Automated tuning of a piezoelectric power harvesting cantilever beam via the application of an axial load
Bibliographic record
Abstract
This thesis deals with automatic tuning of piezoelectric power harvesters. A prototype was constructed to verify the effect of the application of an axial load on a cantilever beam and the effectiveness of increasing the power harvested from a piezoelectric beam via axial loading. It was shown, experimentally, that the natural frequency of a piezoelectric beam harvester can be changed over a range of 25Hz. From the experimental results it was shown that the power can increase up to seven times when tuned in comparison to unturned. Computer simulations were used to demonstrate a closed loop tuning system’s ability to apply an axial load effectively onto a piezoelectric cantilever beam in response to ambient vibrations. The closed loop tuning system is a viable option for tuning and can lead to increased power when applying the axial load suggested by the tuning system.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".