Impacts of Reduced Tire Pressure on Strain Response of Thaw-Weakened, Low-Volume Roads in Manitoba, Canada
Bibliographic record
Abstract
The spring thaw period significantly reduces the bearing capacity of low-volume asphalt roads. To compensate for the reduced bearing capacity, highway agencies apply spring load restrictions (SLR) to limit the damage caused by heavy loads during the period when the road is weakened by thaw. Although the imposition of SLR may reduce road damage, it has a major impact on truck productivity. An alternative to reducing truck loads during the spring is the reduction of truck tire pressure. The reduced tire pressure lowers the tire–pavement contact pressure and the associated damage during the spring period. In 2008, asphalt strain gauges were installed in a section of a low-volume haul road in Manitoba, Canada. Field testing was conducted in the spring and fall of 2009 with a double semitrailer or B-Train equipped with a semiautomated tire pressure control system. The tests were conducted at various loads and speeds and at normal and reduced tire pressures. The results of the field testing showed that when the tire pressure was reduced by 50%, the measured maximum tensile strain at the bottom of the asphalt layer decreased by an average of 15% to 20%. The effects of gauge orientation, truck speed, and tire offset from the strain gauge were analyzed and are presented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".