Low temperature testing on some PMA binders and mixes and predictions of stiffness and failure stress of asphalt mixes
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Two modifiers, SBS and EVA, were used for the asphalt modification in this study. The BBR and DTT were used to investigate the low temperature creep and fracture properties of the asphalt binders, and the IDT was used for the low temperature creep and fracture characteristics of asphalt mixes. The modification with SBS was found more effective than that with EVA for both binders and mixes. The empirical methods for the mix stiffness prediction using binder stiffness were examined. It was found that Bonnaure method predicts relatively accurate mix stiffness, but Heukelom and Klomp method significantly underestimates it. The possibility to predict the mix tensile strength using binder properties was also investigated. It was found that the normalized mix tensile strength is well correlated with the mix failure stiffness and the maximum tensile strength of the mixes is well correlated with that of the binders. Based on these findings, it is suggested that the current Superpave asphalt binder specification (AASHTO MP1a) should not use the pavement constant 18 and the DTT binder strength to predict the mix cracking temperatures. The thermal stress should be calculated using the mix creep properties predicted from those of the binders. The mix tensile strength can also be found using the normalized tensile strength vs. failure stiffness relationship and the maximum tensile strength. The maximum tensile strength can be either tested using IDT or predicted from that of the binders. In order to use the normalized tensile strength vs. failure stiffness relationship and to satisfy the actual field loading rate conditions which are usually much slower than those used in the labs, the concept of practical stiffness can be used.
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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 | 0.000 | 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 | 0.000 |
| 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 it