In this lecture, we will explore the fundamentals of geometry creation and CAD modeling tailored for CFD applications. You'll learn how to install FreeCAD and use its essential features to design geometry specifically for fluid flow simulations. As a hands-on exercise, we will create a simple CAD model for simulating flow past a cube, providing a practical foundation for integrating CAD with CFD workflows.

In this lecture, we will install Gmsh and explore its key features for mesh generation in CFD applications. You will learn how to control mesh size in specific regions and understand the essential requirements for creating a mesh that a solver can interpret correctly. We will also cover how to label boundary surfaces so that appropriate boundary conditions can be applied during simulation.

In this lecture, we will explore the importance of Docker and why it is a valuable tool for running simulations. You will learn how to install Docker step-by-step, and then test your installation by running an example OpenFOAM simulation within the Docker environment to ensure everything is set up correctly.

In this lecture, we will explore the concept and importance of boundary conditions in CFD simulations. You will learn why they are essential and how they influence simulation results. We will then examine the OpenFOAM folder structure to understand how simulation data is organized. Finally, you will learn how to identify and correctly label mesh boundaries, convert meshes to the OpenFOAM format, and set up appropriate boundary conditions for your simulation case.

In this lecture, we will learn how to configure discretization schemes in OpenFOAM, specifying how each term in the fluid flow equations should be numerically treated. We will then explore how these equations are assembled into a linear system and how to choose appropriate solvers for different terms. Additionally, we will discuss the concept of mesh orthogonality, its impact on simulation accuracy, and how it influences solver settings. These concepts will be introduced through visual inspection of the mesh, which will be explored further in the following lecture.

In this lecture, we will assume a target Reynolds number commonly used in CFD simulations and compute the corresponding kinematic viscosity. Using the prescribed free-stream velocity, we will then calculate an appropriate time step to ensure the flow behaves according to the desired Reynolds number. This process is essential for setting up physically realistic and numerically stable simulations in OpenFOAM.

In this lecture, we will demonstrate how to install ParaView independently and use it to visualize OpenFOAM simulation results. You'll be introduced to key features of ParaView for effective post-processing. We will also explore OpenFOAM’s built-in post-processing functions that can be applied after simulations are complete. Finally, we’ll use basic Python scripting to extract and plot drag force results for further analysis.

In this hands-on lecture, we will guide you through creating an AWS account and introduce the various types of compute resources available, including cost expectations. You will learn how to use the terminal to run jobs, securely transfer files using SCP, install Docker on AWS, and run OpenFOAM simulations in the cloud. Finally, we will cover how to transfer your simulation results back to your local machine.

In this lecture, we provide hands-on instructions for installing all the software used in the course on the Windows operating system. The focus of this session is solely on the installation process; all other steps and workflows remain the same as demonstrated in previous lectures. This lecture ensures that Windows users can follow the course seamlessly without any interruptions.