Modeling of a Complete Morphing Mechanism Covered by a Paneled Morphing Skin
Bibliographic record
Abstract
Abstract Presented in this paper is a method for modeling and simulation of a complete morphing mechanism. The said mechanism has a rigid panel morphing skin that morphs along with a driving mechanism. The said skin is made of segmented panels, inspired by fish scales. Since the gaps between these panels are undesirable, a gapless design is introduced in this paper by using shape-memory polymer (SMP) joints. This paper aims to solve two fundamental problems for the entire system: (1) motion control and (2) force control. The motion control is addressed through the kinematic modeling of two equations including (a) the passive rigid panels and (b) the passive rigid panels to the active mechanism. Force control is achieved through force modeling. This is to develop a relationship of the SMP deformations to the required actuator forces. The experiment is carried out to determine the SMP forces versus deformation, and simulations are conducted to investigate how a complete morphing mechanism behaves. It also reveals that the workspace and singularity of the original mechanism will change after covered by a morphing skin. The developed method sheds light on the design of a complete morphing mechanism.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".