Multileaf Spring Model and Its Behaviour in a Tandem Bogie Layout
Bibliographic record
Abstract
The utilization of independent suspension is rising. For a very specific conditions, the dependent suspension types are still preferred, mainly in case of heavier trucks. Ordinary leaf spring material-steel is being replaced by a variety of composite materials. For the dynamic simulation of the vehicle, the greater importance than a material type, lies in the layout of the suspension. The tandem bogie layout of the multileaf spring suspension has many differences in its behaviour in comparison with ordinary layout-set of two separated multileaf springs allocated to one axle. In the first part of the paper, these differences are listed and explained-mainly the ability of load sharing between the axles. The second part deals with specific aspects of the FEM model, along with the necessary analytical background. The third part consists of various simulation cases with different initial conditions-different constrains, pretension and spring as tyre stiffness. In the last part, the effect of the aforementioned conditions are evaluated and commented. The variations of the hysteresis loops, in force-displacements characteristics, along with derived linear stiffness's and its behaviour are recommended to be understood for additional application. Therefore, the conclusions are drawn for further utilization of gathered data for the full vehicle simulation.
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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".