Learning outcome

A candidate who has passed the course will have a learning outcome in the form of acquired knowledge, skills, and general competence, as described below.

Knowledge

The candidate will:

• understand the meaning of the terminology associated with computational fluid dynamics
• understand the physical principles associated with the subject
• understand the general transport equations for mass, momentum and energy
• understand the numerical methods for solving the transport equations for mass, momentum, energy and other scalar transport equations
• understand the physical behaviour of turbulence and how it is modelled in RANS

Skills

The candidate will:

• be able to apply adequate methods, techniques and equations in solving problems using CFD
• be able to apply and solve the transport equations for mass, momentum and energy
• be able to assess different numerical methods for solving transport equations
• be able to use relevant CFD software

General competence

The candidate will:

• be able to use CFD on new problems
• be able to report results from CFD-analysis
• be able to apply the transport equations in new problems
• Derivation of the transport equations of mass, momentum and energy, both generally and for a Newtonian fluid
• Turbulence and modelling of turbulence in RANS
• Numerical methods for convection and diffusion problems
• Numerical methods for pressure-velocity linked equations
• Numerical methods for algebraic equations
• Boundary conditions for transport equations
• Computer lab with relevant CFD software

Course Description

Content

• Derivation of the transport equations of mass, momentum and energy, both generally and for a Newtonian fluid
• Turbulence and modelling of turbulence in RANS
• Numerical methods for convection and diffusion problems
• Numerical methods for pressure-velocity linked equations
• Numerical methods for algebraic equations
• Boundary conditions for transport equations
• Computer lab with relevant CFD software

Teaching and Learning Methods

Lectures, exercises, computer lab and assignments are used.

Assessment Methods

The final test counts 70 %; the mid-term test counts 30 %. Grades A-F are used. To pass the course, the final test must be passed. The laboratory work is given on a pass/fail basis; to pass the course, the laboratory work must be passed.

Minor adjustments may occur during the academic year, subject to the decision of the Dean