AMME5060: Semester 2, 2020

University home

Library

Current students

Staff intranet

Find an event

Give

Current students

Units AMME5060 Semester 2 2020 [Normal day]

Unit of study_

AMME5060: Advanced Computational Engineering

Semester 2, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

This unit will cover advanced numerical and computational methods within an engineering context. The context will include parallel coding using MPI, computational architecture, advanced numerical methods including spectral methods, finite difference schemes and efficient linear solvers including multi-grid solvers and Krylov subspace solvers. Students will develop to skills and confidence to write their own computational software. Applications in fluid and solid mechanics will be covered.

Unit details and rules

Unit code	AMME5060
Academic unit	Aerospace, Mechanical and Mechatronic
Credit points	6
Prohibitions ?	None
Prerequisites ?	UG students are required to complete AMME3060 before enrolling in this unit.
Corequisites ?	None
Assumed knowledge ?	Linear algebra, calculus and partial differential equations, Taylor series, the finite difference and finite element methods, numerical stability, accuracy, direct and iterative linear solvers and be able to write Matlab Scripts to solve problems using these methods.
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Nicholas Williamson, nicholas.williamson@sydney.edu.au
Lecturer(s)	Nicholas Williamson, nicholas.williamson@sydney.edu.au
Tutor(s)	Vassili Issaev, vassili.issaev@sydney.edu.au

Type	Description	Weight	Due	Length
Online task	Tutorial assignments Each worth 3%. Must be submitted in laboratory time and demonstrated.	18%	Multiple weeks	n/a
Outcomes assessed:
Assignment	Assignment 1 Written report, Code and datafiles	11%	Week 06 Due date: 02 Oct 2020 at 23:00 Closing date: 02 Oct 2020	n/a
Outcomes assessed:
Tutorial quiz	Quiz 1 Online quiz with calculations, coding, analysis	10%	Week 07 Due date: 13 Oct 2020 at 10:00	1hr quiz in Tuesday Lecture time at 10am
Outcomes assessed:
Assignment	Assignment 2 Written report, Code and datafiles	11%	Week 10 Due date: 06 Nov 2020 at 23:00 Closing date: 06 Nov 2020	n/a
Outcomes assessed:
Tutorial quiz	Quiz 2 Online quiz with calculations, coding, analysis	10%	Week 11 Due date: 10 Nov 2020 at 10:00	1hr quiz in Tuesday Lecture time at 10am
Outcomes assessed:
Assignment	Major project A written report, code, and presentation/oral exam.	40%	Week 12 Due date: 20 Nov 2020 at 02:00 Closing date: 20 Nov 2020	n/a
Outcomes assessed:
= group assignment ?

Assessment summary

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.

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.

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
Week 01	1. Introduction; 2. Compiled languages, Fortran	Lecture and tutorial (4 hr)
Week 02	1. High performance computing; 2. Parallel programing, MPI	Lecture and tutorial (4 hr)
Week 03	1. MPI; 2. Basic Linear solvers	Lecture and tutorial (4 hr)
Week 04	Memory Management, Advanced MPI	Lecture and tutorial (4 hr)
Week 05	1. Linear Solvers 2. Multigrid solver	Lecture and tutorial (4 hr)
Week 06	Krylov Space Solvers	Lecture and tutorial (4 hr)
Week 07	Spectral Methods	Lecture and tutorial (4 hr)
Week 08	Spectral Methods	Lecture and tutorial (4 hr)
Week 09	1. Spectral Methods; 2. Job Schedulers	Lecture and tutorial (4 hr)
Week 10	1. Spectral Methods 2. Advanced MPI, Efficient Programing	Lecture and tutorial (4 hr)
Week 11	Major Project Support	Lecture and tutorial (4 hr)
Week 12	1. OpenMP. 2. Course Review	Lecture and tutorial (4 hr)

Attendance and class requirements

Attendance in the laboratory sessions is compulsory and will be recorded.

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.

Required readings

The following textbook can be accessed through the Library eReserve, available on Canvas.

Stephen J. Chapman, FORTRAN FOR SCIENTISTS & ENGINEERS (4). 9780073385891

The following text book is also a required:

Introduction to High Performance Computing for Scientists and Engineers by Georg Hager: ISBN 978-1439811924

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. A major project will be undertaken in groups. Each member will have responsibilities for delivering these complex and technically demanding projects. Group members will have to work closely and understand all aspects of the project to deliver a successful software solution.
LO2. Students will have to engage with engineering standards for computational mechanics and ensure their testing of their software meets these standards. This includes appropriate bench-marking of solutions, professionally presenting these and indicating the range of applicability for their solution
LO3. Students will design numerical simulation software in small groups. The students will select the underlying numerical method, choice of computation architecture, coding language and design the code structure.
LO4. Students will be required to select the most appropriate numerical tools to solve engineering problems and how to represent these problems in a simulation. This requires and understanding of solution behaviour, what aspects of a problem are critical and what aspects can be simplified.
LO5. Students will apply advanced numerical methods to a range of complex engineering problems. Students will be required to write their own software.
LO6. Students will become proficient in advanced numerical methods, their suitability and application to numerical modelling of engineering problems.

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.

Changes to online teaching.

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

Required readings

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