Postgraduate Course: Computational Fluid Dynamics (MSc) (PGEE11055)

Course Outline
School	School of Engineering	College	College of Science and Engineering
Credit level (Normal year taken)	SCQF Level 11 (Postgraduate)	Availability	Not available to visiting students
SCQF Credits	20	ECTS Credits	10
Summary	This course introduces CFD by means of a set of lectures covering the background physics and mathematics, together with practical assignments that use commercial CFD software to solve flow problems. The need for error control and independent validation of results is stressed throughout. Although particular software (Star-CCM+) is used for the assignments, the underlying themes of the module are generic.
Course description	Not entered

Course Delivery Information
Not being delivered

Learning Outcomes
On completion of the module, students should be able to: 1. Describe how the fields of fluid mechanics, mathematics and computer science have contributed to the development of CFD. 2. Identify the key aspects of fluid mechanics relevant to the setting up of a problem for CFD, and to the interpretation of the results. 3. Describe how various levels of approximation to the equations of motion are appropriate to particular classes of flow problem. 4. Describe the nature of turbulent flows and explain why 'turbulence models' are necessary to many CFD solutions. 5. Distinguish between the important classes of turbulence model. 6. Describe the important classes of numerical discretisation scheme, and explain the relationship between the discretisation process and the underlying fluid physics. 7. Appreciate the significance of error control and validation in CFD. 8. Discuss the sources of error in CFD solutions, and describe steps which can be taken to estimate the magnitude of errors. 9. Set up a two-dimensional flow problem for CFD solution, including geometry, boundary conditions, flow models and solution parameters. 10. Use pre-processor, solver and post-processor software to build a CFD model for two-dimensional problem, and obtain a solution. 11. Estimate the magnitudes of solution errors, and take steps to validate the results.