Outline

Overview

This unit will address the use of state of the art engineering software packages for the solution of advanced problems in engineering. We will cover the solution of partial differential equations in heat transfer; fluids, both inviscid and viscous, and solids. While some analytical methods will be considered, the primary focus of the course will be on the use of numerical solution methods, including finite difference, finite element, finite volume and discrete element methods. Commercial engineering packages will be introduced with particular attention given to the development of standards for the accuracy.

Unit details and rules

Academic unit	Aerospace, Mechanical and Mechatronic
Credit points	6
Prerequisites ?	AMME2000 or MATH2067 or (MATH2061 and MATH2065) or MATH2021
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Nicholas Williamson, nicholas.williamson@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Final Exam Written Exam	46%	Formal exam period	2.5 hours	AI prohibited
Outcomes assessed:
In-person practical, skills, or performance task or test	Tutorial Assessments Tutorial working and oral exam	9%	Multiple weeks	5min oral exam on tutorial problems	AI prohibited
Outcomes assessed:
Interactive oral	Assignment 1 Oral Oral on Assignment 1	10%	Multiple weeks	30min	AI prohibited
Outcomes assessed:
Practical skill	Laboratory Held on Weeks 3,5,6,8,10,11 and week 12	7%	Multiple weeks	Approx 100min of modelling + 3minQ&A	AI allowed
Outcomes assessed:
Written work	Assignment 1 Written report, Matlab Code	3%	Week 06 Due date: 12 Sep 2025 at 23:00 Closing date: 15 Sep 2025	Report <10pages Code<8pages	AI allowed
Outcomes assessed:
In-person practical, skills, or performance task or test	Quiz 1 Written quiz, conducted in person, calculations and analysis. Long answer.	12%	Week 08 Due date: 23 Sep 2025 at 13:00 Closing date: 23 Sep 2025	1 hour	AI prohibited
Outcomes assessed:
Written work	Assignment 2 A group report, computer code	3%	Week 12 Due date: 31 Oct 2025 at 23:00 Closing date: 03 Nov 2025	Report <10pages Code<8pages	AI allowed
Outcomes assessed:
Interactive oral	Assignment 2 Oral Oral Exam on Assignment 2	10%	Week 13	30min	AI prohibited
Outcomes assessed:
= hurdle task ? = group assignment ? = early feedback task ?

Assessment summary

Exam is 2.5hrs. This is a written exam. An exam mark of at least 40% is required to pass the unit of study.

Assignments 1 and 2 are group assignments where students are required to discretize partial differential equations, write MATLAB code to solve these equations numerically and perform analysis. Commercial analysis software may also be required. The work is submitted as a report together with the code and datafiles through canvas Turnitin. Students will be required to demonstrate their assignment submissions and answer verbal questions on the work and associated concepts in scheduled oral exams. The oral exams are scheduled in the groups, they will take place in either timetabled lab sessions or in the tutorial time in the weeks following the due date. There are marks associated with the submitted work and the discussion. Students are required to submit assignment progress updates through Canvas in Friday of week 3,4,5 for assignment 1 and Friday of week 10 and 11 for assignment 2. Completion of these tasks carries a course weighting. Solutions are posted shortly after the completion of the oral exams.

Generative AI: Generative AI may be used in Assignments 1 and 2 to assist in the completion of the assessment; however, all use of generative AI must be acknowledged, and all command prompts and answers must be recorded and provided to the unit of study coordinator on request. All submitted work must be the students work and fully understood. Most of the assessment weighting is carried by the oral exams where understanding of the submitted work and the underlying methods, concepts and logic will be tested.

Quiz 1 is a timed written quiz conducted during lecture time (in person). These are long answer questions that must be handwritten. The quizzes are held during the lecture time but can be asynchronously scheduled for special consideration if held on the same calendar day. Some solutions may be provided as early as 24hrs after the quiz so no quiz can be scheduled after 24hrs. In this circumstance, the Exam will be re-weighted to include the quiz weighting.

