Acoustics and Heat Transfer Characteristics of Piezoelectric Driven Central Orifice Synthetic Jet Actuators
Bibliographic record
Abstract
Growth in computational capacity combined with a decrease in the size of digital devices has led to increasing demand for more active and efficient cooling of electronics. In this study, an experimental investigation into two different sizes of central orifice Synthetic Jet Actuators (SJAs) is conducted to evaluate their heat transfer as well as noise generation characteristics. Two SJAs (40 mm and 20 mm) are examined, covering a distinct span of frequencies ranging from low to medium (<5500 Hz) in regards to the effect of SJA size over performance. The SJAs’ disk deflection, structural frequency, and jet exit velocity were measured to fully characterize the jet performance. The maximum Nusselt number for the largest SJA was 3 times more than the smallest SJA, where the evaluation of stroke length suggests no effective synthetic jet formation for the smallest SJA. The noise from the SJAs was measured in an anechoic chamber using three microphones, Fast Fourier Transform (FFT) of the sound pressure levels provide contributions to different tones in the resulting noise. 1/3 Octave Constant Percentage Bandwidth (CPB) analysis was performed to identify the frequency bands making the largest contribution to the noise. The largest SJA showed the highest heat transfer at acceptable noise levels during the operation below resonance frequency.
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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 | 0.001 | 0.001 |
| 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 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".