Analysis of rheological properties of rubberized binders containing warm asphalt additives
Bibliographic record
Abstract
The main objective of using warm mix asphalt (WMA) is to reduce emissions and improve the workability by lowering the mixing and compaction temperatures of asphalt mixes through different mechanisms. Since warm asphalt is a relatively new technology, not much research has been conducted on various mix compositions. While some of the concerns about WMA have been addressed, the interaction of warm mix additives with modified binders, especially crumb rubber modified (CRM) binder, is not known in great detail. This paper presents the data on rheological tests conducted on rubberized binders containing warm asphalt additives. Binders from five different sources were modified using 10% crumb rubber by weight of the virgin binders. Two of the available warm asphalt technologies, Aspha-min® and Sasobit®, were used to produce the warm asphalt binders. From the tests, it was observed that the addition of the warm asphalt additives significantly reduce the permanent deformation of the binders, increase the viscosity at 60 °C and the complex modulus, G*, and decrease the phase angle, δ, at high frequencies and low temperatures compared with the CRM binders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".