Acoustic energy generation of “air-jet” instruments: Energy transfer between jet oscillation and acoustic field

2016 ◽  
Vol 140 (4) ◽  
pp. 3253-3253
Author(s):  
Kin'ya Takahashi ◽  
Sho Iwagami ◽  
Taizo Kobayashi ◽  
Toshiya Takami
Keyword(s):  
Energy Transfer ◽  
Acoustic Field ◽  
Energy Generation ◽  
Acoustic Energy ◽  
Air Jet ◽  
Jet Oscillation

Theoretical Estimation of the Acoustic Energy Generation and Absorption Caused by Jet Oscillation

2016 ◽  
Vol 85 (4) ◽  
pp. 044402 ◽  
Author(s):  
Kin’ya Takahashi ◽  
Sho Iwagami ◽  
Taizo Kobayashi ◽  
Toshiya Takami
Keyword(s):  
Energy Generation ◽  
Acoustic Energy ◽  
Theoretical Estimation ◽  
Jet Oscillation

Three-dimensional numerical analysis of acoustic energy transfer in air-jet instrument

2021 ◽  
Vol 149 (4) ◽  
pp. A68-A68
Author(s):  
Ryoya Tabata ◽  
Hiroko Midorikawa ◽  
Taizo Kobayashi ◽  
Ki’nya Takahashi
Keyword(s):  
Energy Transfer ◽  
Numerical Analysis ◽  
Three Dimensional ◽  
Acoustic Energy ◽  
Air Jet

Collective oscillations in bubble clouds

2011 ◽  
Vol 680 ◽  
pp. 114-149 ◽  
Author(s):  
ZORANA ZERAVCIC ◽  
DETLEF LOHSE ◽  
WIM VAN SAARLOOS
Keyword(s):  
Frequency Response ◽  
Acoustic Field ◽  
Low Frequency ◽  
Acoustic Energy ◽  
Viscous Damping ◽  
Edge States ◽  
Bubble Cloud ◽  
Collective Oscillations ◽  
The Individual ◽  
Bubble Oscillations

In this paper the collective oscillations of a bubble cloud in an acoustic field are theoretically analysed with concepts and techniques of condensed matter physics. More specifically, we will calculate the eigenmodes and their excitabilities, eigenfrequencies, densities of states, responses, absorption and participation ratios to better understand the collective dynamics of coupled bubbles and address the question of possible localization of acoustic energy in the bubble cloud. The radial oscillations of the individual bubbles in the acoustic field are described by coupled linearized Rayleigh–Plesset equations. We explore the effects of viscous damping, distance between bubbles, polydispersity, geometric disorder, size of the bubbles and size of the cloud. For large enough clusters, the collective response is often very different from that of a typical mode, as the frequency response of each mode is sufficiently wide that many modes are excited when the cloud is driven by ultrasound. The reason is the strong effect of viscosity on the collective mode response, which is surprising, as viscous damping effects are small for single-bubble oscillations in water. Localization of acoustic energy is only found in the case of substantial bubble size polydispersity or geometric disorder. The lack of localization for a weak disorder is traced back to the long-range 1/r interaction potential between the individual bubbles. The results of the present paper are connected to recent experimental observations of collective bubble oscillations in a two-dimensional bubble cloud, where pronounced edge states and a pronounced low-frequency response had been observed, both consistent with the present theoretical findings. Finally, an outlook to future possible experiments is given.

Simulating Ultrasound Piezoelectric Power Transfer in the Near Field and Experimental Validations

2021 ◽  
Vol 05 ◽  
Author(s):  
Ammar Mohammed ◽  
Changki Mo ◽  
John Miller ◽  
David Lowry ◽  
Jassim Alhamid
Keyword(s):  
Energy Transfer ◽  
Lead Zirconate Titanate ◽  
Near Field ◽  
Acoustic Power ◽  
Acoustic Energy ◽  
Transfer Efficiency ◽  
Ultrasonic Power ◽  
Power Transfer ◽  
Piezoelectric Energy ◽  
Power Transfer Efficiency

