Using non-destructive testing to evaluate geogrid-stabilised aggregates subject to accelerated traffic loading
Bibliographic record
Abstract
Roadways include stiff aggregate layers, which support and dissipate traffic loads before reaching the subgrade soil. The aggregate stiffness must be preserved to reduce rutting severity. Geosynthetic-stabilisation can preserve the aggregate stiffness through aggregate-geosynthetic interaction at small strains. The performance of geosynthetic-stabilised roadways depends on the properties of both the geosynthetic and the selected aggregate. A study was completed at the University of Saskatchewan to determine the relative performance of two geogrids used to stabilise two types of aggregate. A recently built full-scale wheel trafficker system applies accelerated traffic loading to 1.5 m wide unsurfaced test sections. Accelerometers were installed on the surface to measure changes in the aggregate stiffness with traffic loading using multichannel analysis of surface waves (MASW). This method facilitates non-destructive measurements of stiffness at numerous depths throughout the aggregate. The average shear wave velocity and rutting performance are presented for each soil-geogrid composite.
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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 | 0.001 | 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 | 0.001 |
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".