In this lecture, we will introduce the flow problem that will be studied throughout the course and discuss the challenges associated with accurately resolving boundary layers in high Reynolds number flows. We will demonstrate how to generate a computational mesh using Gmsh, and examine why simple triangulated meshes are often insufficient for capturing near-wall behavior. This session will emphasize the importance of mesh quality and refinement strategies when preparing for turbulence modeling using RANS equations.

In this lecture, we will demonstrate how to create a mesh for the backward-facing step geometry using blockMesh in OpenFOAM. We'll explain how to define the block structure, and introduce concepts such as simple grading and edge grading, detailing what these parameters mean and how they influence mesh resolution. You will learn how to modify grading to control element size distribution, especially near walls where higher resolution is required. Finally, we will compare the blockMesh output with a triangulated mesh to highlight how blockMesh offers fewer elements and better control over mesh density—making it an efficient choice for structured meshing.

In this lecture, we will explore zero-equation turbulence models, which are the simplest form of turbulence modeling. These models, such as the mixing-length model, do not involve solving additional transport equations. Instead, they rely on empirical relationships to estimate turbulent viscosity based on local flow properties.

While zero-equation models are computationally efficient and useful for simple flows, we will also discuss why they are not suitable for accurately capturing complex separated flows—such as the backward-facing step problem we'll be studying in this course.

In this lecture, we will introduce the Spalart–Allmaras turbulence model, a widely used one-equation model developed primarily for aerospace and external aerodynamic applications. Unlike two-equation models, it solves a single transport equation for a modified eddy viscosity, making it both efficient and robust for certain classes of flows.

We will discuss the underlying assumptions of the model, its strengths in predicting boundary layers and attached flows, and its limitations in more complex or separated flow scenarios. This lecture provides a foundation for understanding where and how to effectively apply one-equation models in CFD simulations.

In this lecture, we will start with the standard cavity flow example provided in OpenFOAM and modify it to suit the backward-facing step geometry. The focus will be on implementing the Spalart–Allmaras turbulence model, a one-equation model widely used in aerospace and external aerodynamic simulations for its simplicity and efficiency.

We will walk through the setup process, including adjusting the mesh, modifying boundary and initial conditions, and enabling the Spalart–Allmaras model. This hands-on session will demonstrate how to adapt existing OpenFOAM cases and apply appropriate turbulence models to simulate separated flows.

In this lecture, we will start with the standard cavity flow example provided in OpenFOAM and modify it to suit the backward-facing step geometry. The focus will be on implementing the Spalart–Allmaras turbulence model, a one-equation model widely used in aerospace and external aerodynamic simulations for its simplicity and efficiency.

We will walk through the setup process, including adjusting the mesh, modifying boundary and initial conditions, and enabling the Spalart–Allmaras model. This hands-on session will demonstrate how to adapt existing OpenFOAM cases and apply appropriate turbulence models to simulate separated flows.

In this lecture, we will set up and run a simulation of the backward-facing step problem using the k-epsilon turbulence model in OpenFOAM. We’ll discuss the specific requirements for using the k-epsilon model, including boundary conditions, initial values, and wall treatment strategies. The lecture will also evaluate the model’s performance in reattachment.

In this lecture, we will explore the theoretical background of the k-omega and k-omega SST (Shear Stress Transport) turbulence models. We will begin by discussing the motivation behind the development of the k-omega model, its mathematical formulation, and its key advantages—particularly its effectiveness in resolving near-wall flows and boundary layers.

We will then introduce the k-omega SST model, which blends the strengths of both k-omega and k-epsilon models through a blending function. This approach improves accuracy in flows with separation and strong adverse pressure gradients, making it one of the most robust RANS models for practical engineering simulations.

In this lecture, you will learn how to set up and run turbulence simulations in OpenFOAM using the l-omega and k-omega SST turbulence models. We'll cover the selection of appropriate model files, boundary condition setup, and key parameters that influence solution accuracy. By the end of the session, you’ll be able to confidently configure and execute RANS-based simulations for wall-bounded and separated flows using these widely used models.

In this lecture, we will explore the theoretical background of Reynolds Stress Models (RSM) in turbulence modeling. The focus will be on understanding the Launder–Reece–Rodi (LRR) model, a widely used closure approach within the RSM framework. We will discuss the advantages of using the LRR model in anisotropic and complex turbulent flows.

In this lecture, we will learn how to use the Reynolds Stress Model (RSM) for turbulence modeling in OpenFOAM. Unlike eddy-viscosity models, RSM solves transport equations for each component of the Reynolds stress tensor, making it capable of capturing the anisotropic nature of turbulence. We will go through the setup process, including how to define initial values and boundary conditions for RSM fields. This session will highlight the advantages of using RSM for flows with strong anisotropy, such as swirling or highly curved flows.