Cement Stabilization of Reclaimed Asphalt Pavement Materials
Bibliographic record
Abstract
Many road agencies are experiencing severe aggregate pit depletion and are faced with considering more cost effective alternatives to reduce reliance on virgin granular materials. Increased environmental awareness in combination with a surplus of stockpiled reclaimed asphalt pavement (RAP) materials in many urban centres has led to determining alternative uses for recycled asphaltic concrete materials. This study investigated how cement stabilization would affect both conventional and mechanistic material properties of crushed RAP materials and crushed asphaltic concrete (AC) millings. Overall, both the untreated crushed RAP and the untreated crushed AC millings showed improved California bearing ratio strength and triaxial frequency sweep behaviour in comparison to the conventional City of Saskatoon granular base course. The mechanical properties of the recycled asphaltic materials further improved with cement stabilization. The crushed AC millings had superior mechanical properties in comparison to the crushed RAP material. This study showed that cement stabilization improved the behaviour of recycled asphaltic concrete rubble materials. In addition, the recycled asphaltic materials characterized in this study demonstrated significant residual viscoelastic behaviour, which should improve climatic durability and mechanistic-climatic material behaviour. As a result, cement stabilization of reclaimed and recycled asphaltic concrete materials showed significant improvement in mechanical behaviour, illustrating the potential use of these materials as engineered granular base course.
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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 | 0.000 |
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".