This thesis presents the analytically predicted position, motion, attitude, power output and forces on Florida Atlantic University's (FAU) first generation ocean current turbine for a wide range of operating conditions. These values are calculated using a 7- DOF dynamics simulation of the turbine and the cable that attaches it to the mooring system. The numerical simulation modifications and upgrades completed in this work include developing a wave model including the effects of waves into the simulation, upgrading the rotor model to specify the number of blades and upgrading the cable model to specify the number of cable elements. This enhanced simulation is used to quantify the turbine's performance in a wide range of currents, wave fields and when stopping and starting the rotor. For a uniform steady current this simulation predicts that when the rotor is fixed in 1.5 m/s current the drag on the turbine is 3.0 kN, the torque on the rotor is 384 N-m, the turbine roll and pitch are 2.4º and -1.2º . When the rotor is allowed to spin up to the rotational velocity where the turbine produces maximum power, the turbine drag increases to 7.3 kN, the torque increases to 1482 N-m, the shaft power is 5.8 kW, the turbine roll increases to 9º and the turbine pitch stays constant. Subsequently, a sensitivity analysis is done to evaluate changes in turbine performance caused by changes in turbine design and operation. This analysis show, among other things, that a non-axial flow on the turbine of up to 10º has a minimal effect on net power output and that the vertical stable position of the turbine varies linearly with the weight/buoyancy of the turbine with a maximum variation of 1.77 m for each increase or decrease of 1 kg at a current speed of 0.5 m/s. / by Nicolas Vanrietvelde. / Thesis (M.S.C.S.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.

This thesis proposes a sensor approach for quantifying the hydrodynamic performance of Ocean Current Turbines (OCT), and investigates the influence of sensor-specific noise and sampling rates on calculated turbine performance. Numerical models of the selected sensors are developed, and then utilized to add stochastic measurement error to numerically-generated, non-stochastic OCT data. Numerically-generated current velocity and turbine performance measurements are used to quantify the relative influence of sensor-specific error and sampling limitations on sensor measurements and calculated OCT performance results. The study shows that the addition of sensor error alters the variance and mean of OCT performance metric data by roughly 7.1% and 0.24%, respectively, for four evaluated operating conditions. It is shown that sensor error results in a mean, maximum and minimum performance metric to Signal to Noise Ration (SNR) of 48.6% and 6.2%, respectively. / by Matthew T. Young. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.