AMME2500: Semester 1, 2025

Overview

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 ?	{(MATH1X61 or MATH1971) or [(MATH1X21 or MATH1931) and MATH1X02]} and [(MATH1X62 or MATH1972) or (MATH1X23 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)	Ankith Anil Das, ankith.anildas@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Supervised exam ?	Final exam Final Exam. Hurdle task, set at 40%	60%	Formal exam period	2 hours
Outcomes assessed:
Small continuous assessment	Weekly tutorial problems Work in small groups. Marked off by tutors	5%	Multiple weeks	2 hr per week during allocated tutorial
Outcomes assessed:
Small test	Major Assignment Prospectus Form groups and plan Major Project including division of group member responsibilities This is an individual submission and is your Early Feedback Task #earlyfeedbacktask	1%	Week 03 Due date: 14 Mar 2025 at 23:59 Closing date: 17 Mar 2025	2 hr
Outcomes assessed:
Small test	Quiz 1 problem solving, analysis, calculation	5%	Week 05 Due date: 24 Mar 2025 at 09:00 Closing date: 24 Mar 2025	1 hr
Outcomes assessed:
Small test	Quiz 2 problem solving, analysis, calculation	5%	Week 10 Due date: 05 May 2025 at 09:00 Closing date: 05 May 2025	1 hr
Outcomes assessed:
Assignment	Major Assignment Group Report problem solving, analysis, calculation, computer-based analysis and report You will be required to review your performance and that of your team members using SPARKPLUS. Individual marks for group assessments will be determined using these reviews	14%	Week 13 Due date: 30 May 2025 at 23:59 Closing date: 09 Jun 2025	Average student 12 hours
Outcomes assessed:
Assignment	Lab reports Reports on lab activities: online materials/videos/datasets provided. Lab report is submitted individually. No extensions are possible.	10%	Week 13 Due date: 30 May 2025 at 23:59 Closing date: 06 Jun 2025	Average student 8 hours
Outcomes assessed:
= hurdle task ? = group assignment ? = AI allowed ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Tutorials: Tutorials will run weeks 1-12. Problems are solved collaboratively and individual mark is awarded.
Quizzes: Quizzes will test Modules 1, 2 and 3.
Major Assignment: This will involve student groups performing computational modelling of a dynamic system.
Lab reports: The two laboratories are worth 5% each, and are assessed based on a written report. Online materials are provided incuding a Canvas module to work through containing reading material and video demonstrations.

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.

Use of generative artificial intelligence (AI) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

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:

As per university policy

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.

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.

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

Weekly schedule

WK	Topic	Learning activity
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)
	Weeks 1,2,3. Module 1: Dynamics of point-mass systems	Lecture and tutorial (18 hr)
	Weeks 5,6. Module 2: Introduction to vibration	Lecture and tutorial (12 hr)
	Weeks 8,9,11,12. Module 3: Dynamics of rigid body systems	Lecture and tutorial (24 hr)
	Weeks 4,7,10: Module 4: Computational dynamics	Lecture and tutorial (18 hr)
Week 13	Week 13. Course Review	Lecture (3 hr)

Attendance and class requirements

Attendance: Attendance at all lectures, designated tutorial and laboratory sessions in expected. Non-attendance at laboratory sessions or tutorials will result in a mark of zero for those assessment items.

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

James L. Meriam, L. G. Kraige, J. N. Bolton, Engineering Mechanics: Dynamics, 9th Australia & New Zealand Edition

ISBN: 978‐1119‐39098‐5

Available as an e-text: https://www.wileydirect.com.au/blog/buy/engineering-mechanics-dynamics-si-version-australia-new-zealand-edition/

The book is essential. The course follows the text book closely. Example and tutorial problems are taken from it.

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. 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.
LO13. confirming achievement of minimum engineering dynamics knowledge

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.

Student feedback is an important part of the continual development and refinement of AMME2500/9500. This year we have made the following changes: 1. Theory is being presented through pre-recorded lectures which students can watch during the allocate time or at another time of their choosing 2. Worked examples and practical demonstrations will be given during the weekly lectorial (Wednesday 9 - 11) 3. The computational dynamics module will be presented in three stages over the whole semester, giving students longer to prepare the major assignment 4. The major assignment will be more open ended and students will be rewarded for novelty and creativity 5. Sparkplus will be used for the major assignment 6. To cater for the increased class size, the laboratory session will be condensed to 1.5 hours and supplemented by some demonstrations during the lectorials

Additional information

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

Self and peer review of team contribution: All group assessments require you to review your performance and that of your team members using SPARKPLUS. Individual marks for group assessments will be determined using these reviews

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.

This unit of study outline was last modified on 11 Mar 2025.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

AMME2500: Engineering Dynamics

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI) and automated writing tools

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

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

Additional information

Additional information

Additional costs

Work, health and safety

Disclaimer

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Student links

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