Moisture susceptibility of Warm-Mix-Asphalt in a changing climate: incorporating top-down cracking and fracture mechanics approach
Bibliographic record
Abstract
Over the next decade, climate changes may cause an increase in precipitation in some areas of Canada, including Ontario. In such areas, moisture damage can be one of the major causes of premature degradation of asphalt pavements. Failure of asphalt pavements due to moisture damage causes a considerable expenditure of funds for repair and rehabilitation every year. Traditionally moisture damage of the asphalt mixtures is evaluated by tensile strength ratio between dry and wet condition, which is not sufficient to conclude the moisture damage performance. Also, the results from the majority of conventional tests do not correlate well with the observed field performance. In order to overcome these difficulties, the varying effects of moisture damaged on wax modified asphalt mixture properties were investigated by using Superpave IDT creep, resilient modulus and strength tests. Moreover, fracture mechanics approach has also been utilized to characterize the moisture susceptibility of the asphalt mixture performance. In recent years, with the increasing concerns of global warming and increasing emissions, the asphalt industry has been using commercial waxes in asphalt mixtures to lower its emissions by reducing the mixing and compaction temperatures. Thus, in this study, PG 58-22 asphalt binder was modified by two types of commercial waxes (FT-paraffin and Asphaltan B) and mixed with two types of crushed granite aggregates, which were used to investigate the moisture damage potential of the wax modified asphalt mixtures. This paper provides a summary of the evaluation test set up and obtained results. It was found that the warm mix asphalt mixtures have a higher moisture damage ratio (MDR) of Energy Ratio compared to unmodified mixtures, clearly indicating the higher fracture resistance than the control mixtures. Moreover, the results obtained from moisture damage ratio in terms of the number of load repetition required to grow a fixed crack (MDRN); also confirms the wax modified mixtures have a better crack initiation and growth resistance even after conditioning. The analyses of the obtained results, thus, indicate that warm mix asphalt could be a greener solution to the climate change and towards a durable pavement infrastructure.
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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".