Modeling in Situ Performance of Cement-Stabilized Granular Base Layers of Urban Roads
Bibliographic record
Abstract
This study used a three-dimensional nonlinear orthotropic computational road model to measure the performance of reclaimed and recycled portland cement concrete (PCC) aggregates and reclaimed asphalt pavement (RAP) aggregates stabilized with cement as a base layer in a typical local road structure in the city of Saskatoon, Saskatchewan, Canada. The pavement structure was composed of 45-mm hot-mix asphalt concrete on a 225-mm granular base built directly over an in situ subgrade. The cross section was analyzed with a conventional granular base layer as a baseline and PCC and RAP base layers with 2% cement stabilization. The cement-stabilized PCC and RAP base layers showed improved shear strain and horizontal strain behavior when compared with the conventional granular base layer (which was not cement stabilized). This improvement con-firmed that cement stabilization of reclaimed PCC and RAP materials provided an enhanced primary response. This study demonstrated that typical thin Saskatoon pavement structures were highly dependent on the constitutive properties of base layer material. Stabilizing the PCC and RAP base layers with 2% cement reduced the maximum shear strains at the edge of the pavement structure by 12% and 25%, respectively, compared with the unstabilized conventional granular base layer. It was believed that the increased fracture and cohesion of the residual cementitious materials inherent to recycled granular base, as well as the cementitious binder added, improved structural performance.
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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 | 0.005 | 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 | 0.001 | 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".