A Regularized Contact Model for Multibody System Simulation
Bibliographic record
Abstract
Simulation of large-scale multibody systems with unilateral contacts requires formulations with which good computational performance can be achieved. The availability of many solver algorithms for Linear Complementarity Problems (LCP) makes the LCP-based formulations a good candidate for this. However, considering friction in contacts asks for new friction models compatible with this kind of formulations. Here, a new, regularized friction model is presented to approximate the Coulomb model, which allows to formulate the multibody system dynamics as a LCP with bounds. Moreover, a bristle approach is used to approximate the stiction force, so that it improves the numerical behaviour of the system and makes it able to handle redundancy coming from the friction interfaces. Several examples using a 3D wheel model has been carried out, and the proposed friction model shows a better approximation of the Coulomb model compared to other LCP-based formulations.
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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".