Effect of frost heave on long-term roughness deterioration of flexible pavement structures
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
In northern regions, the frost heave of the subgrade soils due to formation of ice lens is the main mechanism involved in the high degradation rate of the flexible pavement. This paper presents developments of flexible pavement damage models, developed through a multiple linear regression analysis, associated long-term roughness performance to frost heave and degradation mechanisms. Actually, there is no deterioration model that establishes a link between frost heave and flexible pavement. At a design stage, those models would be essential to evaluate the benefits or consequences to have a frost heave lower, equal or higher than the allowable threshold values established by the MTMDET according to the roads functional classification. The result presented illustrate that a significant increase in long-term IRI deterioration rate, usually caused by a more variable subgrade soil, is likely to contribute to the rehabilitation of the pavements up to four years before the end of the pavement service life. This project will allow the administration and the builders to adapt the construction of road infrastructures in cold regions in order to achieve the objectives established to maintain the safety of the users.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it