Modeling Of Structural And Environmental Effects On Microelectromechanical (Mems) Vibratory Gyroscopes
Bibliographic record
Abstract
In this paper we investigate the effects of stiffness, damping and temperature on the performance of a MEMS vibratory gyroscope.The stiffness and damping parameters are chosen because they can be appropriately designed to synchronize the drive and sense mode resonance to enhance the sensitivity and stability of MEMS gyroscope.Our results show that increasing the drive axis stiffness by 50% reduces the sense mode amplitude by ~27% and augments the resonance frequency by ~21%.The stiffness and damping are mildly sensitive to typical variations in operating temperature.The stiffness increases by 1.25%, while the damping decreases by 3.81%, when the temperature is raised from 0C to 45C.Doubling the damping reduces the oscillation amplitude by 80%, but ~1% change in the frequency.The predicted effects of stiffness, damping and temperature can be utilized to design a gyroscope for the desired operating condition.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".