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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2017/2018

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DRPS : Course Catalogue : School of Engineering : Postgrad (School of Engineering)

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

Course Outline
SchoolSchool of Engineering CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThis 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
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Course Delivery Information
Academic year 2017/18, Not available to visiting students (SS1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 22, Supervised Practical/Workshop/Studio Hours 22, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 150 )
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 (MSc)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 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.
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
Keywordscomputational fluid dynamics
Contacts
Course organiserProf David Ingram
Tel: (0131 6)51 9022
Email: David.Ingram@ed.ac.uk
Course secretaryMrs Shona Barnet
Tel: (0131 6)51 7715
Email: Shona.Barnet@ed.ac.uk
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