Accuracy evaluation of statically backcalculated layer properties of asphalt pavements from falling weight deflectometer data
Bibliographic record
Abstract
This study is to evaluate the dynamic effects of falling weight deflectometer (FWD) loading on the surface deflection of asphalt pavement and the accuracy of statically backcalculated layer moduli from FWD data. The dynamic and static deflections were computed using the spectral element method and the layer elastic theory, respectively, for various pavement structures. The static deflection is considerably larger than the dynamic deflection for typical FWD loading and the normalized difference between static and dynamic deflections increases with increasing distance from the load center and decreases with increasing loading duration. The dynamic deflections were utilized to backcalculate the layer moduli using two static backcalculation procedures, MODULUS and EVERCALC. The backcalculated moduli can be significantly different from the actual moduli. The results indicate that the static backcalculation procedure can lead to significant errors in the backcalculated layer moduli by ignoring the dynamic effects of FWD loading.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".