Comparing back-calculated and laboratory resilient moduli of bituminous paving mixtures
Bibliographic record
Abstract
The stiffness of bituminous mixes is an important indicator of mix performance and a required input for mechanistic pavement design. Resilient modulus is one of many stiffness indicators of mixes which can be determined using laboratory testing methods or non-destructive field tests such as falling weight deflectometer (FWD) tests through back calculation. In this paper, two Manitoba mixes known as Bituminous B (Bit B) and Bituminous C (Bit C) are analysed using laboratory testing and FWD back calculation. The experiment involved samples from eight paving sites. Each site included two side-by-side sections having a common Bit B surface course over either a Bit B or a Bit C binder course. Cored samples were tested following the guidelines of the long term pavement performance protocol P07 at 5, 25, and 40 °C. The modulus of each layer was also estimated from FWD deflection measurements. Findings include correlations between the various material and test parameters and a comparison between back calculated and laboratory stiffnesses.Key words: falling weight deflectometer, indirect tensile test, resilient modulus, asphalt concrete.
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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 | 0.000 | 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 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".