An introduction to the fundamentals of Computational Fluid Dynamics (CFD) that are used to solve complex fluid dynamics problems (weather prediction, aircraft flight, turbomachinery) by researchers, scientists and engineers around the world. The course starts from first principles and you will rapidly develop your first CFD solution using the Excel sheets and Python source code provided. By the end of the course, you will understand the importance of upwind differencing, Peclet number and mesh resolution. No prior experience is required and no specific CFD code/coding experience is required!

What you will learn:

How to set up and solve your first CFD solution from first principles
The importance of central differencing, upwind differencing and Peclet number
A common framework to solve any scalar transport equation in CFD

Course requirements:

Basic vector algebra (dot product, gradient, cross product)
Basic differential equations
Basic linear algebra (matrices)

You will learn

Create your own CFD code in a language of your choice (MATLAB, Fortran, C, C++, Java) to solve the 1D problems presented in this course. Use either the Excel sheets, the python source code or the course material to get started. Some things to check when you have written your code:

Do I get the right solution if the flow direction changes?
Can my code handle changes in mesh resolution and input parameters?
Do I get the correct answer that agrees with the course notes?
How fast does my CFD code solve the matrix equations

We would love to see what solutions you come up with!

Requirements

Basic knowledge of Fluid Dynamics is required to start this course, as this is an intermediate level course.

This course is for

This course was made for intermediate-level students.

More info about the instructor,

Dr Aidan Wimshurst

Flow and thermal performance engineer

Aidan is an enthusiastic computational fluid dynamics and thermal performance engineer, who addresses industrial fluid dynamics and heat transfer problems across a range of industrial sectors (Energy, Nuclear, Aviation, Civil and Transport). Aidan has expertise in developing bespoke computational solutions to complex modelling problems, such as hindered settling, conjugate heat transfer, external aerodynamics and turbomachinery. As a PhD student at Oxford University, Aidan developed novel modelling techniques for wind and tidal turbine rotors with several ground breaking research papers on rotor tip aerodynamics, which are published in the leading journal in the field: Wind Energy. In his spare time, Aidan is interested in computational fluid dynamics, numerical methods and renewable energy technologies. He runs a successful YouTube channel ‘Fluid Mechanics 101’, which aims to explain complex fluid dynamic modelling approaches to engineers, students and data scientists.

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