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Unit outline_

AMME2500: Engineering Dynamics

Semester 1, 2022 [Normal day] - Camperdown/Darlington, Sydney

This unit of study will focus on the principles governing the state of motion or rest of bodies under the influence of applied force and torque, according to classical mechanics. The course aims to teach students the fundamental principles of the kinematics and kinetics of systems of particles, rigid bodies, planar mechanisms and three-dimensional mechanisms, covering topics including kinematics in various coordinate systems, Newton's laws of motion, work and energy principles, impulse and momentum (linear and angular), gyroscopic motion and vibration. Students will develop skills in analysing and modelling dynamical systems, using both analytical methods and computer-based solutions using MATLAB. Students will develop skills in approximating the dynamic behaviour of real systems in engineering applications and an appreciation and understanding of the effect of approximations in the development and design of systems in real-world engineering tasks.

Unit details and rules

Academic unit Aerospace, Mechanical and Mechatronic
Credit points 6
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 (AMME1802 or ENGG1802)
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

Familiarity with the MATLAB programming environment

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Matthew Cleary, m.cleary@sydney.edu.au
Lecturer(s) Matthew Cleary, m.cleary@sydney.edu.au
Tutor(s) Abdulmalik Altaee, abdulmalik.altaee@sydney.edu.au
Robert Virgona, robert.virgona@sydney.edu.au
Moustafa Ali, moustafa.ali@sydney.edu.au
Type Description Weight Due Length
Final exam (Open book) Type C final exam Final exam
Final Exam (Canvas)
50% Formal exam period 2 hours
Outcomes assessed: LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO11 LO12
Assignment Lab reports
Reports on lab activities: online materials/videos/datasets provided
10% Multiple weeks Average student 8 hours
Outcomes assessed: LO1 LO2
Small continuous assessment Week 1 Tutorial
weekly tutorial questions
1% Week 01 2 hours
Outcomes assessed: LO5 LO12 LO10 LO9 LO8 LO7 LO6
Small continuous assessment Week 2 Tutorial
weekly tutorial questions
1% Week 02 2 hours
Outcomes assessed: LO5 LO12 LO10 LO9 LO8 LO7 LO6
Small continuous assessment Week 3 Tutorial
weekly tutorial questions
1% Week 03 2 hours
Outcomes assessed: LO2 LO12 LO11 LO7 LO6 LO3
Assignment Assignment 1
problem solving, analysis, calculation, computer-based analysis and report
10% Week 04
Due date: 19 Mar 2022 at 23:59
Average student 8 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO10 LO11 LO12
Small continuous assessment Week 5 Tutorial
weekly tutorial questions
1% Week 05 2 hours
Outcomes assessed: LO2 LO11 LO5 LO4 LO3
Small continuous assessment Week 6 Tutorial
weekly tutorial questions
1% Week 06 2 hours
Outcomes assessed: LO2 LO12 LO11 LO7 LO6 LO4 LO3
Small continuous assessment Week 7 Tutorial
weekly tutorial questions
1% Week 07 2 hours
Outcomes assessed: LO2 LO12 LO11 LO10 LO9 LO8 LO7 LO6 LO4 LO3
Small continuous assessment Week 8 Tutorial
weekly tutorial questions
1% Week 08 2 hours
Outcomes assessed: LO2 LO12 LO11 LO10 LO9 LO8 LO7 LO6 LO4 LO3
Assignment Assignment 2
problem solving, analysis, calculation, computer-based analysis and report
10% Week 09
Due date: 30 Apr 2022 at 23:59
Average student 8 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11 LO12
Small continuous assessment Week 10 Tutorial
Weekly tutorial problems
1% Week 10 2 hrs
Outcomes assessed: LO2 LO12 LO11 LO10 LO9 LO8 LO7 LO6 LO5 LO4 LO3
Small continuous assessment Week 11 Tutorial
Weekly tutorial problems
1% Week 11 2 hrs
Outcomes assessed: LO2 LO11 LO10 LO9 LO8 LO7 LO6 LO4 LO3
Small continuous assessment Week 12 tutorial
Weekly tutorial problems
1% Week 12 2 hrs
Outcomes assessed: LO2 LO12 LO11 LO9 LO8 LO3
Assignment Assignment 3
problem solving, analysis, calculation, computer-based analysis and report
10% Week 13
Due date: 28 May 2022 at 23:59
Average student 8 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO10
Type C final exam = Type C final exam ?

Assessment summary

  • Tutorials: Tutorials will run weeks 1-13 inclusive and will require the submission of a tutorial worksheet to the tutors during the tutorial, which will be marked. You will only receive your mark if you attend your allocated tutorial session and submit your worksheet to the tutors within the allocated time. 
  • Assignments: Assignments 1 and 2 will involve a combination of problem solving, analysis and calculation, computer-based analysis and report writing, based on topics presented in the associated lectures. Assignment 3 will involve students performing research into a dynamic system in an engineering application of their choice (for example industrial machinery, automotive suspension, aircraft/spacecraft flight dynamics, athletic biomechanics etc.) performing analysis and computer-based modelling of the system.
  • Lab reports: The two laboratories are worth 5% each, and are assessed based on a written report that must be submitted (via Canvas) for each lab. Online materials are provided incuding a Canvas module to work through containing reading material, video demonstrations and lab datasets to download and analyse in the student’s submitted lab reports.
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

Exceptional standard of work completed in meeting course learning outcomes.

