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Unit of study_

AMME8202: Computational Fluid Dynamics

Semester 1, 2023 [Normal day] - Camperdown/Darlington, Sydney

Objectives: To provide students with the necessary skills to use commercial Computational Fluid Dynamics packages and to carry out research in the area of Computational Fluid Dynamics. Expected outcomes: Students will have a good understanding of the basic theory of Computational Fluid Dynamics, including discretisation, accuracy and stability. They will be capable of writing a simple solver and using a sophisticated commercial CFD package. Syllabus summary: A course of lectures, tutorials and laboratories designed to provide the student with the necessary tools for using a sophisticated commercial CFD package. A set of laboratory tasks will take the student through a series of increasingly complex flow simulations, requiring an understanding of the basic theory of computational fluid dynamics (CFD). The laboratory tasks will be complemented by a series of lectures in which the basic theory is covered, including: governing equations; finite difference methods, accuracy and stability for the advection/diffusion equation; direct and iterative solution techniques; solution of the full Navier-Stokes equations; turbulent flow; Cartesian tensors; turbulence models.

Unit details and rules

Unit code AMME8202
Academic unit Aerospace, Mechanical and Mechatronic
Credit points 6
Assumed knowledge

Partial differential equations; Finite difference methods; Taylor series; Basic fluid mechanics including pressure, velocity, boundary layers, separated and recirculating flows. Basic computer programming skills

Available to study abroad and exchange students


Teaching staff

Coordinator Steven Armfield,
Lecturer(s) Steven Armfield,
Type Description Weight Due Length
Assignment Lab attendance/completion
Lab attendance/completion
8% Multiple weeks n/a
Outcomes assessed: LO1 LO3 LO4
Tutorial quiz Quiz 1
10% Week 06 n/a
Outcomes assessed: LO1 LO4 LO3
Assignment Lab report 1
Lab report
4% Week 06
Due date: 31 Mar 2023 at 23:59
Outcomes assessed: LO1 LO3 LO4
Assignment Assignment 1
15% Week 07
Due date: 07 Apr 2023 at 23:59
Outcomes assessed: LO5
Assignment Lab report 2
Lab report
4% Week 09
Due date: 28 Apr 2023 at 23:59
Outcomes assessed: LO1 LO3 LO4
Assignment Assignment 2
15% Week 10
Due date: 05 May 2023 at 23:59
Outcomes assessed: LO5
Assignment Lab report 3
Lab report
4% Week 11
Due date: 12 May 2023 at 23:59
Outcomes assessed: LO1 LO3 LO4
Tutorial quiz Quiz 2
10% Week 12 n/a
Outcomes assessed: LO1 LO4 LO3
Assignment Major project
30% Week 13
Due date: 26 May 2023 at 23:59
Outcomes assessed: LO1 LO4 LO3 LO2

Assessment summary

  • Assignments: Two assignments based on developing computer programs using MATLAB which are then used to solve fluid dynamics problems.
  • Lab reports: Three lab reports based on fluid dynamics simulations performed using a commercial software package (ANSYS).
  • Quizzes: Two quizzes based on computational fluid dynamics theory presented in lectures.
  • Major project: Group project based on theoretical analysis and numerical simulation of a complex fluid problem.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

Result name

Mark range


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 1. Explicit finite difference discretisation of diffusion equation; 2. Solution approach; 3. Navier-Stokes equations Lecture and tutorial (12 hr) LO4 LO5
Week 02 1. Inversion; 2. Implicit finite difference discretisation of diffusion equation Lecture and tutorial (12 hr) LO4 LO5
Week 03 Accuracy and stabiity Lecture and tutorial (12 hr) LO4 LO5
Week 04 Finite difference discretisation of the advection/diffusion equation Lecture and tutorial (12 hr) LO4 LO5
Week 05 Accuracy stability of the advection diffusion equation Lecture and tutorial (12 hr) LO4 LO5
1. Gauss-Seidel; 2. Alternating direction implicit; 3. Direct; 4. Jacobi Lecture and tutorial (12 hr) LO4 LO5
Week 07 Finite volume method Lecture and tutorial (12 hr) LO4 LO5
Week 08 1. Solution methods for the Navier-Stokes equations; 2. Projection; 3. MAC Lecture and tutorial (12 hr) LO4 LO5
Week 09 1. Boundary conditions for pressure; 2. Boundary conditions for velocity and scalars Lecture and tutorial (12 hr) LO4 LO5
Week 10 1. Direct simulation; 2. Turbulent flow Lecture and tutorial (12 hr) LO4 LO5
Week 11 1. Mixing length; 2. Cartesian tensors; 3. Turbulence models Lecture and tutorial (12 hr) LO4 LO5
Week 12 1. Reynolds stress; 2. k-epsilon Lecture and tutorial (12 hr) LO4 LO5
Week 13 Large eddy simulation Lecture and tutorial (12 hr) LO4 LO5

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Write a consulting report
  • LO2. Plan and manage a major group project
  • LO3. assess fluid mechanics problems commonly encountered in industrial and environmental settings, construct and apply computational models, determine critical control parameters and relate them to desired outcomes and write reports
  • LO4. use a state of the art commercial computational fluid dynamics package
  • LO5. write a basic Navier-Stokes solver and to assess the stability, accuracy and convergence of Navier-Stokes solvers

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

Overall the the unit was received positively with only one comment requesting a slower pace in the lectures. Next year I will look at dropping some of the earlier material already covered in previous courses which will allow a slower pace for the more advanced material.


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