Applied Sciences | 2021

Prediction of Sound Scattering from Deep-Sea Targets Based on Equivalence of Directional Point Sources

 
 
 
 
 
 

Abstract


A fast prediction method is proposed for calculating the sound scattering of targets in the deep-sea acoustic channel by equating the sound scattering field of a complex elastic target to the acoustic field excited by a directional point source. In deep-sea conditions, the effects of the sea surface on the impedance characteristics of the elastic target surface can be ignored. Through the finite element simulation of the acoustic scattering of the target in the free field, the sound scattering field is equated to the radiation field of a directional point source. Subsequently, the point source is placed in the channel, and the acoustic ray method is used to calculate the distribution of the scattering field. On the basis of theoretical modelling, the method of obtaining the directional point source and the influence of the sea surface on the impedance of the scattering field are analysed. Subsequently, the proposed method is compared with the finite element method in terms of computational efficiency. The result shows that the method considers the multiple complex coupling effects between the elastic structure and marine environment. The influence of the boundary is approximately negligible when the distance from the ocean boundary to the elastic structure is equal to the wavelength. The method only performs finite element coupling calculation in the free field; the amount of mesh size is greatly reduced and the calculation efficiency is significantly improved when compared with the finite element calculation in the entire channel, the. The calculation time in the example can be reduced by more than one order of magnitude. This method organically combines the near-field calculation with acoustic ray theory and it can realise the rapid calculation of the large-scale acoustic scattering field in complex marine environments.

Volume 11
Pages 5160
DOI 10.3390/APP11115160
Language English
Journal Applied Sciences

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