MECH4301 Computational Fluid Dynamics Course description

This course covers some fundamental concepts of Computational Fluid Dynamics and their practical use in computer simulations. Students learn about different challenges associated with compressible and incompressible flows, different grid structures and the numerical modelling of turbulence. The theoretical understanding is put to practical use through programming exercises with computer tools such as OpenFoam and python.

Approved by the Doctoral Committee 24 May 2018. Minor changes approved 27.04.2020.

This PhD-course is open for candidates at the PhD Program in Educational Sciences for Teacher Education, other PhD candidates and academic employees.

Language: English (and Norwegian, dependent on the language of participants).

This course introduces Cultural-Historical Activity Theory (CHAT) as an epistemological and methodological framework for conducting action research in social, work-based and/or educational settings. Action research is broadly defined as research and development work in which researchers and practitioners jointly investigate work activities and analyze empirical data in order to design a new or improved model of the activity.

Knowledge:

The candidate

• can derive the governing equations and explain the standard mathematical classifications of fluid flow
• can formulate fluid flow problems in terms of Partial Differential Equations
• can explain the difference between Direct Numerical Simulation and averaged turbulence models in CFD
• can explain the difference between staggered and collocated grids for a CFD meshing structure.

Skills:

The candidate

• can solve standard fluid flow problems by applying CFD tools, such as OpenFOAM
• can implement Finite Volume solution algorithms in Python
• can apply von Neumann and TVD analysis to derive precise stability bounds on numerical methods for partial differential equations
• can design suitable mesh structures for CFD analysis tailored to a given fluid flow problem.

General competence:

The candidate

• can design and perform CFD simulations for common industrial problems
• is capable of critically evaluating the results of CFD analyses and identifying potential sources of errors and inaccuracies
• can communicate their work and can master language and terminology of the CFD field.

• Lectures
• Problem solving sessions
• Computer laboratory sessions in
  • Applied CFD using high-level tools such as OpenFOAM.
  • Scientific programming in python.

None

Individual oral examination, 30 minutes per student.

None

Grade scale A-F.

Two internal examiners. External examiner is used periodically.

Tore Flåtten