Evaluation of Environmental Impact on Perpetual and Conventional Pavement Designs: A Canadian Case Study
Bibliographic record
Abstract
The Ministry of Transportation of Ontario (MTO) constructed a test section in partnership with University of Waterloo, the Ontario Hot Mix Producers Association (OHMPA) and various other partners to evaluate the use of perpetual flexible pavement design on Highway 401. Samples from different asphalt mixes used in the construction of the test sections were structurally evaluated by implementing dynamic modulus testing on the construction year. The samples were then stored and subjected to all seasonal effects, environmental impacts and aging for a year. The same asphalt samples were used to evaluate the dynamic modulus of the asphalt mixes after being subjected to freeze-thaw cycles representing one Canadian winter. The dynamic modulus results showed strong statistical evidence that a significant deterioration in average |E*| results occurred in the SuperPave (SP) 12.5, SP 25 and SP 25 with Rich Bottom Mix (RBM). The deterioration mainly occurred at the results of dynamic modulus at low temperatures as -10ºC and 4ºC. However, the SP 19 mix showed weak statistical evidence of deterioration after one seasonal effect on the samples. The dynamic modulus results were used to evaluate the benefits obtained by adding 0.8% of additional binder to the regular SP 25 mix to develop the SP 25 RBM. The dynamic modulus results did not show statistical significant difference between average |E*| of the SP 25 and SP 25 RBM on the construction year. Moreover, the benefits of additional binder content showed up clearly after one season of freeze-thaw cycles. The results of the dynamic modulus testing after one year of conditioning showed statistical evidence that the strain developed in SP 25 RBM is less than that developed in SP 25, when both mixes are subjected to the same load and loading frequencies especially at -10ºC and 4ºC.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".