Study on Nonlinear Acoustic Waves in Stepped Acoustic Resonators.
Published In: Journal of Theoretical & Computational Acoustics, 2024, v. 32, n. 3. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Yu, Yanan; Chen, Qi; He, Wen; Zhou, Jie 3 of 3
Abstract
The problem of investigating the nonlinear acoustic waves in stepped acoustic resonators is treated theoretically. A perturbation scheme that combines the method of multi-scale expansion yields a set of coupled nonlinear ordinary differential equations for deriving an analytical model to describe the resonant oscillations. The nonlinear sound pressure in stepped resonator is predicted with accuracy up to the second-order terms of a small-amplitude parameter . The pressure amplitudes and waveforms at the closed end of stepped resonators with different size parameters are investigated by the derived analytical model and qualitatively compared with the measured results in experiment. The qualitative comparison of calculated and measured results shows good agreement. The results suggest that the sound pressure generated in stepped resonators with different size parameters may be very different. Not all stepped resonators can generate high-amplitude and low-distortion standing waves. The derived analytical model can be used to qualitatively study the nonlinear acoustic waves in stepped acoustic resonators and design suitable tube dimensions for resonant macrosonic synthesis. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Theoretical & Computational Acoustics. 2024/09, Vol. 32, Issue 3, p1
- Document Type:Article
- Subject Area:Science
- Publication Date:2024
- ISSN:2591-7285
- DOI:10.1142/S2591728524500014
- Accession Number:180000699
- Copyright Statement:Copyright of Journal of Theoretical & Computational Acoustics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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