Development of a New Heat Extraction Method to Reduce Permafrost Degradation under Roads and Airfields
Bibliographic record
Abstract
One of the main degradation mechanisms of permafrost underlying transportation infrastructures is associated with the geometry of airfields and roadway embankments. The two phenomena that are associated with this mechanism are shoulder rotation and longitudinal cracking. These problems occur on the embankment side-slopes because of the important snow drift in winter, which causes a warming. This warming induces an accelerated thaw of the permafrost table under the shoulder causing a loss of support. In this context, the paper describes a new mitigation method, the heat drain, that was developed to counter permafrost degradation problem on the side-slopes of the embankment. The heat drain was developed by the Groupe de recherche en ingénierie des chaussées de l'Université Laval. This technique allows heat extraction from the embankment during winter. The heat drain consists in a highly permeable geocomposite placed in the shoulder. An air intake is installed at the foot of the embankment in order to allow the upward movement of air in the membrane. The paper summarizes the performance of this new technique. This new method was tested in laboratory and proved to be effective to reduce the ground temperature.
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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 | 0.000 | 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 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".