Undergraduate Course: Computational Fluid Dynamics 5 (MECE11004)
Course Outline
School  School of Engineering 
College  College of Science and Engineering 
Credit level (Normal year taken)  SCQF Level 11 (Year 5 Undergraduate) 
Availability  Available to all students 
SCQF Credits  20 
ECTS Credits  10 
Summary  This module 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 (StarCCM+) is used for the assignments, the underlying themes of the module are generic. 
Course description 
Not entered

Entry Requirements (not applicable to Visiting Students)
Prerequisites 

Corequisites  
Prohibited Combinations  
Other requirements  None 
Information for Visiting Students
Prerequisites  None 
Course Delivery Information

Academic year 2014/15, Available to all students (SV1)

Quota: None 
Course Start 
Semester 1 
Timetable 
Timetable 
Learning and Teaching activities (Further Info) 
Total Hours:
200
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 20,
Formative Assessment Hours 1,
Summative Assessment Hours 12,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
153 )

Assessment (Further Info) 
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %

Additional Information (Assessment) 
Assignment 50%
Final Examination 50%

Feedback 
Not entered 
Exam Information 
Exam Diet 
Paper Name 
Hours & Minutes 

Main Exam Diet S1 (December)  Computational Fluid Dynamics 5  2:00   Resit Exam Diet (August)   2:00  
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 twodimensional flow problem for CFD solution, including geometry, boundary conditions, flow models and solution parameters.
10. Use preprocessor, solver and postprocessor software to build a CFD model for twodimensional problem, and obtain a solution.
11. Estimate the magnitudes of solution errors, and take steps to validate the results.

Contacts
Course organiser  Prof David Ingram
Tel: (0131 6)51 9022
Email: David.Ingram@ed.ac.uk 
Course secretary  Mr Paulo Nunes De Moura
Tel: (0131 6)51 7185
Email: paulo.nunesdemoura@ed.ac.uk 

