Time Scales in Polymer Modified Asphalts
Bibliographic record
Abstract
Abstract Historically, Maxwell was probably the first one who recognized the importance of time scales for understanding the mechanical response of asphalt. In instantaneous response asphalt behaves as an elastic, solid‐like material, on the other hand its long time response is that of a viscous, fluid‐like material. In the linear viscoelastic region asphalt behaves as a low molecular weight polymer. However, in the nonlinear region of high strains or rates of strain the behavior of some asphaltic systems can be rather complicated. In asphalts, asphaltenes, resins and alkanes compose a complex colloidal system, in which alkanes act as a solvent, asphaltenes as micelles and the polar resins as stabilizers. In order to enhance the mechanical properties of asphalts they are frequently modified by blending them with appropriate polymers. Changes in the impermanent network that can be formed in some of these blends can lead to an unexpected behavior of the steady shear viscosity function. Several different time scales emerge from this behavior. A possible relation of these “nonlinear” time scales to the linear viscoelastic time scales is discussed and examples of anomalous behavior of polymer‐modified asphalts are given.
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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) | 0.004 | 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".