Comparisons of analytical and approximate interconversion methods for thermal stress computation
Bibliographic record
Abstract
In the northern US and Canada, low temperature cracking represents a significant distress for asphalt pavements. As temperature drops thermal stress develops in the restrained asphalt surface layer and when it reaches a critical value cracking occurs. For this reason, thermal stress is a crucial parameter for evaluating the low temperature pavement performance. Conventionally, thermal stress is computed by converting creep compliance into its corresponding relaxation modulus based on different techniques. In this paper, five analytical and approximate interconversion methods are used to obtain the asphalt binder thermal stress and the results are graphically and statistically compared. Clear differences in thermal stress are found when using power law based interrelationships in comparison with the numerical solution of the convolution integral according to Hopkins and Hamming’s algorithm. Nevertheless, the approximate methods provide a simpler approach for determining satisfactory upper and lower boundary limits when estimating the thermal stress of asphalt binder.
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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 | 0.000 |
| 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 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".