  Hydrokinetic turbines extract kinetic energy from moving water to generate
renewable electricity, thus contributing to sustainable energy production and
reducing reliance on fossil fuels. It has been hypothesized that a duct can
accelerate and condition the fluid flow passing the turbine blades, improving
the overall energy extraction efficiency. However, no substantial evidence has
been provided so far for hydrokinetic turbines. To investigate this problem, we
perform a CFD-based optimization study with a blade-resolved Reynolds-averaged
Navier--Stokes (RANS) solver to explore the design of a ducted hydrokinetic
turbine that maximizes the efficiency of energy extraction. To handle the
high-dimensional design space of the blade and duct geometry, we use a
gradient-based optimization approach where the gradients are computed using the
adjoint method. The final design is re-evaluated through higher-fidelity
unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an
efficiency of about 54% over a range of operating conditions, higher than the
typical 46% efficiency of unducted turbines such as the well-known Bahaj model.
