Author(s): Arun Kamath; Hans Bihs; Øivind A. Arntsen
Keywords: Oscillating water column; CFD; Wave energy
Abstract: An Oscillating Water Column (OWC) device is a wave energy converter that can be deployed in shallow coastal waters to convert incident wave energy into electrical energy. The installation of an OWC device in the coastal region has consequences on the waves incident on the coast as it reduces the energy content of the waves that are headed towards the coastline. It can be used to meet dual objectives of generating clean energy and also coastal protection. In this scenario, the flow around an OWC device has an influence on the coastal dynamics and on the performance of the device itself. Thus, it is essential to obtain a good understanding of the influence of installing an OWC device in a coastal environment. This paper uses a CFD model to investigate the hydrodynamics of an OWC device placed in a numerical wave tank and study the flow features around the device. The free surface motion inside the chamber, velocity of the free surface motion and the chamber pressure are studied. A 2D simulation is first carried out and the numerical results are compared with experimental observations. Further, 3D simulations are carried out and difference in the hydrodynamics of the device in 3D simulations in comparison to 2D simulations is studied. This provides insight into the hydrodynamics of the device taking into account the effect of the side walls and the interaction of the device with the incident waves in a realistic environment. The numerical model uses the Reynolds-Averaged Navier-Stokes equations to solve the fluid flow problem. The 5thorder conservative finite difference WENO scheme is used to discretize the convective terms and a 3rd-order TVD Runge-Kutta scheme is employed for time advancement. Pressure discretization is carried out using Chorin’s projection method and the Poisson pressure equation is solved using a pre-conditioned Bi CGStab algorithm. A sharp representation of the free surface is obtained using the level set method. Turbulence modeling is carried out using the k-ωmodel. Computational performance of the numerical model is improved by parallel processing using the MPI library.