Evaluating the structural performance of eRoad pavements: impact of inductive charging coils on mechanical behaviour
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Electric Road Systems (ERS) are pivotal in advancing Electric Vehicle (EV) technology by enabling dynamic wireless charging through integrated elements in roadway infrastructure. These systems extend EV range and reduce the need for frequent recharging, while supporting smaller batteries. In contactless ERS, inductive coils are embedded in pavement layers, leaving the road surface unaltered, unlike ground-based conductive systems. However, the long-term effects of embedded coils on the mechanical response and integrity of pavement structures, particularly under Canadian climatic and traffic conditions, remain underexplored. This study evaluates the mechanical performance of electrified road (eRoad) pavements with inductive coils, compared to traditional pavements (tRoad). Sensor-based monitoring assessed the performance of three full-scale pavement structures (two eRoad and one tRoad) built at Laval University's accelerated pavement test facility, under varying loads and environmental conditions. Results show different strain distribution in eRoad pavement, suggesting possible bonding issues between coil casing material and asphalt concrete.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it