Title | Numerical Study of Acoustic Propagation Characteristics in the Multi-scale Seafloor Random Media |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Han, K., Zhang, W., Liu, C. |
Conference Name | 2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP) |
Keywords | acoustic anisotropy, acoustic coupling, acoustic data, acoustic propagation characteristics, acoustic wave propagation, acoustic wave scattering, acoustic wave velocity, acoustic wave velocity dispersion, acoustic waves, Acoustics, complicated wave propagation, coupled PSM-BEM program, distributed multiscale random media, fluid flow, high frequency seafloor acoustics, Human Behavior, low frequency seafloor acoustics, Media, multi-scale, multiscale distribution, multiscale seafloor random media, Numerical models, numerical study, oceanographic techniques, pore space, pubcrawl, random media, Resiliency, Scalability, Sea floor, seafloor phenomena, sediments, two-dimensional PSM-BEM program, underwater acoustic propagation |
Abstract | There is some uncertainty as to the applicability or accuracy of current theories for wave propagation in sediments. Numerical modelling of acoustic data has long been recognized to be a powerful method of understanding of complicated wave propagation and interaction. In this paper, we used the coupled two-dimensional PSM-BEM program to simulate the process of acoustic wave propagation in the seafloor with distributed multi-scale random media. The effects of fluid flow between the pores and the grains with multi-scale distribution were considered. The results show that the coupled PSM-BEM program can be directly applied to both high and low frequency seafloor acoustics. A given porous frame with the pore space saturated with fluid can greatly increase the magnitude of acoustic anisotropy. acoustic wave velocity dispersion and attenuation are significant over a frequency range which spans at least two orders of magnitude. |
DOI | 10.1109/ICICSP50920.2020.9232061 |
Citation Key | han_numerical_2020 |