We present a numerical model based on the Smoothed Particle Hydrodynamics (SPH) method for the simulation of sea waves and and Wave Energy Converters (WECs). SPH is a Lagrangian and mesh-free method, that can easily deal with large deformations, free surfaces and interfaces. Unlike various approaches to the simulation of WEC that rely on analytical representations of the fluid, SPH is fully numerical, and therefore allows a full representation of the hydrodynamics of the problem.
In this work we study a setup for supplying electricity to an Unmanned Underwater Vehicle (UUV) by means of a WEC. A two-body point absorber WEC is considered, where a submerged heave plate is used to provide a reaction force to waves motion, as well as to serve as docking station for the UUV. This setup has been physically implemented and tested on field, providing a rich set of data.
An initial validation of the numerical model is performed against a laboratory model of a heave plate, oscillating in a tank of water. The controlled environment where the experiments are performed, and the driven motion of the plate, allow to gather a large variety of clean data, including hydrodynamic forces and visual representation of flow structures. For the latter, dye injections were used. The validation is done against reaction forces and generation and evolution of flow structures in proximity of the plate. From this initial study, an optimal SPH formulation is achieved, so to provide accurate and resolute results, and establish a compromise with the computational demand. Comparisons to laboratory observations and measurements showed a good level of agreement. Additionally, the numerical model is used to get further insights about the fluid-plate interaction, including velocity field and streamlines.
The SPH model is then applied to the whole field setup. For this scope, it is initially coupled to a FEM model for handling elastic bodies (cables and connections between parts of the system), and to a rigid bodies solver, to handle the WEC. Simulated and measured data, including motion of the devices, forces and generated power, are compared to measurements for different configurations of the setup. Expedients to reduce the complexity and computational load of the numerical model are introduced with this application and discussed. Finally, we show some examples of optimization of the system carried out using the numerical model.