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AMME5060: Advanced Computational Engineering (2019 - Semester 2)

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Unit: AMME5060: Advanced Computational Engineering (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Aerospace, Mechanical & Mechatronic Engineering
Unit Coordinator/s: Dr Williamson, Nicholas
Session options: Semester 2
Versions for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Brief Handbook Description: 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, compact finite difference schemes, numerical dispersion and diffusion and efficient linear solvers. Students will develop to skills and confidence to write their own computational software. Applications in fluid and solid mechanics will be covered.
Assumed Knowledge: Linear algebra, calculus and partial differential equations and be familiar with Taylor series, the finite difference method, the finite element method (linear, quadratic elements), numerical stability, accuracy, direct and iterative linear solvers and be able to write Matlab Scripts to solve problems using these methods. Recommend AMME3060 or similar course.
Timetable: AMME5060 Timetable
T&L Activities: Independent Study: Approximately 5 hours per week of independent study outside of scheduled hours are required to complete the course assessments.

Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.

Attribute Development Method Attribute Developed
Students will become proficient in advanced numerical methods, their suitability and application to numerical modelling of engineering problems. (1) Maths/ Science Methods and Tools (Level 5)
Students will apply advanced numerical methods to a range of complex engineering problems through assignments and a large project. Students will be required to write their own software. (2) Engineering/ IT Specialisation (Level 5)
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. (3) Problem Solving and Inventiveness (Level 4)
Students will design numerical simulation software in small groups. The students will selection the underlying numerical method, choice of computation architecture and coding language. (4) Design (Level 4)
The 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. (7) Project and Team Skills (Level 4)
Students will have to engage with engineering standards for computational mechanics and ensure their testing of their software meets these standards. This includes appropriate benchmarking of solutions, professionally presenting these to clients and indicating the range of applicability for their solution. (8) Professional Effectiveness and Ethical Conduct (Level 3)

For explanation of attributes and levels see Engineering & IT Graduate Outcomes Table 2018.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

(7) Project and Team Skills (Level 4)
1. 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.
(8) Professional Effectiveness and Ethical Conduct (Level 3)
2. 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.
(4) Design (Level 4)
3. 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.
(3) Problem Solving and Inventiveness (Level 4)
4. 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.
(2) Engineering/ IT Specialisation (Level 5)
5. Students will apply advanced numerical methods to a range of complex engineering problems. Students will be required to write their own software.
(1) Maths/ Science Methods and Tools (Level 5)
6. Students will become proficient in advanced numerical methods, their suitability and application to numerical modelling of engineering problems.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Quiz 1 No 15.00 Week 7 (Tuesday, 10 am) 6,
2 Quiz 2 No 15.00 Week 11 (Tuesday, 10 am) 6,
3 Assignment 1 No 10.00 Week 6 (Thursday, 11 pm) 5, 6,
4 Assignment 2 No 10.00 Week 10 (Thursday, 11 pm) 5, 6,
5 Major Project Yes 40.00 Week 13 (Friday, 11 pm) 1, 2, 3, 4, 5, 6,
6 Tutorial Assignments No 10.00 Multiple Weeks (During your timetabled class, 12 pm) 5, 6,
Assessment Description: Quiz: Two quizzes will be set, each worth 15% of the total mark. These will be held in during the lecture slots.

Assignments: Two individual short assignments each worth 10% of the total mark. Text-based similarity detecting software (Turnitin) will be used to detect plagiarism.

Lab Assignments: Weekly lab assignments will be set worth a total of 10%. Weekly assignments are due by the following laboratory and will be marked in the laboratory session only. Some solutions will be provided 7 days after the due date. No submissions will be accepted 7 days after the due date.

Major Project: One major design project worth 40% of the total mark will be set. This project will have a group work component however all students must submit individual reports focusing on their individual contributions.

There may be statistically defensible moderation when combining the marks from each component to ensure consistency of marking between markers, and alignment of final grades with unit outcomes.

Assignments submitted after the due date will receive a 5% penalty per day. Assignments more than 10 days late receive 0.
Prescribed Text/s: Note: Students are expected to have a personal copy of all books listed.
  • FORTRAN FOR SCIENTISTS & ENGINEERS
Recommended Reference/s: Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 Lecture: Introduction
Lecture: Compiled Languages, Fortran, C
Week 2 Lecture: High Performance Computing
Lecture: Parallel Programing, MPI
Week 3 Lecture: Parallel Linear Solvers
Lecture: Efficient Coding
Week 4 Lecture: Krylov Space Solvers
Lecture: Krylov Space solvers
Week 5 Lecture: Multigrid Solvers
Lecture: Linear Solvers
Week 6 Lecture: Spectral Methods
Lecture: Spectral Methods
Assessment Due: Assignment 1
Week 7 Lecture: Quiz 1
Lecture: Numerical Dispersion
Assessment Due: Quiz 1
Week 8 Lecture: Numerical Dissipation and Dispersion
Lecture: Higher Order Schemes
Week 9 Lecture: Applications, CFD
Week 10 Lecture: Applications, hyperbolic equations
Assessment Due: Assignment 2
Week 11 Lecture: Quiz 2
Lecture: Applications
Assessment Due: Quiz 2
Week 12 Lecture: Guest Lecture
Lecture: Review
Week 13 Project Presentations
Assessment Due: Major Project

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Aeronautical Mid-Year 2016, 2017, 2018, 2019, 2020
Aeronautical 2016, 2017, 2018, 2019, 2020
Mechanical Mid-Year 2019, 2020
Mechanical/ Project Management 2019, 2020
Mechanical 2019, 2020
Mechanical / Arts 2019, 2020
Mechanical / Commerce 2019, 2020
Mechanical / Science 2019, 2020
Mechanical/Science(Health) 2019, 2020
Mechanical / Law 2019, 2020
Master of Engineering 2017, 2018, 2019, 2020
Mechanical/Science (Medical Science Stream) 2019, 2020
Master of Professional Engineering (Accelerated) (Aerospace) 2019, 2020
Master of Professional Engineering (Aerospace) 2017, 2018, 2019, 2020
Master of Professional Engineering (Accelerated) (Mechanical) 2019, 2020
Master of Professional Engineering (Mechanical) 2017, 2018, 2019, 2020

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
(7) Project and Team Skills (Level 4) Yes 6%
(8) Professional Effectiveness and Ethical Conduct (Level 3) Yes 4%
(4) Design (Level 4) Yes 8%
(3) Problem Solving and Inventiveness (Level 4) Yes 4%
(2) Engineering/ IT Specialisation (Level 5) Yes 23%
(1) Maths/ Science Methods and Tools (Level 5) Yes 55%

These goals are selected from Engineering & IT Graduate Outcomes Table 2018 which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 2018 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.