AMME2000: Semester 1, 2020

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Units AMME2000 Semester 1 2020 [Normal day]

Unit of study_

AMME2000: Engineering Analysis

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

This course is designed to provide students with the necessary tools for mathematically modelling and solving problems in engineering. Engineering methods will be considered for a range of canonical problems including; Conduction heat transfer in one and two dimensions, vibration, stress and deflection analysis, convection and stability problems. The focus will be on real problems, deriving analytical solutions via separation of variables; Fourier series and Fourier transforms; Laplace transforms; scaling and solving numerically using finite differences, finite element and finite volume approaches.

Unit details and rules

Unit code	AMME2000
Academic unit	Aerospace, Mechanical and Mechatronic
Credit points	6
Prohibitions ?	None
Prerequisites ?	(MATH1001 OR MATH1021 OR MATH1901 OR MATH1921 OR MATH1906 OR MATH1931) AND (MATH1002 OR MATH1902) AND (MATH1003 OR MATH1023 OR MATH1903 OR MATH1923 OR MATH1907 OR MATH1933) AND (ENGG1801 OR INFO1103 OR INFO1903 OR INFO1110 OR INFO1910 OR DATA1002 OR DATA1902)
Corequisites ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Ben Thornber, ben.thornber@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Weekly pre-work	5%	-	n/a
Outcomes assessed:
Final exam	Exam Delivered online through Canvas	45%	Formal exam period	2 hours
Outcomes assessed:
Assignment	Tutorial question - total for all tuts	10%	Multiple weeks	n/a
Outcomes assessed:
Tutorial quiz	Quiz 1 Delivered online using Canvas in Thursday Week 4, 12-1pm	10%	Week 04	1 hour
Outcomes assessed:
Assignment	Assignment 1	10%	Week 06	n/a
Outcomes assessed:
Tutorial quiz	Quiz 2 Delivered online using Canvas in Thursday Week 10, 12-1pm.	10%	Week 10	1hr
Outcomes assessed:
Assignment	Assignment 2	10%	Week 12	n/a
Outcomes assessed:

Assessment summary

Assignment 1: Analytical and numerical solution of the heat or wave diffusion equation.
Assignment 2: Analytical and numerical solution of the Laplace Equation
Quiz 1: Material in Sections 1 and 2 of the lecture notes
Quiz 2: Analytical solutions to the heat, wave, Laplace/Poisson equations, integrals and transforms.
Tutorial question: One exercise from each tutorial must be completed by 9 am Tuesday of the following week. A student completing all exercises successfully will gain 10%.
Weekly pre-work: This mark is based on a short exercise or quiz, based on the pre-work, to be completed prior to the lectures that week.

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 to the UoS; 2. Introduction to numerical methods; 3. Discretisation; 4. Interpolation; 5. Least squares; 6. Cubic Splines; 7. Taylor series; 8. Finite differences	Lecture (2 hr)
Week 02	1. What is a PDE?; 2. Generic PDE introduction inc. classification; 3. Derivation of the heat diffusion equation; 4. Exact solution of the heat diffusion equation (Fourier series); 5. Solution of heat equation via separation of variables; 6. Heat equation with non-homogeneous boundary conditions	Lecture (2 hr)
Week 03	1. Initial value problems, boundary value problems, initial conditions, boundary conditions, well posed problems; 2. Accuracy, stability, consistency; 3. Linear algebra;	Lecture (2 hr)
Week 04	Forward time centred space solution of the heat diffusion equation.	Lecture (2 hr)
Week 05	1. Heat equation with more complex initial and boundary conditions; 2. Introduction to and derivation of the wave equation; 3. Classification of wave-like equations; 4. Approximate solution using Fourier series	Lecture (2 hr)
Week 06	1. Wave equation with complex initial conditions; 2. Numerical solution of the wave equation.	Lecture (2 hr)
Week 07	1. Introduction and derivation of the Laplace and Poisson equation; 2. Applications; 3. Exact solution based on Fourier series. 4. Numerical discretization of the 2D Laplace equation; 5. Solution using iterative methods;	Lecture (2 hr)
Week 08	1. Understanding PDEs - method to determine behaviour. 2. Fourier integrals and transforms;	Lecture (2 hr)
Week 09	1. Fourier integral solutions to infinite problems; 2. FFT and Signal Processing; 3. Fourier Transform solutions to PDEs.	Lecture (2 hr)
Week 10	1. Laplace transforms; 2. Solution of the semi-infinite wave equation using Laplace transforms	Lecture (2 hr)
Week 11	1. Laplace Transform solution to the heat equation; 2. Introduction to finite elements;	Lecture (2 hr)
Week 12	1. Piecewise linear basis functions; 2. Method of weighted residuals; 3. Weak formulation of the PDE and solution.	Lecture (2 hr)
Week 13	1. Foundations of stress analysis; 2. FEA solution for an axially loaded bar	Lecture (2 hr)

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

All readings for this unit can be accessed on the Library eReserve link available on Canvas.

Advanced Engineering Mathematics, E. Kreyszig, 10th Edition, Wiley, 2011.

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. understand and apply the physical relations and mathematical modelling of fundamental problems in engineering structures, fluid mechanics and heat and mass transfer.
LO2. creatively solve assignment problems, which focus on real-life engineering challenges
LO3. have developed proficiency in a structured approach to engineering problem identification, modelling and solution; develop proficiency in translating a written problem into a set of algorithmic steps, and then into computer code to obtain a solution

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.

Bringing the Laplace equation forward so that students understand better the connections and differences in solutions with heat/wave using Fourier Series. Including an new video lecture on the characteristic equation and how it results in different solutions An analytical practice problem will be covered in the tutorial each week Moving from 3 assignments and 1 quiz, to 2 quizzes and 2 assignments to ensure that key material presented early is bedded in for the rest of the UoS. Provide a forum to go over assignment solutions following marking Make assignment rubric available before submission Consolidated FEA materials The catch-up tutorial is now at 5pm instead of 6pm

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

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

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