A non-destructive approach for the predictive master curve of ASPHALT pavements using ultrasonic and deflection methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The elastic modulus of an asphalt mixture varies with temperature and frequency of load due to its visco-elastic nature, and this behaviour is represented by a master curve constructed by either laboratory tests or predictive models based on known material properties. The predictive approach is based on the material specifications and enables to estimate the modulus over a range of frequency without any laboratory tests. However, this estimated curve should be corrected with respect to a measured reference value, which can be obtained from non-destructive methods. In this study, ultrasonic surface waves (USW) and light weight deflectometer (LWD) tests are conducted on two laboratory slab specimens and an as built pavement, and the experimental results are compared with the predictive master curves. The measured dynamic moduli are found consistently higher than the predictive master curves indicating that the model underestimates the modulus of asphalt mix. Finally, the method is verified by shifting the moduli measured at different frequencies to the 25-Hz-design modulus, of which those obtained by the USW tests from the laboratory and field match very well, whereas those by the USW and the LWD tests from the as built pavement are also found highly consistent with each other.
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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