Hydrodynamic Loads of the “Ningde No. 1” Offshore Aquaculture Platform Under Current-Only Conditions

This study investigates the hydrodynamic loads of “Ningde No. 1” offshore aquaculture under current-only conditions using a fluid–structure interaction (FSI) approach with the computational fluid dynamics (CFD) solver OpenFOAM. A porous-media-based model is applied to simulate net-induced drag, while the rigid framework is resolved using a large eddy simulation (LES) turbulence model. A comprehensive set of 350 CFD simulations is performed, with varying flow velocities, flow directions, draft depths, and existence of nets. The results reveal that the load on this fishing facility in the streamwise direction (Fx) increases monotonically with flow velocity, direction, and draft. The lateral (Fy) and vertical (Fz) loads exhibit non-linear trends, peaking at a specific flow direction (approximately 60°) and draft levels (around 11.5 m). The fishing nets substantially increase the streamwise load by up to 80%, while their influence on the lateral forces is dependent on submergence depth. To efficiently predict hydrodynamic loads without performing additional and lengthy CFD simulations, a physics-informed neural network (PINN) is trained using the simulated data. The PINN model is found able to accurately reproduce the hydrodynamic force across a wide range of current conditions, offering a practical and interpretable surrogate approach for structural design optimization and mooring system development in offshore aquaculture industry.