Electrical Power Generation Using Dynamic Piezoelectric Shear Deformation Under Friction
Bibliographic record
Abstract
Abstract A new electrical power generation device based on high-frequency dynamic piezoelectric shear deformation under friction is developed. During the operation of a moving plate compressed and sliding on the top of a piezoelectric patch with constant velocity, dynamic shear deformation of the elastic piezoelectric patch is excited by periodic friction force and status (sliding and stick) variation. The dynamic piezoelectric shear strain can then generate continuous electrical power for energy absorbing and harvesting applications. The design of the piezoelectric couple device is first provided, and its mechanism, dynamic response and electric power generation under friction are described by a detailed iteration model. By comparing with previous experimental results, the accuracy of the proposed model is proven. Through numerical studies, the influences of the equivalent mass of the system, the velocity of the sliding object, the static friction coefficient and its lower limit, as well as the friction force delay rate on the power generation are obtained and discussed. The numerical results show that with the proposed design, up to 50-Watt maximum electrical power could be generated by a piezoelectric patch with a dimension of $$20\times 2\times 6$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>20</mml:mn> <mml:mo>×</mml:mo> <mml:mn>2</mml:mn> <mml:mo>×</mml:mo> <mml:mn>6</mml:mn> </mml:mrow> </mml:math> cm under continuous friction with the moving plate at the velocity of 15 m/s. The possible bi-linear elastic stiffness variation of the system is also introduced, and the threshold of bi-linear elastic deformation, where the system stiffness changes, can be optimized for obtaining the highest power generation.
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How this classification was reachedexpand
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 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".