Static and Dynamic Analysis of a Bistable Micro-Actuator
Bibliographic record
Abstract
The static response of an electrostatic micro-catilever beam has been obtained by using Galerkin’s method. To make the system bi-stable, a controller has been added and the static response profile is presented using a multi-mode model for the beam. The number of mode shapes leading to convergence has been studied. The softening effect of adding more mode shapes has been investigated along with the effect of changing the system parameters on the static response. Decreasing the controller gain has been found to widen the voltage range of the bi-stability region and increasing the sensor amplification factor is shown to push the upper equilibrium point away from pull-in. Properly choosing these parameters can adjust the range of voltage for bi-stability. By doing a linearization about the stable fixed points, we also found the two natural frequencies for each stable equilibrium point. Finally, we have found the dynamic response of the bistable system using one- and three-mode-models. The basins of attraction for each stable fixed point and the exchange of energy between the two potential energy wells (equilibrium points), are demonstrated.
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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) | 0.003 | 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".