Multifunction switching by a flat structurally tunable acoustic metasurface for transmitted waves

In this paper a flat structurally tunable acoustic metasurface is constructed based on the helical unit cell. The length of the acoustic channel can be tuned by the screw-in depth of the helix. Accordingly, the wave phase for the transmitted acoustic wave can be tuned and the wavefront can be manipulated. Then multifunctions such as anomalous refraction, point focusing, beam focusing and self-bending can be realized and switched just by screwing in or out the helixes. At the same time, the broadband operating frequency is also realized. The experiments for anomalous refraction and point focusing are also performed, and the results show that the designed metasurface is effective. The present studies have important applications in dynamic manipulation of acoustic waves by metasurfaces.

Tunable Fluid-Type Metasurface for Wide-Angle and Multifrequency Water-Air Acoustic Transmission

Efficient acoustic communication across the water-air interface remains a great challenge owing to the extreme acoustic impedance mismatch.Few present acoustic metamaterials can be constructed on the free air-water interface for enhancing the acoustic transmission because of the interface instability.Previous strategies overcoming this difficulty were limited in practical usage,as well as the wide-angle and multifrequency acoustic transmission.Here,we report a simple and practical way to obtain the wide-angle and multifrequency water-air acoustic transmission with a tunable fluid-type acoustic metasurface(FAM).The FAM has a transmission enhancement of acoustic energy over 200 times,with a thickness less than the wavelength in water by three orders of magnitude.The FAM can work at an almost arbitrary water-to-air incident angle,and the operating frequencies can be flexibly adjusted.Multifrequency transmissions can be obtained with multilayer FAMs.In experiments,the FAM is demonstrated to be stable enough for practical applications and has the transmission enhancement of over 20 dB for wide frequencies.The transmission enhancement of music signal across the water-air interface was performed to demonstrate the applications in acoustic communications.The FAM will benefit various applications in hydroacoustics and oceanography.

Tunable Fluid-Type Metasurface for Wide-Angle and Multifrequency Water-Air Acoustic Transmission

Efficient acoustic communication across the water-air interface remains a great challenge owing to the extreme acoustic impedance mismatch.Few present acoustic metamaterials can be constructed on the free air-water interface for enhancing the acoustic transmission because of the interface instability.Previous strategies overcoming this difficulty were limited in practical usage,as well as the wide-angle and multifrequency acoustic transmission.Here,we report a simple and practical way to obtain the wide-angle and multifrequency water-air acoustic transmission with a tunable fluid-type acoustic metasurface(FAM).The FAM has a transmission enhancement of acoustic energy over 200 times,with a thickness less than the wavelength in water by three orders of magnitude.The FAM can work at an almost arbitrary water-to-air incident angle,and the operating frequencies can be flexibly adjusted.Multifrequency transmissions can be obtained with multilayer FAMs.In experiments,the FAM is demonstrated to be stable enough for practical applications and has the transmission enhancement of over 20 dB for wide frequencies.The transmission enhancement of music signal across the water-air interface was performed to demonstrate the applications in acoustic communications.The FAM will benefit various applications in hydroacoustics and oceanography.

Boundary integrated neural networks and code for acoustic radiation and scattering

This paper presents a novel approach called the boundary integrated neural networks(BINNs)for analyzing acoustic radiation and scattering.The method introduces fundamental solutions of the time-harmonic wave equation to encode the boundary integral equations(BIEs)within the neural networks,replacing the conventional use of the governing equation in physics-informed neural networks(PINNs).This approach offers several advantages.First,the input data for the neural networks in the BINNs only require the coordinates of“boundary”collocation points,making it highly suitable for analyzing acoustic fields in unbounded domains.Second,the loss function of the BINNs is not a composite form and has a fast convergence.Third,the BINNs achieve comparable precision to the PINNs using fewer collocation points and hidden layers/neurons.Finally,the semianalytic characteristic of the BIEs contributes to the higher precision of the BINNs.Numerical examples are presented to demonstrate the performance of the proposed method,and a MATLAB code implementation is provided as supplementary material.