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An analytical theory is developed that describes acoustic microstreaming produced by the interaction of an oscillating gas bubble with a viscoelastic particle. The bubble is assumed to undergo axisymmetric oscillation modes, which can include radial oscillation, translation and shape modes. The oscillations of the particle are excited by the oscillations of the bubble. No restrictions are imposed on the ratio of the bubble and the particle radii to the viscous penetration depth and the separation distance, as well as on the ratio of the viscous penetration depth to the separation distance. Capabilities of the developed theory are illustrated by computational examples. The shear stress produced by the acoustic microstreaming on the particle surface is calculated. It is shown that this stress is much higher than the stress predicted by the formula of Nyborg, which is commonly used to evaluate the time-averaged shear stress produced by a bubble on a rigid wall.

Self-oscillations underlie many natural phenomena such as heartbeat, ocean waves, and the pulsation of variable stars. From pendulum clocks to the behavior of animal groups, self-oscillation is one of the keys to the understanding of synchronization phenomena and hence the collective behavior of interacting systems. In this study, we consider two closely spaced bubbles pulsating in the kHz range in response to ultrasonic excitation. A translational bouncing motion emerges from their interaction with a much lower frequency than the bubble pulsation frequency. Our analysis reveals that the observed bubble bouncing exhibits the main features of self-oscillation, such as negative damping and the emergence of a limit cycle. These results highlight unexpected nonlinear effects in the field of microbubbles and give insights into the understanding of synchronization in large bubble clouds.

Noise generated by wind turbines is significantly impacted by its propagation in the atmosphere. Hence, for annoyance issues an accurate prediction of sound propagation is critical to determine noise levels around wind turbines. This study presents a method to predict wind turbine sound propagation based on linearized Euler equations. We compare this approach to the parabolic equation method, which is widely used since it captures the influence of atmospheric refraction, ground reflection, and sound scattering at a low computational cost. Using the linearized Euler equations is more computationally demanding but can reproduce more physical effects as fewer assumptions are made. An additional benefit of the linearized Euler equations is that they provide a time-domain solution. To compare both approaches, we simulate sound propagation in two distinct scenarios. In the first scenario, a wind turbine is situated on flat terrain; in the second, a turbine is situated on a hilltop. The results show that both methods provide similar noise predictions in the two scenarios. We find that while some differences in the propagation results are observed in the second case, the final predictions for a broadband extended source are similar between the two methods.

A good understanding of wind turbine noise propagation is relevant to better measure the impact of turbines on the environment. In this study, we developed numerical simulations to study the impact of a 2D hill on the sound propagation for a turbine in non flat terrain. The simulations employed a propagation model derived from the linearized Euler equations, solved in a moving frame following the wavefront. The wind turbine noise was modeled using a point source approach. The flow structure in the atmospheric boundary layer and the wind turbine wake were obtained from large-eddy simulations. We find that the wind turbine wake acts as a waveguide that focuses sound propagation towards the ground. This effect is most pronounced for the flat terrain case and when the turbine is placed on the hill. The sound attenuation is more localized and closer to the turbine when the wind turbine is placed on the hilltop than in the flat case. As the wind speed increases, the sound focusing is observed closer to the turbine. For a turbine placed in front of the hill, the sound propagation is mainly determined by the flow over the hill. This demonstrates that terrain topography can have surprising effects on wind turbine noise propagation., Comment: 14 pages, 17 figures

Intraventricular vector flow mapping (iVFM) is a technique for retrieving 2-D velocity vector fields of blood flow in the left ventricle. This method is based on conventional color Doppler imaging, which makes iVFM compatible with the clinical setting. We have generalized the iVFM for a three-dimensional reconstruction (3D-iVFM). 3D-iVFM is able to recover three-component velocity vector fields in a full intraventricular volume by using a clinical echocardiographic triplane mode. As with the 2-D version, the method is based on the mass conservation, and free-slip boundary conditions on the endocardial wall. These mechanical constraints were imposed in a least-squares minimization problem that was solved through the method of Lagrange multipliers. We validated 3D-iVFM in silico in a patient-specific CFD (computational fluid dynamics) model of cardiac flow, and tested its feasibility in vivo on volunteers. In both in silico and in vivo investigations, the dynamics of the intraventricular vortex that forms during diastole was deciphered by 3D-iVFM. Our results tend to indicate that 3D-iVFM could provide full-volume echocardiographic information on left intraventricular hemodynamics from the clinical modality of triplane color Doppler., Comment: original paper