Dynamic characteristics of planar linear array deployable structure based on scissor-like element with differently located revolute clearance joints
Bibliographic record
Abstract
This paper comprehensively investigates the parametric effects of differently located revolute clearance joints on the dynamic behavior of planar deployable structure based on scissor-like element. Considering the real physical mechanical joints, the normal and the tangential forces in the revolute clearance joints are respectively modeled using Flores contact-force model and LuGre friction model. The resulting forces and moments are embedded in the equations of motion of the scissor deployable structure for accurately describing the effect of joint clearance and governing the dynamic response of this structure. The effects of the main parameters such as the location of the clearance joint, the clearance size and the number of clearance joints on the dynamic characteristics of a multibody mechanical system have been numerically evaluated, and the results indicate that joints at different locations in a mechanical system have different sensitivities to the clearance size, and the more sensitive joint should be controlled to reduce the nonlinear behavior of this structure. Also, it can be concluded that the motion in one revolute clearance joint will affect the motion in the other clearance joints and the dynamic interaction of clearance joints is the important source of structural behavior change. Therefore, in order to accurately predict the dynamic responses of the mechanical system, the clearance effect of each joint on the multibody system should be investigated and understood.
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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 | 0.000 |
| 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) | 0.001 | 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".