Abstract
During the optimization phase of a wave energy converter (WEC), it is essential to be able to rely on a model that is both fast and accurate. In this regard, Computational Fluid Dynamic (CFD) with Reynolds Averaged Navier–Stokes (RANS) approach is not suitable for optimization studies, given its computational cost, while methods based on potential theory are fast but not accurate enough. A good compromise can be found in boundary element methods (BEMs), based on potential theory, with the addition of non-linearities. This paper deals with the identification of viscous parameters to account for such non-linearities, based on CFD-Unsteady RANS (URANS) analysis. The work proposes two different methodologies to identify the viscous damping along the rotational degree of freedom (DOF) of pitch and roll: The first solely involves the outcomes of the CFD simulations, computing the viscous damping coefficients through the logarithmic decrement method, the second approach solves the Cummins’ equation of motion, via a Runge-Kutta scheme, selecting the damping coefficients that minimize the difference with CFD time series. The viscous damping is mostly linear for pitch and quadratic for roll, given the shape of the WEC analysed.
Highlights
Developing efficient, cost competitive and survivable wave energy converters (WECs), has proven, in the last years, to be a challenging task [1,2,3]
Computational Fluid Dynamic (CFD) with Reynolds Averaged Navier–Stokes (RANS) approach is not suitable for optimization studies, given its computational cost, while methods based on potential theory are fast but not accurate enough
The work proposes two different methodologies to identify the viscous damping along the rotational degree of freedom (DOF) of pitch and roll: The first solely involves the outcomes of the CFD simulations, computing the viscous damping coefficients through the logarithmic decrement method, the second approach solves the Cummins’ equation of motion, via a Runge-Kutta scheme, selecting the damping coefficients that minimize the difference with CFD time series
Summary
Developing efficient, cost competitive and survivable wave energy converters (WECs), has proven, in the last years, to be a challenging task [1,2,3]. The linearization is always referred to the operating point In many applications this is a reasonable assumption, since the working condition is not far respect a specific setpoint; in contrast, in the case of wave energy conversion, the objective is to drive the system as far away from equilibrium as possible, in order to maximize the produced energy. This is likely to excite nonlinear dynamics, resulting in non-representative linear models, which usually underestimate energy losses and overestimate the productivity of the WEC [7]
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