Bibliographic record
Abstract
In the development of the equations of motion of a rigid multibody system, particularly vehicles, it is quite common to linearize the equations after they are derived, or even to ignore the non-linear terms from the outset. When doing so, the tangent stiffness matrix, i.e., the stiffness term that results from preload of the system rather than physical flexibility, is often ignored. The motion analysis of preloaded mechanical systems, e.g., the ride quality analysis of vehicle suspensions, may be significantly altered by this omission. Explicit expressions for the tangent stiffness matrix for a few of the common constraint types, including the revolute joint and the rolling wheel, are derived in this article. These expressions are coded into software and included in an open-source linear equation of motion generator for rigid multibody systems. A sample automotive suspension system is analysed, comparing the results with and without the tangent stiffness matrix effects; additionally, a benchmark solution is developed using a commercial multibody dynamics code. The results provide confirmation of the significance of the tangent stiffness effect on motion analysis and correlate well with non-linear transient solutions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".