Journal article
Full acoustic analogy of linear noise in unbounded underwater environments
- Abstract:
- Conventional acoustic analogy methods are often prohibitively expensive in computational resources when simulating far-field noise in underwater environments and are unable to handle noise in heterogeneous media. The Fully Acoustic Analogy (FAA) method overcomes this limitation by combining acoustic analogy with wave propagation modeling, thereby providing a more efficient solution for far-field noise prediction. This study presents complete implementation and extension of the FAA three-stage workflow within the open-source Computational Fluid Dynamics (CFD) platform OpenFOAM: (1) Large-eddy simulation (LES) with the WALE subgrid-scale model to resolve unsteady flow field; (2) By leveraging the sound propagation characteristics in water, we simplified and improved the Ffowcs-Williams and Hawkings (FW-H) equations into the RTFWH equation for computing linear noise; (3) Development of a wave-equation-based propagation solver with advective non-reflective boundary conditions for acoustic wave propagation in unbounded domains. Validation cases (cube, sphere and propeller) demonstrate that FAA accurately reproduces FW-H predicted temporal/frequency-domain acoustic pressure characteristics while excelling in far-field directivity analysis. The noise attenuation follows the expected transition from 1/r² (near-field source-dominated) to 1/r (far-field source-dominated) scaling, when propagating in a heterogeneous density field, sound pressure exhibits a positive correlation with density. with demonstrated robustness across varying Reynolds numbers and geometries. This work provides an framework for rapid Underwater Radiated Noise (URN) assessment in marine applications and provides a foundation for far-field propagation studies of nonlinear noise.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Publisher copy:
- 10.1016/j.ast.2026.111874
Authors
+ Science and Technology Department of Sichuan Province
More from this funder
- Funder identifier:
- https://ror.org/04323m874
- Grant:
- 2025YFHZ0038
- Programme:
- Sichuan Provincial Science and Technology Support Program
+ Ministry of Education of the People's Republic of China
More from this funder
- Funder identifier:
- https://ror.org/01mv9t934
- Grant:
- 2682025XJ009
- 2682025CX159
- Programme:
- Fundamental Research Funds for the Central Universities
+ National Natural Science Foundation of China
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- Funder identifier:
- https://ror.org/01h0zpd94
- Grant:
- 52101374
- 52471351
- Publisher:
- Elsevier
- Journal:
- Aerospace Science and Technology More from this journal
- Volume:
- 174
- Article number:
- 111874
- Publication date:
- 2026-02-14
- Acceptance date:
- 2026-02-07
- DOI:
- ISSN:
-
1270-9638
- Language:
-
English
- Keywords:
- Pubs id:
-
2381974
- Local pid:
-
pubs:2381974
- Deposit date:
-
2026-04-30
- ARK identifier:
Terms of use
- Copyright holder:
- Elsevier Masson SAS.
- Copyright date:
- 2026
- Rights statement:
- ©2026 Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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