Outline

Overview

The unit will provide an avenue to apply the mathematics concurrently taught in year one, enhance computing skills and data analysis as well as furthering and cementing knowledge provided in AMME1705. The unit is aimed at providing an overview on conducting experiments, data acquisition and data analysis, thus expanding and providing further foundation on the faculty vision of large digital data analysis.

Unit details and rules

Unit code	AERO2710
Academic unit	Aerospace, Mechanical and Mechatronic
Credit points	6
Prohibitions ?	None
Prerequisites ?	AERO1560 and ENGG1810 and AMME1705
Corequisites ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Nicholas Lawson, nicholas.lawson@sydney.edu.au
Lecturer(s)	Nicholas Lawson, nicholas.lawson@sydney.edu.au
Tutor(s)	Nishanth Menakath, nishanth.menakath@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Group Lab Report 1 Group report of Laboratory 1 data processing, analysis and presentation	16%	Please select a valid week from the list below Due date: 17 Mar 2023 at 23:59 Closing date: 26 May 2023	10 - 20 pages
Outcomes assessed:
Assignment	Group Lab Report 2 Group report of Laboratory 2 data processing, analysis and presentation	16%	Please select a valid week from the list below Due date: 07 Apr 2023 at 23:59 Closing date: 26 May 2023	10 - 20 pages
Outcomes assessed:
Assignment	Group Lab Report 3 Group report of Laboratory 3 data processing, analysis and presentation	16%	Please select a valid week from the list below Due date: 05 May 2023 at 23:59 Closing date: 26 May 2023	10 - 20 pages
Outcomes assessed:
Assignment	Group Lab Report 4 Group report of Laboratory 4 data processing, analysis and presentation	16%	Please select a valid week from the list below Due date: 19 May 2023 at 23:59 Closing date: 26 May 2023	10 - 20 pages
Outcomes assessed:
Assignment	Group Lab Report 5 Group report of Laboratory 5 data processing, analysis and presentation	16%	Please select a valid week from the list below Due date: 02 Jun 2023 at 23:59 Closing date: 02 Jun 2023	10 - 20 pages
Outcomes assessed:
Presentation	Lab Group Presentation Group presentation on a selected group laboratory	10%	Please select a valid week from the list below Due date: 26 May 2023 at 14:59 Closing date: 26 May 2023	up to 20 mins
Outcomes assessed:
Presentation	Tutorial Assessment 4 Group task set and data & method presented at end of each tutorial class	2.5%	Please select a valid week from the list below Due date: 05 May 2023 at 12:59 Closing date: 05 May 2023	up to 10 mins
Outcomes assessed:
Presentation	Tutorial Assessment 3 Group task set and data & method presented at end of each tutorial class	2.5%	Please select a valid week from the list below Due date: 28 Apr 2023 at 12:59 Closing date: 28 Apr 2023	up to 10 mins
Outcomes assessed:
Presentation	Tutorial Assessment 2 Group task set and data & method presented at end of each tutorial class	2.5%	Please select a valid week from the list below Due date: 31 Mar 2023 at 12:59 Closing date: 31 Mar 2023	up to 10 mins
Outcomes assessed:
Presentation	Tutorial Assessment 1 Group task set and data & method presented at end of each tutorial class	2.5%	Please select a valid week from the list below Due date: 10 Mar 2023 at 12:59 Closing date: 10 Mar 2023	up to 10 mins
Outcomes assessed:
= group assignment ?

Assessment summary

Assignments: Assignment reports will cover the 5 laboratories completed by the groups of students which will cover a cylinder wake, a heated cylinder, a boundary layer transition, a wing bending measurement and a free flight glider. Different groups will be assigned for each report and each group member will receive a weighted mark based on a Sparkplus survey from the rest of the group members.
Tutorial Assessments: In 4 of the 5 tutorial sessions, students will be set a basic data processing and data analysis task in their current group and will be required to present data and a solution to the problem at the end of the tutorial session, with a maximum direction of 10 mins, through a simple group demonstration to all the students. An assessment grading of the final solution will be made based on this demonstration, presentation of the method and the answers given to questions from the lecturer, tutor and their peers. All students must attend these sessions to receive a mark. Non-attendence by any given group member will result in a nil mark for that group member.
Lab Group Presentation: A group presentation of up to 20 mins long must be made by the current set groups of students on a laboratory completed throughout the semester. This laboratory will be set by the lecturer up to two weeks ahead of the presentation date. The assessment mark for each group will be made based on the presentation quality and content from the group and the answers given to questions from the lecturer, tutor and their peers.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2021 (sydney.edu.au) (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	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an exceptional standard as defined by grade descriptors or exemplars established by the faculty.
Distinction	75 – 84	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a very high standard as defined by grade descriptors or exemplars established by the faculty.
Credit	65 – 74	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a good standard as defined by grade descriptors or exemplars established by the faculty.
Pass	50 – 65	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an acceptable standard as defined by grade descriptors or exemplars established by the faculty.
Fail	0 – 50	To be awarded to students who, in their performance in assessment tasks, fail to demonstrate the learning outcomes for the unit at an acceptable standard established by the faculty. This grade, with corresponding mark, should also be used in cases where a student fails to achieve a mandated standard in a compulsory assessment, thereby failing to demonstrate the learning outcomes to a satisfactory standard. In such cases the student will receive the mark awarded by the faculty up to a maximum of 49.

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.

