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Unit information: Computational Aerodynamics in 2016/17

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Unit name Computational Aerodynamics
Unit code AENGM2004
Credit points 10
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Professor. Allen
Open unit status Not open
Pre-requisites

EMAT20200 Engineering Mathematics 2

Co-requisites

None

School/department Department of Aerospace Engineering
Faculty Faculty of Engineering

Description

This unit is an introduction to the fundamental mathematical and physical principles involved in the development and application of modern methods in computational aerodynamics. Forms of the governing flow equations are first discussed and these are then reduced to a simple model equation, which is used for the development and testing of numerical methods. Accuracy, stability, and convergence of these schemes are investigated mathematically. Issues involved in applying these methods to real aerodynamic flows are then discussed, including grid generation aspects, data storage and memory implications, and the impact of continuing developments in computer architecture.

Aims:

The aim of this unit is to equip the student with: Knowledge and understanding of the fundamental mathematical and physical principles involved in the development of numerical methods; Knowledge and understanding of the issues involved in applying modern numerical methods in computational aerodynamics; Knowledge and understanding of methods of mesh generation and links with numerical code development; Knowledge and understanding of the impact of developments in computer hardware and software on application of computational methods; Basic skills necessary to develop numerical simulation codes

Intended learning outcomes

On successful completion of the unit students should be able to achieve the following outcomes:

  1. Understand the form and properties of the governing fluid flow equations, including different modelling level options
  2. Derive numerical methods for the solution of systems of partial differential equations;
  3. Analyse the stability, accuracy and convergence of these methods mathematically;
  4. Understand and apply the principles of time-marching, central-difference and upwind, and explicit and implicit formulations;
  5. Understand the principles of numerical grid generation, and their links with flow-solver development and application;
  6. Understand the link between numerical method application and computer architecture;
  7. Code advanced numerical methods in C++, Fortran, or Matlab.

Teaching details

Students will receive two one hour lectures every week for ten weeks. Several demonstration codes are presented during the lectures, and these codes are given to the students. The lectures are supported by a series of 10 computer labs (students typically attend around half of these), wherein students are given a series of development exercises in which they are required to modify the demonstration codes to reinforce the lecture concepts. In addition, several development tasks (non-assessed) are set to complement the lectures, which require the students to write their own codes (they can choose any coding language), and force them to think deeply about the concepts in the lectures. Model codes and results are distributed and discussed in lectures every few weeks. In the Summer Term, structured example and exam revision classes will be organised.

Assessment Details

The lecture course will be assessed by a two-hour written examination, and two pieces of assessed coursework. The examination consists of a compulsory question, and four other questions of which candidates should answer two. Each of the questions consists of some conceptual sections, to test the students’ fundamental understanding and knowledge, followed by some more detailed analysis and derivation of numerical methods for common partial differential equations in aerodynamics. The form of the examination will typically test learning outcomes 1-6, though with different emphasis in different questions. There are also two pieces of assessed coursework. Each requires derivation of various forms of numerical methods, testing some or all of learning outcomes 1-6, and application to a typical aerodynamic or fluid dynamic problem by developing a computer code, testing learning outcome 7.

Assessment weightings:

Examination 50%

Standard coursework 21%

Advanced coursework 29%

Reading and References

Numerical Computation of Internal and External Flows, Vols 1 and 2, C. Hirsch. Wiley 2007. Complete reference text for all aspects of CFD. Most of this is probably beyond the scope of the course.

Computational Methods for Fluid Dynamics, J.H. Ferziger and M. Peric. Springer 2001. Good general numerical methods book.

Computational Fluid Dynamics, J. Anderson. McGraw-Hill 1995. Best general CFD book.

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