Background: Acoustic power transfer is a method for wireless energy transfer to implanted medical devices that permits a greater range of separation between transmitter and receiver than is possible with inductive power transfer. In some cases, short-distance ultrasonic power transfer may be employed; consequently, their operation may be complicated by the near-field aspects of piezoelectric acoustic energy transfer. Methods: A piezoelectric energy transfer system consisting of two lead zirconate titanate (PZT) transducers was analyzed in this work using a combination of experimental measurements and computer simulations. Results: Simulations using the COMSOL Software package showed good agreement with a measured output voltage as a function of the distance between and alignment of the transmitter and receiver with water as a medium. We also simulated how operating frequency affects power transfer efficiency at various distances between the transmitter and receiver and found reasonable agreement with experiments. We report model predictions for power transfer efficiency as a function of the thickness and diameter of the transmitter and receiver. Conclusion: The results show that with proper choice of parameters, piezoelectric systems can provide high power transfer efficiency in the near-field region.

scholarly journals Acoustic Energy Transfer by Friction Induced Vibrations

2017 ◽  
Vol 199 ◽  
pp. 1356-1361 ◽  
Author(s):  
G. Lacerra ◽  
F. Massi ◽  
E. Chatelet ◽  
E. Moulin
Keyword(s):  
Energy Transfer ◽  
Acoustic Energy

scholarly journals A System for Acoustic Field Measurement Employing Cartesian Robot

2016 ◽  
Vol 23 (3) ◽  
pp. 333-343 ◽  
Author(s):  
Maciej Szczodrak ◽  
Adam Kurowski ◽  
Józef Kotus ◽  
Andrzej Czyżewski ◽  
Bożena Kostek
Keyword(s):  
Acoustic Field ◽  
Energy Flow ◽  
Velocity Vector ◽  
Sound Pressure ◽  
Sound Field ◽  
Acoustic Energy ◽  
The Other ◽  
Object Shape ◽  
Movement Path ◽  
Optimum Path

AbstractA system setup for measurements of acoustic field, together with the results of 3D visualisations of acoustic energy flow are presented in the paper. Spatial sampling of the field is performed by a Cartesian robot. Automatization of the measurement process is achieved with the use of a specialized control system. The method is based on measuring the sound pressure (scalar) and particle velocity(vector) quantities. The aim of the system is to collect data with a high precision and repeatability. The system is employed for measurements of acoustic energy flow in the proximity of an artificial head in an anechoic chamber. In the measurement setup an algorithm for generation of the probe movement path is included. The algorithm finds the optimum path of the robot movement, taking into account a given 3D object shape present in the measurement space. The results are presented for two cases, first without any obstacle and the other - with an artificial head in the sound field.

Holographic mirrors for spatial ultrasound modulation in contactless acoustic energy transfer systems

2021 ◽  
Vol 119 (14) ◽  
pp. 144101
Author(s):  
Ahmed Sallam ◽  
Vamsi C. Meesala ◽  
Muhammad R. Hajj ◽  
Shima Shahab
Keyword(s):  
Energy Transfer ◽  
Acoustic Energy ◽  
Ultrasound Modulation

An Energy Boundary Element Formulation for Predicting the Acoustic Field Around a Vehicle at High Frequencies Due to Airborne Noise Sources

2003 ◽  
Author(s):  
Aimin Wang ◽  
Nickolas Vlahopoulos ◽  
Jason Zhu ◽  
Mike Qian
Keyword(s):  
Energy Density ◽  
Boundary Element ◽  
Acoustic Field ◽  
Test Data ◽  
Acoustic Energy ◽  
Element Formulation ◽  
Acoustic Intensity ◽  
Numerical Predictions ◽  
Airborne Noise ◽  
Acoustic Energy Density

An Energy Boundary Element Analysis (EBEA) formulation is presented for calculating sound radiation from a source with arbitrary shape at high frequency. The basic integral equation for the EBEA is derived including a half-space boundary condition. The time and frequency averaged acoustic energy density and acoustic intensity constitutes the primary variables of the new formulation, and the corresponding Green’s functions are derived. The governing equations for the EBEA are established and the numerical formulae for the coefficients of the system matrix, the acoustic energy density, and the acoustic intensity are derived using a Gaussian quadrature. The EBEA formulation and the corresponding numerical implementation are validated by comparing EBEA results to test data for the acoustic field around a vehicle that originates from an airborne noise source. Good correlation is demonstrated between numerical predictions and test data.

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