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
Demonstrator(s)	Ankith Anil Das, ankith.anildas@sydney.edu.au
Demonstrator(s)	Shanil Jayawardena, shanil.jayawardena@sydney.edu.au
Lecturer(s)	Nicholas Williamson, nicholas.williamson@sydney.edu.au
Tutor(s)	Mark George, mark.george@sydney.edu.au

Type	Description	Weight	Due	Length
Oral exam ?	Major Project (Part B) Oral Exam	30%	Formal exam period	20 minutes (oral)
Outcomes assessed:
Small test	Laboratory Held on Weeks 3,5,6,8,11 and week 12 or 13 (depending on group)	6%	Multiple weeks	Approx 100min of modelling + 3minQ&A
Outcomes assessed:
Small continuous assessment	Mini-Assignment 1 Mini-assignment, submitted in canvas and demonstrated in the tutorials	2%	Week 04 Due date: 22 Aug 2023 at 15:00 Closing date: 22 Aug 2023	<100lines of code+<5min Q&A
Outcomes assessed:
Assignment	Assignment 1 Written report, calculations, Matlab Code. Oral Exam in tutorials	14%	Week 06 Due date: 08 Sep 2023 at 23:00 Closing date: 22 Sep 2023	Report <8pages, Code<8pages; Oral 5min
Outcomes assessed:
Tutorial quiz	Quiz 1 Written quiz, conducted in person, calculations and analysis. Long answer.	16%	Week 08 Due date: 19 Sep 2023 at 12:00 Closing date: 19 Sep 2023	typically 4 to 6 pages of working
Outcomes assessed:
Small continuous assessment	Mini-Assignment 2 Mini-assignment, submitted in canvas and demonstrated in the tutorials	2%	Week 09 Due date: 03 Oct 2023 at 15:00 Closing date: 03 Oct 2023	<100lines of code+<5min Q&A
Outcomes assessed:
Tutorial quiz	Quiz 2 Written quiz, conducted in person, calculations and analysis. Long answer.	16%	Week 12 Due date: 24 Oct 2023 at 12:00 Closing date: 24 Oct 2023	typically 4 to 6 pages of working
Outcomes assessed:
Assignment	Major Project (Part A) A group report, computer code and analysis	14%	Week 13 Due date: 03 Nov 2023 at 23:00 Closing date: 10 Nov 2023	20pg report, ~200lines code
Outcomes assessed:
= group assignment ?

Assessment summary

Major Project (Part B) Oral Exam: This exam will be conducted in project groups. The exam will cover the Major project submissions and also assess students understanding of associated theory from across the unit of study. Individual marks will be awarded.

Major Project (Part A) Submitted Assignment: In this project students will investigate an engineering problem using numerical methods. They will be required to write code, perform numerical simulations using their code and also commercial packages and perform analysis. The work will be conducted in groups but have individual components. The students will write a group report and submit this and their code through Canvas. There is also a seperate oral exam associated with this project (Major Project Part B).

Quiz 1,2 are timed written quizzes conducted in lecture time (in person). These are long answer questions which 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 Major Project Oral exam will be re-weighted to include the quiz weighting.

Laboratory sessions are independent work supported by a tutor. 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.

Mini-Assignment 1 and 2: These are short assignments which require students to write Matlab or Python code. Students will be required to demonstrate their assignment submissions in the tutorial time to the tutors. The students will aso be required to discuss their work and demosntrate their understanding of the concepts. There are marks associated with the submitted work and the discussion. The students are required to upload their solutions to Canvas before the tutorial. Some solutions will be presented in the tutorial time so no extensions are possible. If special consideration is awarded the Major Project Oral exam will be re-weighted to include the mini-assignment weighting.

Assignment 1 is a group assignment where students are required to discretise partial differential equations, write MATLAB code to solve these equations numerically and perform analysis. Use of 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 in the tutorial time in the two weeks following the due date. There are marks associated with the submitted work and the discussion. Solutions are posted on the cose date so extension beyond this period is not possible. In this circumstance, the oral exam should be re-weighted to include the assignment weighting.

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 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.

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 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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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.

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	Lecture and tutorial (2 hr)
Week 02	1. Weighted residuals; 2. 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	1. Numerical stability 1; 2. Numerical stability 2	Lecture and tutorial (4 hr)
Week 11	ANSYS 5: CFD	Computer laboratory (2 hr)
Week 11	1. Computational fluid dynamics (advection schemes); 2. Discrete element method	Lecture (2 hr)
Week 12	ROCKY DEM	Computer laboratory (2 hr)
Week 12	1.Quiz, 2. Non-linear solvers;	Lecture and tutorial (4 hr)
Week 13	Engineering standards for computational analysis, Review	Lecture and tutorial (4 hr)

Attendance and class requirements

Independent Study: Approximately 5 hours per week of independent study outside of scheduled hours are required to complete the course assessments.

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.

Modifications to the assessment structure to better support Matlab coding skill development

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

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

Media

Student links

About us

Connect

Current students

AMME3060: Engineering Methods

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

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

Media

Student links

About us

Connect