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Unit outline_

AMME3060: Engineering Methods

Semester 2, 2024 [Normal day] - Camperdown/Darlington, Sydney

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) Shanil Jayawardena, shanil.jayawardena@sydney.edu.au
ISADORA BUGARIN, isadora.bugarin@sydney.edu.au
Lecturer(s) Nicholas Williamson, nicholas.williamson@sydney.edu.au
Tutor(s) Mark George, mark.george@sydney.edu.au
Bradley Pascoe, bradley.pascoe@sydney.edu.au
The census date for this unit availability is 2 September 2024
Type Description Weight Due Length
Supervised exam
? 
hurdle task
Final Exam
Written Exam
46% Formal exam period 2.5 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
Small test Laboratory
Held on Weeks 3,5,6,8,10,11 and week 12
7% Multiple weeks Approx 100min of modelling + 3minQ&A
Outcomes assessed: LO5 LO6
Small continuous assessment Tutorial Assessments
Tutorial working and oral exam
9% Multiple weeks 1-3pages writing and code, oral
Outcomes assessed: LO2 LO1 LO3 LO4 LO6
Assignment group assignment Assignment 1
Written report, Matlab Code and Oral Exam.
13% Week 06
Due date: 06 Sep 2024 at 23:00

Closing date: 23 Sep 2024
Report <10pages Code<8pages; Oral <10min
Outcomes assessed: LO5 LO1 LO3 LO4 LO6
Tutorial quiz Quiz 1
Written quiz, conducted in person, calculations and analysis. Long answer.
12% Week 08
Due date: 17 Sep 2024 at 14:00

Closing date: 18 Sep 2024
typically 4 to 6 pages of working
Outcomes assessed: LO3 LO4 LO6
Assignment group assignment Assignment 2
A group report, computer code and Oral exam
13% Week 12
Due date: 25 Oct 2024 at 23:00

Closing date: 29 Oct 2024
Report <10pages Code<8pages; Oral <10min
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
hurdle task = hurdle task ?
group assignment = group assignment ?

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 on the close date so extension beyond this period is not possible. In this circumstance, the final Exam should be re-weighted to include the assignment weighting.

 

  • 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 provided in an appendix. All submitted work must be fully understood. Most of the assessment weighting is carried by the oral exam where understanding of the submitted work and the underlying methods, concepts and logic will be tested. Generative AI may not be used in any other assessment.

 

  • 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 50% of 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.

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.

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 2023 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 2023. 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

WK Topic Learning activity Learning outcomes
Multiple weeks Independent study to prepare for classes and to work on assignments. Independent study (85 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 01 1. Approximate methods; 2. The heat equation 2. Weighted residuals Lecture and tutorial (2 hr) LO1 LO3 LO6
Week 02 FEM: Galerkin Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 03 ANSYS 1: FEM Computer laboratory (2 hr) LO1 LO5 LO6
1. Quadratic Elements; 2. FEM: Galerkin Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 04 FEM: 2D Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 05 ANSYS 2: Mesh Generation 1 Computer laboratory (2 hr) LO5
1. Mesh generation; 2. Mesh generation 2 Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 06 ANSYS 3: Mesh Generation 2 Computer laboratory (2 hr) LO5
1. Accuracy: Finite volume method; 2. Finite difference method Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 07 1. Direct solvers; 2. Iterative solvers Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 08 ANSYS 4: Unsteady Problems Computer laboratory (2 hr) LO1 LO5 LO6
Quiz, Unsteady methods Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 09 1. Unsteady FEM; 2. Unsteady methods Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 10 Numerical stability in Practice Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
ANSYS 5: CFD Computer laboratory (2 hr) LO1 LO5 LO6
Week 11 Computational fluid dynamics Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6
ANSYS 6: CFD Computer laboratory (2 hr) LO5
Week 12 ROCKY DEM Computer laboratory (2 hr) LO5 LO6
1.DEM 2. Non-linear solvers; Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 13 Engineering standards for computational analysis Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6

Attendance and class requirements

Tutorial Attendance is compulsory. Failure to attend at least 6/12 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 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. 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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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.