Graph theoretic modeling and analysis of multibody planar mechanical systems
Bibliographic record
Abstract
A methodology of modeling and analysis of planar mechanical systems is developed based on graph theoretic methods, with improvements in component models. The system model based on cutset and circuit topologies is used to derive a new hybrid cutset-circuit method of formulation of the equations of motion for planar systems. Computer-aided formulation is based on analysis of the substitution procedure mandated by the hybrid cutset-circuit formulation. A new graphical representation of the formulation process is introduced: substitution graphs. No special programming is needed for computer-aided formulation which can be achieved in a symbolic form using the off the shelf Maple symbolic mathematics system. Symbolic formulation requires only inputting the systems equations in an order and form as derived from the analysis of the hybrid formulation. An algorithm for symbolic formulation using Maple is given. A compact set of differential-algebraic equations results, which can be solved numerically. Some simple systems will result in closed-form solutions. A number of examples are given to illustrate the modeling and formulation. Numerical solutions are also given to demonstrate the effectiveness and correctness of the formulation procedure.
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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) | 0.001 | 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) | 0.003 | 0.001 |
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".