On nonlinear yaw–roll–pitch model of the dynamics of log hauling trucks
Bibliographic record
Abstract
A full nonlinear yaw–roll–pitch model of the dynamics of log hauling trucks is developed based on Kane's equations. All the joint stiffnesses, suspension springs and dampers, and the vertical compliance of the tyres are considered in the model. The relationships amongst the articulation angles between the vehicle units, the sliding length of the drawbar, and the bounce of the trailing unit at the pintle hook joint, relative to the leading unit, have been introduced into the governing equations of motion. The orthogonal complement array and the zero eigenvalue method are used to deal with the closed–loop constraint equation. The numerical results for directional responses of the system are checked against measured responses in field tests. A comparison of the results of the yaw–roll–pitch and a nonlinear yaw model is also carried out. The sensitivity of the handling performance due to changes in the magnitude of the mass and the location of the mass centre of the payload and the stiffness and cornering characteristics of the tyres are investigated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".