Etude de l’effet des chaussées dégradées sur la consommation de carburant des véhicules et la sécurité des usagers de la route.
Bibliographic record
Abstract
RESUME : Le projet permet d’etudier de facon theorique l’effet de la degradation des chaussees sur la consommation de carburant des vehicules et l’energie necessaire au roulement. Une revue litteraire vient debuter le projet, ce qui permet de se familiariser avec les parametres prejudiciables a la consommation de carburant des vehicules, tels que l’uni routier, l’amplitude et la longueur d’onde d’une deformation. Il est egalement interessant de quantifier les pertes d’energie engendrees par le deplacement d’un vehicule. La suite du projet est portee sur des simulations dynamiques effectuees a l’aide de logiciels d’analyse adaptes que sont CarSim v.8.02 et ProVAL 3.0. Des profils typiques de surface de chaussees, generes par ordinateur, et reels, fournis par le Ministere des Transports du Quebec, sont analyses par les logiciels, puis compares et interpretes, en termes d’uni de la chaussee, de consommation de carburant et d’emissions de gaz a effet de serre, et d’energie necessaire au roulement. Le projet permet enfin de valider la fiabilite d’un logiciel de simulation pour determiner theoriquement, a moyen ou long terme, des balises rationnelles pour la revision des seuils de deficience des chaussees. //////////////////////////////////////////////////////////// TRADUCTION : This project studies the effect of the pavement degradation on vehicles fuel consumption and rolling energy using an academic approach. A literature review begins the project; it permits to gain more knowledge about parameters that influence vehicle fuel consumption. These parameters include, but are not limited to, evenness, distortion amplitude, and wavelength. It is also interesting to scale energy losses caused by the moving vehicle. The project uses computer simulations done with the CarSim v.8.02 and ProVAL 3.0 packages. Virtual profiles of pavements surface, created by computer algorithms, and real profiles, provided by the Ministere des Transports du Quebec, are analyzed and discussed while keeping evenness, fuel consumption and emissions of greenhouse gases, and rolling energy as the main focus of this report. Finally, the feasibility of using simulation software, for the medium and long run, to set new standards of pavements deficiency thresholds is also discussed.
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.
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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".