Distinction

75 - 84

Very good standard of work completed in meeting course learning outcomes.

Credit

65 - 74

Good standard of work completed in meeting course learning outcomes.

Pass

50 - 64

Acceptable standard of work completed in meeting course learning outcomes.

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.

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.

WK Topic Learning activity Learning outcomes
Multiple weeks An average student should spent a total of 65 hours of independent study over the semester, including work on assessment tasks. Independent study (65 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11 LO12
Week 01 1. Introduction to dynamics; 2. Revision of selected mathematical topics; 3. Kinematics of particles in various coordinate systems Lecture and tutorial (5 hr) LO3 LO5 LO10
Week 02 Kinematics and kinetics of particles: relative and constrained motion, force mass and acceleration Lecture and tutorial (5 hr) LO2 LO3 LO5
Week 03 Kinematics and kinetics of particles: work, energy, impulse and momentum Lecture and tutorial (5 hr) LO2 LO3 LO4 LO5 LO12
Week 04 1. Kinetics of particles in relative frames of reference; 2. Angular momentum; 3. Kinetics of systems of particles Lecture and tutorial (5 hr) LO5 LO7 LO11
Week 05 1. Introduction to dynamics of rigid bodies; 2. Plane kinematics of rigid bodies Lecture and tutorial (5 hr) LO2 LO5 LO10 LO11 LO12
Week 06 Plane kinetics of rigid bodies: force, mass and acceleration Lecture and tutorial (5 hr) LO4 LO5 LO6 LO11 LO12
Week 07 Plane kinetics of rigid bodies: work, energy, impulse and momentum Lecture and tutorial (5 hr) LO4 LO5 LO6 LO7 LO11 LO12
Week 08 1. Modelling of system dynamics; 2. Numerical modelling techniques Lecture and tutorial (5 hr) LO3 LO8 LO10
Week 09 Three-dimensional kinematics of rigid bodies Lecture and tutorial (5 hr) LO5 LO11
Week 10 Three-dimensional kinetics of rigid bodies Lecture and tutorial (5 hr) LO4 LO6 LO11
Week 11 1. Three-dimensional kinetics of rigid bodies; 2. Dynamics of variable mass systems Lecture and tutorial (5 hr) LO4 LO6 LO11
Week 12 Dynamics of free and forced vibration Lecture and tutorial (5 hr) LO3 LO9 LO11 LO12
Week 13 Course review and revision Lecture (5 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11 LO12

Attendance and class requirements

Attendance: Attendance at all lectures and designated tutorial and laboratory sessions in both expected and compulsory.

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.

  • Engineering Mechanics: Dynamics, R.C. Hibbeler, Pearson, 2017
  • Engineering Mechanics: Dynamics, J.L. Meriam and L.G. Kraige, 6th or 7th Edition, Wiley, 2016

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. use basic information literacy skills to seek out existing approaches to the modelling and design of dynamic components of real engineering systems
  • LO2. communicate results in the analysis and solution to engineering problems involving dynamics through the logical presentation of problems solving steps, computer code and written reports
  • LO3. model and approximate real engineering scenarios to basic first-order systems of dynamical equations that can be analysed by the methods developed in the course
  • LO4. outline a logical approach to solving complex problems involving bodies undergoing acceleration based on common scenarios encountered in engineering
  • LO5. analyse problems involving varying coordinate systems, relative motion involving both translating and rotating frames of reference and apply principles of kinematics and kinetics to these systems
  • LO6. apply the principle of work and energy to both systems of particles and rigid-body planar kinetics
  • LO7. apply the principles of impulse, linear and angular momentum to both systems of particles and rigid-body planar kinetics
  • LO8. generate equations of motions for multi-degree of freedom systems involving particles and rigid bodies using free body diagrams and principles of kinetics
  • LO9. determine the equations of motion of free and forced vibrating mechanical systems
  • LO10. use basic computational tools and numerical methods in MATLAB to model, simulate and solve dynamic behaviours of multi-body systems
  • LO11. appreciate and understand fundamental principles in differential and integral calculus, vector calculus and linear algebra and their application in the derivation of dynamical equations of motion
  • LO12. use mathematical tools to analytically derive dynamical equations of motion and calculate results using these tools.

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.

Student feedback is an important part of the continual development and refinement of AMME2500/9500. This year we have refined lecture content, tutorial exercises and structure, assignment tasks.

Please refer to the Canvas site for additional course information including teaching staff details, online resources etc.

Additional costs

There are no additional costs for this unit.

Work, health and safety

This unit of study involves laboratory activities: please refer to the Canvas site and you lab demonstrator for safety requirements while working in the lab.

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.