Frozen-RANS Turbulence Model Corrections for Wind Turbine Wakes in Stable, Neutral and Unstable Atmospheric Boundary Layers

Computational Fluid Dynamics based on RANS models remain the standard but suffer from high errors in complex flows. In particular, turbulent kinetic energy is over-produced in high strain rate regions, such as the near wake of wind turbine flows. Data-driven turbulence modelling methods aim to derive novel turbulence models with lower...

A Machine Learning Approach to Unresolved-Scale Modeling for Burgers’ Equation

This thesis is part of a greater effort to use machine learning for the development of flexible and universal unresolved-scale models in large eddy simulation (LES). The novelty in the current work is that a neural network learns to predict the integral forms of the unresolved-scale terms directly without a priori assumptions on the underlying...

Goal Oriented Optimization of Tailored Modes for Reduced Order Modelling: An alternative perspective on Large Eddy Simulation

This Masters thesis is a new perspective on Large Eddy Simulation. The capability of goal oriented model constrained optimization technique to generate stable reduced order models without any additional stabilization term or subgrid scale modelling has been demonstrated. The low dimensional projection modes sought by the optimization program...