Methodologies for Estimating Effective Performance Grade of Asphalt Binders in Mixtures with High Recycled Asphalt Pavement Content
Bibliographic record
Abstract
In 2009, hot-mix asphalt pavement sections containing 0%, 15%, and 50% recycled asphalt pavement (RAP) were built in a collaborative effort between Manitoba Infrastructure and Transportation and the Asphalt Research Consortium. Two types of 50% RAP mixtures were evaluated: one with no grade change in asphalt binder (PG 58-28) from mixtures with lower RAP content and one with a grade change in asphalt binder (PG 52-34). The following methodologies were used to determine the effective binder properties of the evaluated field-produced mixtures: grading of the recovered binders, blending chart process, mortar procedure, and backcalculation of binder properties from the measured dynamic modulus of mixtures with the Hirsch model and the modified Huet–Sayegh model. Overall, good correlations were observed between the estimated critical temperatures from the blending chart process and the measured ones from the recovered asphalt binders. Of the various evaluated methods, the mortar procedure provided promising results when used to estimate the mixture binder properties at critical pavement temperatures. The findings from the mortar procedure were consistent with the mixtures' resistance to thermal cracking and their current field performance. The procedure indicated that a partial blending was occurring between the virgin and RAP binders of the evaluated mixtures. Although some difficulties arose with the use of the Hirsch model, the backcalculated binder shear moduli were reasonable. The modified Huet–Sayegh model requires further evaluation to assess the true relationship between the characteristic times of the binders and mixtures.
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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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".