This research investigates the effects that geometry and control have on the absorption characteristics of active wavemakers and looks at the feasibility of modelling these wavemakers in commercial computational fluid dynamic software. This thesis presents the hydrodynamic coefficients for four different types of wavemakers. The absorption characteristics of these wavemakers are analysed using different combinations of control impedance coefficients. The effect of combining both geometry and control is then investigated. Results, quantifying the absorption characteristics are then presented. It is shown that the amount of absorption for a given paddle differs greatly depending on the choice of control coefficients used to implement complex conjugate control. Increased absorption can be achieved over a broader bandwidth of frequencies when the geometry of the wavemaker is optimised for one specific frequency and the control impedance is optimised for an alternate frequency. In conjunction to this theoretical study, a numerical investigation is conducted in order to verify and validate two commercial computational fluid dynamic codes' suitability to model the previously discussed absorbing wavemakers. ANSYS CFX and FLOW3D are used to model a physical wavemaker. Both are rigorously verified for discretisation errors and CFX is validated against linear wavemaker theory. Results show good agreement and prediction of the free surface close to the oscillating wavemaker, but problems with wave height attenuation and excessive run times were encountered.

The AOE Accumulated Ocean Energy Inc. (AOE) wave energy converter (WEC) is a cascaded pneumatic system, in which air is successively compressed through three point absorber devices on the way to shore; this air is then used to drive an electricity generator. To better quantify the performance of this device, this thesis presents a dynamically coupled model architecture of the AOE WEC, which was developed using the finite element solver ProteusDS and MATLAB/Simulink. This model is subsequently applied for the development and implementation of control in the AOE WEC. At each control stage, comprehensive power matrix data is generated to assess power production as a function of control complexity. The nature of the AOE WEC presented a series of novel challenges, centered on the significant residency time of air within the power take-off (PTO). As a result, control implementation was broken into two stages: passive and active control. The first stage, passive control, was realized as an optimization of eight critical PTO parameters with the objective of maximizing exergy output. After only 15 generations, the genetic algorithm optimization led to an increase of 330.4% over an initial, informed estimate of the optimal design, such that the annually-averaged power output was 29.37 kW. However, a disparity in power production between low and moderate energy sea-states was identified, which informed the development of an active control strategy for the increase of power production in low energy sea-states. To this aim, a recirculation-based control strategy was developed, in which three accumulator tanks were used to selectively pressurize and de-pressurize the piston at opportune times, thereby increasing the continuity of air throughput. Under the influence of active control, sea-states with significant wave heights between 0.75 m – 1.75 m, which on average encompass 55.93% of the year at the Amphitrite Bank deployment location, saw a 16.3% increase in energy production. / Graduate / 2018-08-18