Stress Analysis of the Multi‐Layered System of a Truck Tire
Bibliographic record
Abstract
Abstract In this paper, a nonlinear finite element tire model is developed as an effective fast modeling approach to analyze the stress fields within a loaded tire structure, with the contact patch geometry and contact pressure distribution in the tire‐road interface as functions of the normal load and the inflation pressure. The model considers the geometry and orientations of the cords in individual layers and the stacking sequence of different layers in the multi‐layered system to predict the interply interactions in the belts and carcass layers. The study incorporates nearly incompressible property of the tread rubber block and anisotropic material properties of the layers. The analysis is performed using ANSYS software, and the results are presented to describe the influence of the normal load on the various stress fields and contact pressure distributions. The computed footprint geometry is qualitatively compared with the measured data to examine the validity of the model. It is concluded that the proposed model can provide reliable predictions about the three‐dimensional stress and deformation fields in the multi‐layered system and the contact pressure distribution in the tire‐road interface.
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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) | 0.000 | 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) | 0.001 | 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 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".