Estimated remaining fatigue life of flexible pavements based on the normalized comprehensive area ratio deflection parameter
Bibliographic record
Abstract
A lot of pavement deflection data are available that may be utilized as a tool to evaluate the structural capacity of pavement structures at network and project levels. Falling weight deflectometer (FWD) is one of the most widely utilized devices in pavement deflection testing. Under FWD testing, deflections generated at several lateral locations as a result of surface loading application are recorded. One of the major downsides of the static FWD testing is the traffic disturbance due to the required lane closures during testing. As an effort to reduce the amount of the required FWD testing on the network level, this study aims to run an advanced computer simulation analysis to mimic the FWD deflection bowl obtained from the field. The entire simulated FWD deflection bowl was utilized in the development of the new comprehensive pavement deflection bowl area parameters. The tensile strain at the bottom of the asphalt layer was successfully related to the developed normalized comprehensive area ratio parameter ([Formula: see text]) and to the number of load repetitions to fatigue failure. The newly developed parameter was evaluated utilizing data for 35 long term pavement performance sections in Texas. The newly developed [Formula: see text] can be easily implemented and utilized as a tool in any pavement management systems.
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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) | 0.001 | 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".