Wheelbase Filtering and Characterization of Road Profiles for Vehicle Dynamics
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
Random road profiles and wheelbase filtering, both of which strongly affect vehicle dynamic performance characteristics, have been explored in many studies. These studies invariably focused on either characterizing road roughness or vehicle dynamics considering wheelbase filtering effect. No effort, however, has been attempted to characterize road roughness profiles upon considering vehicle wheelbase filtering effect, and then to investigate their combined roles on vehicle dynamic responses. In this study, characteristics of different random road profiles are investigated upon considering wheelbase filtering effect. Two vehicle models, including quarter-car and pitch-plane models, are then employed to analyze the combined influence of random road roughness and wheelbase filtering on vehicle dynamics. The simulation results reveal the significant difference between the characteristics of random road profiles with and without wheelbase filtering effect. The results further demonstrate that wheelbase filtering has a positive effect on vehicle vertical ride, with a negligible or small compromise on suspension travel and dynamic tire deflection.
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 | 0.000 | 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 | 0.000 |
| 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