Towards the Prediction of the Underwater Acoustic Footprint of Offshore Wind Turbines
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The rapid deployment of large offshore wind farms has raised growing concerns regarding the transmission of aerodynamic noise into the marine environment. While aerodynamic noise is the dominant source in modern wind turbines, its underwater propagation and potential impacts on marine species remain poorly understood. Our predictions show non-negligible underwater footprint for large newly developed turbines and farms. Here, we introduce the development of the high-order solver HORSES3D, a high-order discontinuous Galerkin spectral element method (DGSEM) solver that resolves the incompressible Navier–Stokes equations coupled with an energy-stable Cahn–Hilliard formulation to accurately capture the air–water interface. This fully coupled framework enables the direct simulation of aeroacoustic wave generation, transmission across the free surface, and underwater propagation. HORSES3D is designed for extreme-scale computing and is ported to GPUs, allowing simulations with millions of degrees of freedom. By integrating blade-resolved or actuator-lines, atmospheric turbulence and free-surface dynamics, our approach provides a pathway toward predictive, farm-scale assessments of underwater noise. The resulting methodology supports the development of acoustically informed turbine designs, wind farm layouts, and operational strategies, contributing to truly sustainable offshore wind energy deployment.
