Laboratory study on an eRoad pavement structure utilizing accelerated loading tests
Bibliographic record
Abstract
The rise in electric vehicle (EV) adoption has spurred the integration of inductive charging systems into road pavements. However, the impact of the inclusion of inductive charging coils in the pavement structure on the overall performance and structural integrity of the road needs to be characterized. This study evaluates this impact using a heavy vehicle simulator on a pavement structure built in a laboratory test pit at Laval University. The test pit comprises a control section representing the standard Québec pavement structure and two sections incorporating inductive charging coils. Various sensors such as strain gauges and load cells were used to monitor the behaviour of each pavement component during dynamic loading tests, from the surface course to the underlying soil. This paper outlines stress measurements at the top of the granular base layer in all sections exposed to different load amplitudes, positions of the load, temperatures, and two water table conditions: high and low.
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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 | 0.001 | 0.001 |
| 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".