Hydrodynamic Optimization of Ducted Hydrokinetic Turbine
ORAL
Abstract
It has long been hypothesized that a duct can accelerate and condition the fluid flow passing the hydrokinetic turbine and improve overall energy extraction efficiency. To investigate this problem, we explore the optimal design of a ducted hydrokinetic turbine to maximize hydrodynamic efficiency in this work. Our method relies on combining both gradient-free and gradient-based optimizations. We first conduct gradient-free Bayesian optimization in conjunction with a low-fidelity steady RANS varying a few important design parameters. The optimal turbine geometry obtained is then used as the baseline design for subsequent gradient-based optimization using the adjoint method with substantially more design variables (representing both blade and duct geometries). The optimized geometry is finally evaluated through unsteady RANS simulations.
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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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Bradford G Knight
University of Michigan
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Yingqian Liao
University of Michigan
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Kevin J Maki
University of Michigan
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Joaquim Martins
University of Michigan
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Yulin Pan
University of Michigan, Michigan