Non-uniform Pressure Distribution in Draw-Bend Friction Test and its Influence on Friction Measurement
Bibliographic record
Abstract
From various draw‐bend friction tests with sheet metals at lubricated conditions, it has been unanimously reported that the friction coefficient increases as the pin diameter decreases. However, a proper explanation for this phenomenon has not been given yet. In those experiments, tests were performed for different pin diameters while keeping the same average contact pressure by adjusting applied tension forces. In this paper, pressure profiles at pin/strip contacts and the changes in the pressure profiles depending on pin diameters are investigated using finite element simulations. To study the effect of the pressure profile changes on friction measurements, a non‐constant friction model (Stribeck friction model), which is more realistic for the lubricated sheet metal contacts, is implemented into the finite element code and applied to the simulations. The study shows that the non‐uniformity of the pressure profile increases and the pin/strip contact angle decreases as the pin diameter decreases, and these phenomena increase the friction coefficient, which is calculated from the strip tension forces using a conventional rope‐pulley equation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".