Experimental Study: Effect of Resonator Parameter Upon the End Correction for Quarter Wavelength Resonator Tube
Bibliographic record
Abstract
Acoustic resonators are fundamental in various engineering applications, from musical instruments to advanced sound filtering systems. Their ability to amplify and sustain specific frequencies has made them indispensable in modern technology. This study presents a comprehensive parametric investigation of acoustic resonators, aiming to identify the effect of parameter changes on the acoustical length and standing wave that significantly influence their performance and efficiency of acoustic energy harvesting design. The research methodology involves experimental analysis to explore the effects of various geometric on the resonator's acoustic end correction and standing wave. The study focuses on traditional Quarter wavelength resonators, and parameters such as resonator shape, size, length, and backplate thickness are systematically varied and studied. The findings of this parametric study provide valuable insights into the optimisation of acoustic resonators for energy harvesting purposes. The impact of parameters like tube length 30cm and diameter 8cm on standing wave is quantified, enabling engineers to tailor resonator designs to meet precise requirements. Other parameters are also vital in constructing a resonator tube that can deliver optimal output when considering other usage circumstances. Furthermore, novel design concepts that demonstrate improved performance compared to conventional resonators are proposed, expanding the possibilities for optimum output of acoustic energy harvesting systems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".