Microstructural Characteristics of Sand Asphalt Mortar
Bibliographic record
Abstract
ABSTRACT Fine aggregate matrix (FAM), an intermediate scale of asphalt concrete (AC), helps identify how small-scale mixture components affect overall AC-scale mechanical behavior. However, investigating FAM does not straightforwardly identify the influence of asphalt binders on AC fatigue behavior due to fine aggregates mixed in FAM. To address this limitation and minimize the variability caused by different fine aggregates, some researchers propose using sand asphalt mortar (SAM) to exclusively focus on the binder effect. To better represent binder characteristics using SAM, it is critical to identify the correct binder amount and its volumetric characteristics. This study aims to perform an in-depth evaluation of SAM microstructural characteristics, specifically air void (AV) and binder film thickness (FT). Thus, six SAM samples, fabricated with Ottawa sand and two types of asphalt binder at three contents (6 %, 8 %, and 10 %) were produced in cylindrical bars. Furthermore, one FAM mixture derived from its AC mixture was also evaluated for comparison. To assess location-dependent microstructural characteristics, the samples were cut into three parts (top, middle, and bottom), which were examined for measuring AV and FT. Test results showed that average AV and median FT were the best parameters to consider. SAM specimens were homogeneous in terms of FT for any content or asphalt binder type; however, in terms of AV, homogeneity was only observed at a 6 % binder content. It is noted that FT values were smaller than 60 µm from both SAM and FAM samples, which is significantly lower than the thickness used at parallel plate geometry (i.e., 1–2 mm thick) in typical rheological tests. These findings indicate that SAM is considered a reasonable mix to effectively characterize binder behavior in AC mixtures due to its realistic film geometry, which is significant for understanding the effects of binder on viscoelastic mechanical properties in AC 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 | 0.001 | 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".