Triaxial Frequency Sweep Characterization of Saskatchewan Granular Base Across Increasing Fines Content and Stabilization Systems
Bibliographic record
Abstract
Approximately one third of the Saskatchewan provincial highway system is comprised of thin granular pavements. Unfortunately, significant portions of the Saskatchewan thin granular pavement system are exhibiting varying degrees of performance including structural failures. Research has shown that many thin granular failures initiate within the granular base layer, and are primarily driven by high deviatoric stress states and/or high fine material content within the grain size distribution. As a result of the aged condition state of many thin granular pavements coupled with increased load spectra demands, much of the Saskatchewan thin granular paved system will require some form of structural rehabilitation in the foreseeable future. Therefore a better understanding of the performance related properties of marginal granular base materials is required to optimize rehabilitation of various quality in situ granular materials. This research employed triaxial frequency sweep testing to characterize the mechanical material constitutive behavior of a typical Saskatchewan granular base across various fine material content and cementitious strengthening to provide a framework for selection and specification of granular stabilization systems. Based on the findings of this study, increased fines content was found to significantly degrade the mechanistic behavior of the granular base material. It was also found that cementitious strengthening significantly improved the mechanical behavior of high fines content granular base materials to the point where granular bases with high fines content may be recycled and used as road structural materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".