Saskatchewan Field Case Study of Triaxial Frequency Sweep Characterization to Predict Failure of a Granular Base across Increasing Fines Content and Traffic Speed Applications
Why this work is in the frame
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Bibliographic record
Abstract
Approximately one-third of the Saskatchewan provincial highway system is comprised of granular base structures with a thin asphaltic or double seal surfacing. Unfortunately, significant portions of the Saskatchewan thin granular system were not constructed to primary legal weight limit standards and are now exhibiting varying degrees load related distresses and in many cases, structural failures. Based on field performance observations, many of the failures are commonly observed within the granular base layer, particularly when the base is comprised of high fines content, and/or when exposed to high deviatoric stress states. A recent increase in load spectra due to increasing truck traffic has resulted in much of the Saskatchewan granular base systems needing structural rehabilitation. In order to optimize the road structure upgrade treatment, it is desirable to better understand the material constitutive relations of granular base materials across fines content, triaxial stress states, and load frequencies representative of those induced within thin granular base pavements in the field. This research employed triaxial frequency sweep characterization to characterize the mechanical material constitutive behavior of a typical Saskatchewan Type 33 granular base across increasing fines content, triaxial stress state, and load frequency. Based on the findings of this study, increased fines content was found to significantly degrade the mechanical behavior of the standard Saskatchewan Type 33 granular base material in terms of dynamic modulus and phase angle. This research showed that under realistic field state conditions in Saskatchewan, phase angle may be an indicator of elevated viscous behavior within the granular base. Based on the mechanical material properties measured, it was also found that the current specified limits for fines content may not be sufficient to ensure optimal mechanistic structural behavior of thin granular pavement systems under severe traffic load conditions.
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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 | 0.000 | 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) | 0.000 | 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 it