Multi-Wheeled Combat Vehicle Maneuverability on Rigid and Soft Terrain
Bibliographic record
Abstract
The dynamic performance of multi-wheeled off-road vehicles on rigid and soft terrain was developed using multi-body dynamics software and validated against measured data. Non-linear tire look-up tables for rigid and soft terrain obtained from three-dimensional non-linear Finite Element Analysis (FEA) off-road tire models developed using PAMCRASH, were used in the simulation. The predictions of the vehicle handling characteristics and transient response during lane change on rigid road at different vehicle speeds were compared with field tests results. Measured and predicted results are compared on the basis of vehicle steering, yaw rates and accelerations. Published US Army validation criteria have been used to validate simulations. The combat vehicle model was used to study vehicle lanechange maneuverability on rigid and soft terrain at different speeds and powertrain configurations. This comparison showed the importance of having active torque distribution system on soft terrain especially at high speeds.
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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 | 0.000 | 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 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".