Winter Maintenance of Permeable Interlocking Concrete Pavement: Evaluating Opportunities to Reduce Road Salt Pollution and Improve Winter Safety
Bibliographic record
Abstract
Permeable interlocking concrete pavement (PICP) is a type of permeable pavement system that uses the joint spaces between pavers to drain water from the surface into an aggregate base and subbase layer below. Because of its ability to rapidly drain surface water, PICP has the potential to reduce the amount of ice formed on the surface during winter conditions compared with traditional impervious pavements. As a result, PICP may reduce the amount of road salt needed for de-icing paved surfaces and may also reduce the risk of pedestrian slipping and vehicle skidding throughout the winter. This study evaluates the performance of an outdoor PICP and asphalt test pad over two winter seasons in Vaughan, Ontario, Canada, by assessing differences in surface conditions, surface friction, and surface temperatures. The results of this study indicate that PICP provides equivalent or higher levels of safety compared with asphalt when treated with de-icing products at medium (0.049 kg/m 2 ) or low (0.024 kg/m 2 ) application rates. Re-freezing of melted snow and ice after sunset was observed on the asphalt surface creating black ice, but not on the PICP cells. Consequently, compared with asphalt pavements, PICP surfaces will require use of less de-icer and will have lower risk of slips and falls for pedestrians, and lower risk of skidding for vehicles throughout the winter.
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.
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 | 0.000 | 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 | 0.001 | 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 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".