Gradient-Based Design Optimization of a 5kW Ducted Hydrokinetic Turbine Using RANS CFD
ORAL
Abstract
Building upon our previous study on ducted hydrokinetic turbine optimization, this study focuses on enhancing the performance of a 5kW ducted hydrokinetic turbine under real-world constraints. Starting with a foil-shaped duct and a turbine featuring a bulky hub to house a generator, we optimize the duct, hub, and blades to maximize efficiency. The geometry is represented by a CAD-based parametrization using an open-source Engineering Sketch Pad. The gradient-based optimization process is performed, evaluating the turbine performance using a RANS-based flow solver and computing the gradients for the optimization using the adjoint method. The optimized design is subsequently re-evaluated using a higher-fidelity flow solver, yielding approximately 50% hydrodynamic efficiency, higher than an unducted counterpart.
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Presenters
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Jeongbin Park
University of Michigan
Authors
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Jeongbin Park
University of Michigan
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Marco Mangano
University of Michigan
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Sabet Seraj
University of Michigan
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Bernardo Pacini
University of Michigan
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Joaquim Martins
University of Michigan
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Kevin John Maki
University of Michigan
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Jing Sun
University of Michigan
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Yulin Pan
University of Michigan