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:

The penalty for lateness is 5% per day. The penalty would apply from the next calendar day after the deadline. The penalty is a percentage of the available mark and is applied to the mark gained after the submitted work is marked (e.g., an assignment worth 100 marks is 1 day late. The content is given a mark of 75. With the 5% penalty, the final mark is 70).

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
Multiple weeks	Independent study – class preps and report writing	Independent study (65 hr)
Week 01	Intro, data, definitions & error analysis	Lecture (3 hr)
	Laboratory 1 – Background and briefing	Lecture (2 hr)
	Laboratory 1 – Signal / data processing	Lecture (2 hr)
Week 02	Laboratory 1 – Data collection	Practical (5 hr)
Week 03	Tutorial 1 – Signal / data processing / group work	Lecture and tutorial (3 hr)
Week 04	Laboratory 2 – Background and briefing	Lecture (2 hr)
	Laboratory 2 – Signal / data processing	Lecture (2 hr)
	Laboratory 3 – Background and briefing	Lecture (2 hr)
	Laboratory 3 – Signal / data processing	Lecture (2 hr)
Week 05	Laboratory 2 – Data collection	Practical (5 hr)
Week 06	Tutorial 2 – Signal / data processing / group work	Lecture and tutorial (3 hr)
Week 07	Laboratory 4 – Background and briefing	Lecture (2 hr)
	Laboratory 4 – Signal / data processing	Lecture (2 hr)
	Laboratory 5 – Background and briefing	Lecture (2 hr)
	Laboratory 5 – Signal / data processing	Lecture (2 hr)
Week 08	Laboratory 3 – Data collection	Practical (5 hr)
Week 09	Tutorial 3 – Signal / data processing / group work	Lecture and tutorial (3 hr)
Week 10	Laboratory 4 – Data collection	Practical (5 hr)
Week 11	Tutorial 4 – Signal / data processing / group work	Lecture and tutorial (3 hr)
Week 12	Laboratory 5 – Data collection	Practical (5 hr)
Week 13	Tutorial 5 – Signal / data processing / group work	Lecture and tutorial (3 hr)
Week 13	Laboratory Group Presentation	Presentation (2 hr)

Attendance and class requirements

Lectures : A total of 23 hours of lectures over the 13 week semester.
Tutorial: Tutorials with examples and group work on open ended problems, to encourage innovation in data processing and analysis methods. Five sessions with a duration of 3 hours / session. Due to the group nature of the tutorials, all students are required to attend.
Independent Study: In order to complete assignments and to understand the concepts and applications presented, students will be required to engage in self-study.

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 compulsory readings for this unit can be accessed through Canvas.

Recommended texts and resources:

Measurement and instrumentation : theory and application, Morris, A.S., Langari, R., 2021, 3rd Edition, London, England : Academic Press (available online from USyd library)

Springer Handbook of Experimental Fluid Mechanics (2007)
Editors: Cameron Tropea, Alexander L. Yarin, John F. Foss

The Scientist and Engineer's Guide to Digital Signal Processing, by Steven W. Smith (available online - http://www.dspguide.com/pdfbook.htm)

Additional Online text resources will be supplied for private study as required throughout the course.

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.

At the completion of this unit, you should be able to:

LO1. investigate available literature to build up background information on set laboratory problems
LO2. understand concepts of aeronautical measurements including pressure, thermal, optical, structural and airborne measurands
LO3. apply scientific principles to a particular situation to obtain solutions to experimental problems
LO4. complete a set of group laboratory reports on aspects of aeronautical measurements including pressure, thermal, optical, structural and airborne measurands
LO5. work as a team to efficiently manage a set of laboratory experiments, present solutions and produce results that meet set deadlines
LO6. present laboratory data and a group laboratory report to a group of colleagues
LO7. understand lab and health and safety requirements

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

Alignment with Competency standards

Outcomes	Competency standards
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice.
	Engineers Australia Curriculum Performance Indicators - 4.3. Proficiency in the engineering design of components, systems and/or processes in accordance with specified and agreed performance criteria. 5.3. Skills in the selection and characterisation of engineering systems, devices, components and materials. 5.4. Skills in the selection and application of appropriate engineering resources tools and techniques, appreciation of accuracy and limitations;.
	Engineers Australia Curriculum Performance Indicators - 4. ENGINEERING APPLICATION EXPERIENCE
	Engineers Australia Curriculum Performance Indicators - 3.1. An ability to communicate with the engineering team and the community at large. 4.4. Skills in implementing and managing engineering projects within the bounds of time, budget, performance and quality assurance requirements.
	Engineers Australia Curriculum Performance Indicators - 3.1. An ability to communicate with the engineering team and the community at large. 4.4. Skills in implementing and managing engineering projects within the bounds of time, budget, performance and quality assurance requirements.
	Engineers Australia Curriculum Performance Indicators - 3.1. An ability to communicate with the engineering team and the community at large. 5.3. Skills in the selection and characterisation of engineering systems, devices, components and materials. 5.4. Skills in the selection and application of appropriate engineering resources tools and techniques, appreciation of accuracy and limitations;.
	Engineers Australia Curriculum Performance Indicators - 4.3. Proficiency in the engineering design of components, systems and/or processes in accordance with specified and agreed performance criteria.

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Additional worked examples and tutorial exercises have been developed for the unit and will be presented and discussed in the lectures and tutorials.

Additional information

Additional costs

N/A

Site visit guidelines

N/A

Work, health and safety

Students will be briefed on the health and safety requirements in the laboratories, ahead of attending the laboratory sesssions.

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

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

AERO2710: Analysis of Aerospace Engineering Data

Semester 1, 2023 [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

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect