Machine Learning of Wind Plant Turbulence Anisotropy Fields

In studies of wind plant designs, wake dynamics are of great interests as wakes affect downstream turbine loading that impacts wind plant efficiency. Recent developments of Tensor Basis Decision Tree (TBDT) based machine learning (ML) models in reconstructing the turbulence anisotropy fields of simple flow cases prompt the motivation in applying...

Multi-fidelity Co-Kriging Optimization using Hybrid Injected RANS and LES

The computation of complex turbulent flows design optimization processes is currently limited by the lack of accuracy of Reynolds-Averaged Navier-Stokes (RANS) in massively separated flows and the infeasible cost of multiple Large-Eddy Simulation (LES) evaluations. A novel method is presented, injecting data from LES or other high-fidelity...

A Study of Global-Coefficient Non-Linear Eddy Viscosity Models

In this research a global-coefficient non-linear eddy viscosity model (NLEVM) is studied. This model stems from the inherent inability of the Boussinesq approximation to model anisotropy and therefore flow features such as: swirl, stream-line curvature and secondary motions (Lumley, 1970; Pope, 1975; Craft et al., 1996). The focus lies on the...