Physical and economic impacts of studded tyre use on pavement structures in cold climates
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
ABSTRACT In cold regions like Alaska of USA, Canada and the northern parts of Europe, using studded tyres is common among the public when driving in icy and snowy conditions. However, studded tyres cause extensive wear to asphalt pavement, reducing pavement life. This study addresses the physical and economic impacts of winter studded tyres on the roadway system to better inform decision makers as they develop alternative solutions and future polices. The approach is applied in a case study from a sample of Alaska statewide road segments. Surveys were employed to examine the extent of the use of studded tyres and cost-effective alternatives. A pavement life-cycle cost review was established considering several variables to discover a realistic cost of roadway resurfacing and rehabilitation. Wear rates due to studded tyres and rut rates due to wheel loads were found for different highway classes. The results indicate higher average wear rates due to studded passenger vehicles on freeways than average rut rates due to heavy wheel loads. The results also indicate lower average wear rates on arterial and collector roads. The estimates show that studded tyre use reduced asphalt surface life by about 7 years on the selected freeway sample in the case study, which is about 47% loss in pavement life based on the initial design life of 15 years. Other road classes experienced lower reductions in service life. Finally, cost analysis was provided to reflect the impact of studded tyres on the state's budget. Countermeasures were suggested, which in turn may help other cold regions develop strategies on the use of new winter tyre technology.
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) | 0.000 | 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 it