Inferring algebraic stress models from high-fidelity data and applying machine learning to enhance and generalize turbulence lag models

Adverse pressure gradients, separation and other forms of non-equilibrium flows are often encountered in flows of interest. In these type of flows, the Boussinesq hypothesis does not hold and often leads to erroneous predictions by eddy viscosity models. In an attempt to capture these non-equilibrium effects, lag parameter models introduce a lag...

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...

Artificial Neural Networks for Flow Field Inference: A machine learning approach

Due to their powerful approximation capabilities, artificial neural networks have seen a wide interest in various fields. A particular application is the use of an artificial neural network to predict solutions of the governing equations for fluid flow i.e. the Navier-Stokes equations. This is done by taking the space and time variables as the...

Field inversion and machine learning in turbulence modeling

Turbulence closure models will continue to be necessary in order to perform computationally affordable simulations in the foreseeable future. It is expected that Reynolds-averaged Navier-Stokes (RANS) turbulence models will still be useful with the further development of the more accurate, but computationally expensive large eddy simulation (LES...

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...

Identiffcation of Momentum Forcing Required to Reduce Base-Model Errors Using Full-Field Inversion

Reynolds Averaged Navier-Stokes turbulence models have been widely used in many industrial applications because of their lower computational cost compared to other simulation approaches such as DNS and LES. This is a consequence of considering mean-ow quantities achieved by the time-averaging process. However, the time-averaging introduces the...

Optimization of a wing-body junction

Junction flows occur when a boundary layer encounters an obstacle (such as a wing) on its path. They can occurr either in laminar or turbulent flow conditions but only the turbulent case is considered here. This type of flow is usually a 3D, anistoropic, unsteady, turbulent flow. These characteristics are the result of two main phenomena. The...

Variational Germano Optimization of Arbitrary Unresolved-Scale Models

This thesis demonstrated how the Newton and BFGS algorithm could be used to solve the standard VGM relations and least-squares formulation respectively, for arbitrary forms of the _ parameter, including nonlinear _ s, appearing in the VMM. The proposed procedure were also shown to be able to handle arbitrary projectors that are compatible with...

Rosenbrock time integration combined with Krylov subspace enrichment for unsteady flow simulations: Unsteady aerodynamics

The GMRES algorithm has been discussed to solve the linear system Ax = b for application in a flow solver. Besides the conventional GMRES algorithm, several approaches are discussed which supposedly reduce the computational costs of the method, and reduce the number of iterations needed to satisfy the convergence criteria. GMRES is one of the...

Multi Point IPR Uncertainty Quantification: novel approach for a next generation reservoir simulator

It is investigated if a Multi Point Inflow Performance Relationship (MIPR) using Uncer- tainty Quantification (UQ) can lead to a step change in completion design. The MIPR model consists of several Kuchuk IPR models coupled with a wellbore network, and is verified against a discretized model. It is found that the assumption of artificial no-flow...

Uncertainty Quantification and Calibration of the k − ǫ turbulence model

Nowadays, the numerical errors are decreased to an acceptable level in the sense that the variability of the model parameters is becoming more important for obtaining results with higher reliability. Therefore, the focus of this thesis is on the quantification of the uncertainties of the turbulent closure model k −ǫ. The k −ǫ model is tuned to...

Mimetic Mesh Refinement: A mortar element approach

This thesis aims to introduce mesh refinement into the Mimetic Spectral Element Method (MSEM). The concept of mimetic discretizations is to mimic the properties of continuous Partial Differential Equations (PDEs) discretely. In many discretization methods information is lost in the actual discretization step which is detrimental to the physical...

Flutter Behaviour of a Laminar Supercritical Airfoil: A Numerical Investigation into the Influence of Boundary Layer Transition

Today a lot of attention is paid to the development of environmental friendly technologies. In the aircraft industry, emissions need to be reduced as well. Fuel can be saved by ensuring that the flow over the wings of the aircraft is completely or partly laminar. A laminar boundary layer creates less skin friction drag than a turbulent boundary...

Application of Uncertainty Quantification to a Fluid-Structure Interaction Experiment: Providing Accurate Insight in Uncertain Phenomena

Societies demand for sustainability is one of the main drivers for innovation in the wind energy industry. The increasing size of wind turbines implies increasingly flexible turbine blades. The flexibility of the blades induces the occurrence of fluid-structure interaction (FSI) phenomena. The simulation codes that are used for the design of...