Tripod Dynamics and Its Inertia Effect
Bibliographic record
Abstract
In this paper the tripod dynamics and its inertia effect is studied. The tripod design is becoming popular for the development of parallel kinematic machines (PKMs). The combination of a tripod with a gantry system forms a hybrid machine that offers the advantages from both serial and parallel structures. The tripod dynamics under study includes the mass of the moving platform as well as those of the legs. The natural orthogonal complement method is applied to derive the dynamic equations. The inertia effect of the moving platform and the legs is investigated in terms of two parameters, namely, the ratio of the total leg mass to the mass of the moving platform, and the velocity of the moving platform. The dynamic equations are separated by three terms, inertia, coupling, and gravity. Quantitative studies are carried out by simulation to examine how the two parameters affect the three respective terms. Based on the simulation results, the dynamic equations can be simplified by retaining the dominant terms while neglecting less significant ones. The simplified dynamic equations provide an efficient model for design and control of tripods.
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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 | 0.001 | 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".