range of damping (ΔT0.7), and area under the loss factor curve (TA), were used to evaluate the damping characteristics of asphalt at a wide temperature range. Based on this, the damping property of the base, SBS, and CR of aged asphalt is analyzed. The results show that in the medium- and high-temperature regions, the crosslinker and plasticizer can effectively improve the temperature sensitivity of SBS modified (SM) asphalt and the damping property. Adding plasticizer and crosslinker at the same time improves the damping property of asphalt most significantly. In the middle-low temperature region, both the SM asphalt and CR modified asphalt have a poor damping property, and the crosslinker and plasticizer have no apparent effect on the improvement of SM asphalt. The damping property of SM asphalt decreases more slowly than that of base asphalt after aging, and it still has a good damping property. The outlined research results show that SM asphalt has a good damping capacity of pavement at medium- and high-temperature ranges and after aging, which can assist in developing a sustainable solution to extend the service life of pavement without increasing the thickness of pavement.
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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 | 0.008 | 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) | 0.000 | 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".