Implementing the AASHTOWare Pavement ME DEsign Guide: Manitoba Issues and Proposed Approaches
Bibliographic record
Abstract
Manitoba Infrastructure and Transportation (MIT) has been using the new Mechanistic Empirical Pavement Design Guide (MEPDG) since 2007 in conjunction with traditional design practices. The objective of this paper is to discuss issues and prospects in using this new design tool by using design examples of typical flexible, rigid and composite (asphalt over concrete) pavements. The influence of traffic volume, asphalt, concrete thickness, base thickness, asphalt binder type, subgrade support and base layer strength on the predicted roughness and surface distresses are analyzed to demonstrate the issues and prospects. Analysis indicates that the default asphalt layer rutting limit of 6 mm is too conservative and the longitudinal cracking model is unreliable. The required asphalt layer thickness could be significantly reduced if the asphalt rutting limit is increased to 12 mm, asphalt longitudinal cracking is ignored and an appropriate asphalt binder is used. In the Pavement ME Design, the base layer exceeding 250 mm and subbase layer are shown to produce no practical influence on the required asphalt thickness. It is recommended that a catalogue of base and subbase thicknesses be developed for frost protection requirement based on local experience. The Pavement ME Design program can be then used to determine the required asphalt thickness. The resilient moduli (stiffness) of base and subgrade are shown to significantly influence the predicted distresses and roughness. The required concrete thickness is shown to be significantly lower than that which Manitoba usually constructs. For the covering abstract of this conference see ITRD record number 201310RT334E.
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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 | 0.000 | 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 | 0.001 |
| 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 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".