Continuously Differentiable Stick-Slip Friction Model with Applications to Cable Simulation Using Nonlinear Finite Elements
Bibliographic record
Abstract
This paper presents a continuously differentiable friction model based on the Quinn regularization of the Coulomb model in order to improve numerical performance for simulating dynamic systems using implicit ODE solvers. The implementation of the friction model for simulations of cable-pulley and cable-winch contact is demonstrated using the nonlinear Absolute Nodal Coordinate Formulation. Frictional contact between the cable and a dynamic surface is implemented using a Lagrange multiplier formulation. Examples of simple a capstan and a motorized pulley system are provided to demonstrate the stick-slip behavior of the model and the performance improvement over the original Quinn model, respectively. Using the ODE solver ode15s, the computation time was reduced by factors of 4.5 to 18.8 depending on the model parameters. The proposed model can be used to model and verify the behavior of dynamics systems in control applications.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".