High-Strength Geotextiles in Ultraheavy-Load Haul Roads
Bibliographic record
Abstract
The heaviest trucks serving shovel-and-truck mining operations have tripled in weight to more than 600 tonnes gross weight over the past 30 years. The design of haul roads to support these trucks is becoming ever more challenging. An additional problem is the huge demand for aggregates with which to construct these thick, wide roads. In this study of the problem, a numerical modeling investigation was performed for a 300-tonne-design axle on a granular pavement consisting of a capping layer, base, and subbase (0.5, 1.0, and 1.5 m thick, respectively). Conventional linearly elastic analyses and analyses not permitting tension were carried out. While the results of the conventional elastic analysis permitting tension had indicated that there was no reinforcing effect with these geotextiles, the results of the no-tension analysis indicated a significant reinforcement effect attributable to the inclusion of high-strength geotextiles in the cross section. The results bring into question the use of analyses permitting tension in the granular pavement materials.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".