Outline

Overview

Develop an essential understanding of structure-property relationship of smart materials, as well as their applications in practical applications; develop student's capability to design functional structures using smart materials; and provide students an opportunity to learn the new knowledge through project approaches.

Unit details and rules

Academic unit	Aerospace, Mechanical and Mechatronic
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Fundamental knowledge in materials science and engineering: 1) atomic and crystal structures 2) metallurgy 3) structure-property relationship 4) mechanics of engineering materials 5) solid mechanics
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Matthew Griffith, matthew.griffith@sydney.edu.au
Laboratory supervisor(s)	Hongjian Wang, hong.j.wang@sydney.edu.au
Lecturer(s)	Lin Ye, lin.ye@sydney.edu.au
Tutor(s)	Yuan Chen, yuan.chen1@sydney.edu.au
Tutor(s)	Youchuan Zhou, yzho3611@uni.sydney.edu.au

Type	Description	Weight	Due	Length
Presentation	Group Presentation Presentations on group project work.	10%	Multiple weeks	15 min for three slots for each group
Outcomes assessed:
Presentation	Presentation on Case Studies Presentations on case studies	10%	Multiple weeks	10 min for each case study
Outcomes assessed:
Assignment	Assignment 1 Design, Analysis, Characterisation, Calculations, etc.	10%	Week 06 Due date: 11 Sep 2022 at 23:59	6 weeks
Outcomes assessed:
Assignment	Assignment 2 A report on a specific smart material based on self-study	10%	Week 06 Due date: 11 Sep 2022 at 23:59	6 weeks
Outcomes assessed:
Small test	Quiz 1 Assessment on knowledge in weeks 1-6	22.5%	Week 07	1 hr
Outcomes assessed:
Assignment	Group Project Report A group report for the group project work	10%	Week 13	10 pages (core part), excl appendix
Outcomes assessed:
Small test	Quiz 2 Assessment on all case studies and project work of all groups	22.5%	Week 13	1 hr
Outcomes assessed:
Assignment	Logbook An individual NOTEBOOK on group project work (not one of stapled sheets)	5%	Week 13 Due date: 06 Nov 2022 at 23:59	5 weeks
Outcomes assessed:
= group assignment ?

Assessment summary

Presentation/Seminar: Presentation on a research paper after intensive studies
Quiz: In-class assessment
Report: Final group project report
Assignment: Assignments
Presentation/Seminar (group): Presentations on project progresses and results

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 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.

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	Introduction, Electrical Resistivity, Assignments 1 and 2 out	Lecture and tutorial (4 hr)
Week 02	Piezo-resisitivity	Lecture and tutorial (4 hr)
Week 03	Shape Memory Materials	Lecture and tutorial (4 hr)
Week 04	Piezoelectric Materials, Case Studies Out	Lecture and tutorial (4 hr)
Week 05	Magneto-Restrictive Materials, ER/MR Fluids, ER/MR Elastomers	Lecture and tutorial (4 hr)
Week 06	Optical Fibre Sensors, Assignments 1 and 2 Due	Lecture and tutorial (4 hr)
Week 07	Quiz 1, Case Study Presentations	Performance (5 hr)
Week 08	Case Study Presentations	Presentation (5 hr)
Week 09	Case Study Presentations	Presentation (5 hr)
Week 10	Project Work, Group Presentations	Project (5 hr)
Week 11	Project Work, Group Presentations	Project (5 hr)
Week 12	Project Work, Group Presentations	Project (5 hr)
Week 13	Quiz 2, Group Report and Logbook due	Project (5 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

The in-class quizzes will be conducted during the lecture time.

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. design and construct simple functional structures using smart materials
LO2. describe and characterise mechanical behaviour of smart materials
LO3. characterise interaction between smart materials and simple structures in actuation and sensing
LO4. describe and characterise novel functions of smart materials using structure-property relationships
LO5. present and demonstrate the functions of smart structures.

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.

No significant changes have been made since this unit was last offered.

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

On this page

Useful links

MECH5305: Smart Materials

Semester 2, 2022 [Normal day] - Camperdown/Darlington, Sydney

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

On this page

Useful links