Journal
CHAOS SOLITONS & FRACTALS
Volume 150, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2021.111105
Keywords
Acoustic propagation; Wave equation; Stochastic equation; Ocean nonlinearity
Categories
Funding
- National Nature Science Foundation of China [61671386, 61771401, 61901385]
- Major State Basic Research Development Program of China [2016YFC1400204]
- Shaanxi Project for Distinguished Young Scholars
- Fundamental Research Funds for the Central Universities
- Research Funds for interdisciplinary sub-ject in Northwestern Polytechnical University , China
- Russian Federation Govern-ment [075-15-2019-1885]
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This study formulates a mathematical model to describe the complex variation of underwater propagating acoustic signals, presenting a perturb-coefficient nonlinear propagation equation and analyzing initial and boundary conditions to obtain solutions. The model is proven effective through simulations and suitable for various underwater circumstances.
The principle of underwater acoustic signal propagation is of vital importance to realize the digital ocean. However, underwater circumstances are becoming more complex and multi-factorial because of raising human activities, changing climate, to name a few. For this study, we formulate a mathematical model to describe the complex variation of underwater propagating acoustic signals, and the solving method are presented. Firstly, the perturb-coefficient nonlinear propagation equation is derived based on hydrodynamics and the adiabatic relation between pressure and density. Secondly, physical elements are divided into two types, intrinsic and extrinsic. The expression of the two types are combined with the perturb-coefficient nonlinear propagation equation by location and stochastic parameters to obtain the stochastic nonlinear differential propagation model. Thirdly, initial and boundary conditions are analyzed. The existence theorem for solutions is proved. Finally, the operator splitting procedure is proposed to obtain the solution of the model. Two simulations demonstrate that this model is effective and can be used in multiple circumstances. (c) 2021 Elsevier Ltd. All rights reserved.
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