Large-Deflection Effect on Thermoelastic Dissipation of Microbeam Resonators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In real applications, beam resonators in MEMS/NEMS often vibrate beyond the linear regime. The present paper aims to study the effect of large-deflection on thermoelastic dissipation of doubly-clamped microbeam resonators. Detailed formulas are derived for quality (Q-) factor due to thermoelastic dissipation which depends on the amplitude of vibration deflection. Under adiabatic or isothermal surface thermal conditions, the nonlinear effect of large-deflection on thermoelastic dissipation is demonstrated with a comparison to the results based on linearized small deflection vibration. Our results show that thermoelastic dissipation is reduced monotonically with increasing amplitude of vibration deflection under adiabatic surface condition, while thermoelastic dissipation is increased monotonically with increasing amplitude under isothermal surface condition. Under both adiabatic and isothermal surface conditions, the large-deflection effect on thermoelastic dissipation becomes more significant for higher vibration frequencies than lower ones. For the first time to the best of our knowledge, these results reveal that large deflection has a significant effect on thermoelastic dissipation of microbeam resonators and surface thermal condition plays an important role in the large-deflection effect. Keywords: Large deflectionMicrobeamsNon-linear vibrationThermoelastic dissipation ACKNOWLEDGMENT The authors gratefully acknowledge the financial support of the Natural Science and Engineering Research Council of Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it