MULTI-WHEELED COMBAT VEHICLE MODELING ON RIGID AND SOFT TERRAIN
Bibliographic record
Abstract
<title>ABSTRACT</title> <p>Multi-wheeled off-road vehicles performance depends not only on the total engine power but also on its distribution among the drive axles/wheels. In this paper, a combat vehicle model was developed to examine dynamic performance on rigid and soft terrain. The vehicle dynamics is validated on rigid road against published measured data. Also non-linear tire look-up tables for rigid and soft terrain were constructed based on developed three-dimensional non-linear Finite Element Analysis off-road tire using PAM-CRASH. The measured and predicted results are compared on the basis of vehicle steering, yaw rates and accelerations using published US Army validation criteria.</p> <p>The validated combat vehicle model then used to study vehicle lane-change 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.</p>
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".