Laboratory sessions are independent work supported by a lab demonstrator. The grades are associated with completion of the work, demonstration of the analysis of computational models and then answering of additional questions with the lab demonstrators. With special consideration, the students can have their work assessed in the following timetabled laboratory session, except for the final lab, where if special consideration is approved, the lab weighting for the final lab would be shifted to the final exam. Labs are held on Weeks 3,5,6,8,10,11 and week 12

Tutorial Assessments: In weeks 2-11, small in-class tutorial assessments will be conducted. The best 9 of these 10 assessments will count towards the total grade for this assessment with each of these assessments being 1%. These assessments will vary slightly from week to week but will comprise of graded tutorial questions and/or small oral exams performed in tutorial groups, and checks on completion of tutorial homework tasks from previous weeks. The Better Mark Principle Applies: if a student attends and fully participates in at least 8 out of 12 tutorials and the exam mark % is higher than the tutorial mark % then the tutorial assessment will receive the exam mark i.e. the student would get the better of their exam mark or tutorial mark.
Special Consideration: For all assessments for which special consideration is approved and for which the assessments are either missed or submitted after the return date, the assessment will receive the final exam mark.
Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Standard late penalties apply

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Multiple weeks	Independent study to prepare for classes and to work on assignments.	Independent study (85 hr)
Week 01	1. Approximate methods; 2. The heat equation 2. Weighted residuals	Lecture and tutorial (2 hr)
Week 02	FEM: Galerkin	Lecture and tutorial (4 hr)
Week 03	ANSYS 1: FEM	Computer laboratory (2 hr)
Week 03	1. Quadratic Elements; 2. FEM: Galerkin	Lecture and tutorial (4 hr)
Week 04	FEM: 2D	Lecture and tutorial (4 hr)
Week 05	ANSYS 2: Mesh Generation 1	Computer laboratory (2 hr)
Week 05	1. Mesh generation; 2. Mesh generation 2	Lecture and tutorial (4 hr)
Week 06	ANSYS 3: Mesh Generation 2	Computer laboratory (2 hr)
Week 06	1. Accuracy: Finite volume method; 2. Finite difference method	Lecture and tutorial (4 hr)
Week 07	1. Direct solvers; 2. Iterative solvers	Lecture and tutorial (4 hr)
Week 08	ANSYS 4: Unsteady Problems	Computer laboratory (2 hr)
Week 08	Quiz, Unsteady methods	Lecture and tutorial (4 hr)
Week 09	1. Unsteady FEM; 2. Unsteady methods	Lecture and tutorial (4 hr)
Week 10	Numerical stability in Practice	Lecture and tutorial (4 hr)
Week 10	ANSYS 5: CFD	Computer laboratory (2 hr)
Week 11	Computational fluid dynamics	Lecture (2 hr)
Week 11	ANSYS 6: CFD	Computer laboratory (2 hr)
Week 12	ROCKY DEM	Computer laboratory (2 hr)
Week 12	1.DEM 2. Non-linear solvers;	Lecture and tutorial (4 hr)
Week 13	Engineering standards for computational analysis	Lecture and tutorial (4 hr)

Attendance and class requirements

Tutorial Attendance is compulsory. Failure to attend at least 8/12 tutorials will result in a fail grade for the unit of study. The tutorials support group learning and group assessments.

Independent Study: The weekly time commitment of this unit of study is 10hrs per week in week 1 and 2 and 12hrs per week from weeks 3-13. This includes time to view lectures, attend tutorials and lab and complete the practice problems outside of class and complete assessments. A detailed breakdown of the time commitment will be provided in Canvas.

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

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.

Outcomes
Graduate qualities

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

LO1. present numerical solutions and describe accuracy of those solutions
LO2. work with engineering standards in this area
LO3. define and solve engineering problems
LO4. write computer code to solve complex problems in engineering using finite-difference and finite-element methods
LO5. use state of the art commercial engineering software packages, such as ANSYS/FLUENT/CFX
LO6. understand stability, accuracy, and convergence.

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
Learning outcomes

Responding to student feedback

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

Made significant modifications to the tutorial structure and introduced small regular weekly assessments.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

AMME3060: Engineering Methods

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links