Computational Fluid Dynamics

Learning Objective:

1. Design an adequate computational method to solve canonical flow problems
2. Choose an adequate computational method to solve a fluid mechanics problem
3. Evaluate the quality of a numerical solutions to a fluid mechanics problem
4. Recommend the use of a computational method or a theoretical approach for a fluid mechanics problem
5. Understand scientific publications in the area of computational fluid dynamics

Description:

The course will cover introductory aspects of Computational Fluid Dynamics (CFD) with focus on canonical flow problems, while providing exposure to the latest advancements in discretization methods for fluid flow problems. We will use programming languages. We will provide sample codes in Matlab. We will also use other freely available software packages, including Freefem or Fenics. We will make use of free visualization tools like Paraview.

Topics Covered:

Classification of partial differential equations

The Navier-Stokes equations

Basic methods for spatial and temporal discretization

Stabilized formulations for advection dominated problems

Incompressible flow problems 

Prerequisites:

Prerequisites for this course include basic knowledge of fluid mechanics, linear algebra, partial differential equations and average programming skills. Intermediate knowledge of MATLAB is required (students with experience in Python should find it easy to transition to MATLAB).

Applied / Theory:

50/50

Web Address:

https://purdue.brightspace.com

Homework:

4-6 homeworks

Projects:

The student is allowed to suggest a topic of their interest, but the approval of the topic is subject to the instructor's discretion. If the student does not wish to propose a topic, the instructor will propose one.

Exams:

One midterm exam

Textbooks:

None

Computer Requirements:

We will provide sample codes in Matlab. We will also use other freely available software packages, including Freefem or Fenics. We will make use of free visualization tools like Paraview.