Preliminary prediction of endurance limit for asphalt rubber mixtures due to healing
Bibliographic record
Abstract
One of the main requirements of designing perpetual pavements is to determine the endurance limit of asphalt mixtures. The endurance limit is the strain below which no fatigue damage occurs or can be healed during unloading. If the pavement thickness is controlled so that the strain at the bottom of the asphalt layer is kept below the endurance limit, the pavement would endure indefinite load repetitions and would not experience bottom-up fatigue cracking. Field observation shows that an endurance limit for hot mix asphalt (HMA) does exist. The endurance limit values were previously determined in the laboratory in the NCHRP Project 9-44A for conventional HMA at different conditions. The purpose of this paper was to determine the endurance limit values for asphalt rubber (AR) mixtures using laboratory beam fatigue tests. The paper discusses the results of a study that produced a preliminary estimation of the endurance limit for an asphalt rubber mixture placed in Sweden. This study included 24 beam fatigue laboratory tests conducted according to the AASHTO T321-03 test procedure with rest periods between loading cycles. Two factors that affect the fatigue response of asphalt mixtures were evaluated, which are the applied strain and the rest period between loading cycles. A model was developed to determine the stiffness ratio as a function of strain and rest period. The endurance limit was determined using the developed model by setting the stiffness ratio as one, indicating no accumulated damage or complete healing. Endurance limit values for the AR mixture ranged from 150 to 175 microstrain at 20 °C, which are significantly higher than those of conventional HMA. This indicates that a thinner asphalt rubber layer can be used to reach the endurance limit as compared to the HMA layer. Determining the endurance limit of asphalt rubber has significant design and economic implications.
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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 | 0.001 | 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 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".