Abstract
Rapid execution is required in operation-oriented applications in underwater acoustic modelling. In this paper, the GPU graphic pipeline is used to accelerate the calculation of high-resolution sound field image in the normal mode model of underwater acoustic propagation. The computer times of the proposed graphic pipeline method, the MATLAB code, and the C# code are compared for a stratified shallow water waveguide using the KRAKEN model at different frequencies. The research validates that the graphic pipeline method outperforms the classic CPU-based methods in terms of execution speed at the frequencies where the eigenvalue equation in normal mode models can be solved.
Highlights
Underwater acoustics entails the development and employment of acoustical methods to image underwater features, to communicate information via the oceanic waveguide, or to measure oceanic properties [1]
Solving the time-varying wave equation produces time-domain methods, such as finite difference method (FDM), finite element method (FEM), and boundary element method (BEM), while solving the Helmholtz equation assuming that density and sound speed of sea water are independent of time produces frequency-domain method, such as normal mode method (NM), parabolic equation (PE) method, and ray theory (RT) method [9]. e 2D Helmholtz equation in a stratified medium with depth z and horizontal distance r is as follows: z zp r +
Equation (6) is solved by the function “eig (A)” in MATLAB, and the eigenvalues and eigenvectors are stored as a binary file as the input of the sound field image module
Summary
Underwater acoustics entails the development and employment of acoustical methods to image underwater features, to communicate information via the oceanic waveguide, or to measure oceanic properties [1]. Underwater acoustic models analytically or numerically predict the propagation of sound waves in the ocean by translating our physical understanding of sound into mathematical formulas solvable by computers. Research-oriented applications are performed in laboratory conditions where the available computing platform is powerful, so accuracy is critical and computer time is not important, such as the design of sonar systems. Input parameters of these applications are usually detailed, so the marine environment needs to be finely measured. Operation-oriented applications are executed in demanding conditions where computing power is limited and a quick decision to the current situation is required, such as fleet operations or underwater acoustic communication. It is usually not feasible to perform fine measurement of the marine environment in demanding conditions, so the input parameters of operation-oriented applications are not as detailed as research-oriented applications
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