Grants and Contributions:

Grant or Award spanning more than one fiscal year (2017-2018 to 2022-2023).

This proposal addresses a problem of critical importance for the hydroelectric power industry, the developmentx000D
of accurate models for the prediction of the flow over rough surfaces, in turbulence far from equilibrium. Twox000D
cases will be considered: a separating flow in a curved duct, and the flow in a rough channel undergoing systemx000D
rotation. We will use direct and large-eddy simulations (DNS and LES) of turbulence to validate the modelsx000D
for the Reynolds-Averaged Navier-Stokes equations that are commonly used in industry. Although the DNSx000D
and LES will be performed at Reynolds numbers lower than those in actual applications, the LES should bex000D
able to achieve the fully rough regime that allows to extend the simulation results to practical applications. Thex000D
proposed research will benefit Canada in several ways: first, it will train one PhD student and one PDF in thex000D
computational sciences; secondly, it will generate fundamental knowledge on the physics of rough-wallx000D
boundary layers in the presence of swirl, curvature, system rotation and separation. Finally, it will developx000D
prediction models that will benefit the power generation industry (and may be extended to other areas ofx000D
application), and can potentially result in significant efficiency increases and financial savings.