Computational Fluid Dynamics (CFD) MSK610

Computational fluid dynamics (CFD) lets us solve the governing equations for fluid dynamics for complex engineering problems. CFD is today used in a wide range of industries, some examples are:

• air resistance in airplanes and cars
• wind and wave loads on buildings and marine structures
• heat- and mass transfer in chemical processing plants
• consequence modelling of fires and explosions in the oil- and gas industry

In this course you will get an introduction to computational fluid dynamics. The first part of the course deals with fundamental theory and numerical methods. The second part of the course introduces use of the practical CFD software OpenFOAM. Both parts end with a group project where you select a problem of your own choice to investigate further.

Course description for study year 2021-2022

Facts
Course code

MSK610

Version

1

Credits (ECTS)

10

Semester tution start

Spring

Number of semesters

1

Exam semester

Spring

Language of instruction

English

Time table
Learning outcome

Knowledge

The students shall

• know the governing equations for fluid dynamics, and how these can be described as a general transport equation
• know the properties of the finite volume method for discretizing transport equations
• know the fundamental discretization schemes for each term of the transport equation
• know the most common methods for treating the coupled flow problem
• know the most common models for turbulent flow
• be able to discuss advantages and disadvantages of different choices of solution methods and models

Skills

The students shall be able to

• perform the discretization of all the terms in the transport equation with the finite volume method
• implement numerical methods to solve transport equations in the Python programming language
• perform simulations in the CFD software OpenFOAM; create simulation mesh, select initial- and boundary conditions, discretization schemes and solution methods and visualize the results
• compare simulations against analytical and experimental results

General qualifications

The students shall be able to

• simplify practical problems to make them amenable for analysis with appropriate scientific methods
• visualize and present data from simulations in a scientific manner
• interpret results from simulations and evaluate accuracy and uncertainty
• collaborate in groups to carry out a project work
Required prerequisite knowledge
None
Recommended prerequisites
FYS100 Mechanics, MAT100 Mathematical Methods 1
Exam

Assignments, projects and written exam

Coursework requirements
Assignments (at least 4 of 6 have to be approved)
Course teacher(s)
Head of Department: Tor Henning Hemmingsen
Open for
Computational Engineering, Master's Degree Programme Environmental Engineering - Master of Science Degree Programme Engineering Structures and Materials - Master's Degree Programme Marine- and Offshore Technology - Master's Degree Programme
Literature
The syllabus can be found in Leganto