An Evaluation of Pavement ME Design Dynamic Modulus Prediction Model for Asphalt Mixes Containing RAP
Bibliographic record
Abstract
Dynamic modulus is a measure of stiffness of an asphalt concrete (AC) mix when subjected to cyclic sinusoidal compressive stresses. In the AASHTOWare Pavement ME Design (ME Design) program, dynamic modulus (E*) value is an essential parameter for the prediction of asphalt pavement distresses such as rutting and fatigue cracking. Several empirical models have been developed by researchers to estimate the E* from the asphalt mix properties when the laboratory measured E* values are unavailable. Witczack model has been integrated into the ME Design program to estimate the E* values when Level 2 and Level 3 inputs for AC mixes are used in the pavement analysis and design. Although Witczack model was developed based upon test data from a different combination of asphalt mixes, the representative data for AC mixes containing reclaimed asphalt pavement (RAP) was not adequate. The study presented in this paper examines the applicability of the Witczack E* prediction model to Manitoba AC mixes containing RAP. For the analysis presented in this paper, asphalt mixes containing different amounts (varied from 0% to 50%) of RAP were prepared in the laboratory. Virgin aggregates and RAP sources remained the same for all mixes to minimize the variability in the laboratory measured E* values. The test for the E* was conducted on the prepared AC specimens at different temperatures and frequencies, E* master curve was then constructed for each AC mix. The developed master curve was compared with the Witczak prediction model. The analysis showed that for Level 2 AC inputs, the Witczak model underestimates the E* by 100% at high temperature but overestimates the E* by 50% at low temperature. For Level 3 AC inputs, Witczak model underestimated the E* by 30% to 70% at high temperature and overestimated the E* by 150% to 200% at low temperature. These indicate that Witczak model may not be appropriate for E* prediction for Manitoba AC mixes. For the use of the ME Design program in Manitoba, Level 1 inputs for Manitoba asphalt mixes may be required.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".