Browsing by Author "Fontaine, Arnold"

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    Model Validation Using Experimental Measurements from the Garfield Thomas Water Tunnel at the Applied Research Laboratory (ARL) at Penn State University
    Gunawan, Budi; Michelen, Carlos; Neary, Vincent S.; Coe, Ryan G.; Johnson, Erik; Fontaine, Arnold; Meyer, Richard S.; Straka, William; Jonson, Michael (2014-04)
    This paper describes the development of a high‐fidelity computational fluid dynamics (CFD) model of a three‐blade horizontal axis current turbine. The CFD model was developed using STAR‐CCM+ and solves the Reynolds‐Averaged Navier‐Stokes (RANS) equation for unsteady flows. Preliminary CFD model results are compared to laboratory measurements. The variables being compared include inflow and wake flow velocity profiles, and performance coefficients (power, thrust and torque coefficients) at different tip‐speed ratios. A preliminary comparison suggests that overall the CFD simulation results have a good agreement with the measurements.
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    Optimization and Annual Average Power Predictions of a Backward Bent Duct Buoy Oscillating Water Column Device Using the Wells Turbine
    Smith, Christopher; Willits, Steven; Bull, Diana; Fontaine, Arnold (2014-04)
    This paper presents work completed by The Applied Research Laboratory at The Pennsylvania State University, in conjunction with Sandia National Labs, on the optimization of the power conversion chain (PCC) design to maximize the Average Annual Electric Power (AAEP) output of an Oscillating Water Column (OWC) device. The design consists of two independent stages. First, the design of a floating OWC, a Backward Bent Duct Buoy (BBDB), and second the design of the PCC. The pneumatic power output of the BBDB in random waves is optimized through the use of a hydrodynamically coupled, linear, frequency-domain, performance model that links the oscillating structure to internal air-pressure fluctuations. The PCC optimization is centered on the selection and sizing of a Wells Turbine and electric power generation equipment. The optimization of the PCC involves the following variables: the type of Wells Turbine (fixed or variable pitched, with and without guide vanes), the radius of the turbine, the optimal vent pressure, and the sizing of the power electronics.