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Unit outline_

AMME5912: Crash Analysis and Design

Semester 1, 2023 [Normal day] - Camperdown/Darlington, Sydney

The objective of the course is to give students skills in the area of highly non-linear finite element analysis. Major topics covered include CAD, Implicit / explicit codes, Wire frame geometry, Elemental Theory, Materials, Pre-processing using ETA-PreSys, Contact, LS-Dyna, using NCAC FEM models, Modeling fasteners and the interaction between solids and fluids. Material covered in lectures is reinforced through independent research, assignments, quizzes and a major capstone project. The capstone project involves the development of an approved crash scenario.

Unit details and rules

Academic unit Aerospace, Mechanical and Mechatronic
Credit points 6
Prerequisites
? 
(MECH2400 or MECH9400) and (AMME2301 or AMME9301) and MECH3460 and MECH3361. Computer Aided Drafting, Basic FEA principles and Solid Mechanics.
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Paul Briozzo, paul.briozzo@sydney.edu.au
Lecturer(s) Paul Briozzo, paul.briozzo@sydney.edu.au
Type Description Weight Due Length
Assignment Assignment 1
Assessment is by way of a report and attached .avi files.
20% Week 04
Due date: 17 Mar 2023 at 23:59

Closing date: 07 Apr 2023
No more than twenty A4 pages in total.
Outcomes assessed: LO1 LO3 LO4 LO6 LO7 LO8 LO9
Assignment Assignment 2
Assessment is by way of a report and attached .avi files.
20% Week 07
Due date: 06 Apr 2023 at 23:59

Closing date: 27 Apr 2023
No more than twenty A4 pages in total.
Outcomes assessed: LO4 LO5 LO7 LO8 LO9
Assignment Assignment 3
Assessment is by way of a report and attached .avi files.
20% Week 10
Due date: 05 May 2023 at 23:59

Closing date: 19 May 2023
No more than twenty A4 pages in total.
Outcomes assessed: LO4 LO5 LO7 LO8 LO9
Assignment group assignment Project
Assessment is by way of a capstone project and attached .avi files.
30% Week 13
Due date: 26 May 2023 at 23:59

Closing date: 16 Jun 2023
No more than forty pages in total.
Outcomes assessed: LO1 LO9 LO8 LO7 LO6 LO4 LO3
Presentation group assignment Presentation / Audio Embedded Powerpoint
Content to be drawn from work undertaken on Project.
10% Week 13
Due date: 26 May 2023 at 23:59

Closing date: 16 Jun 2023
No more than 6 minutes.
Outcomes assessed: LO2
group assignment = group assignment ?

Assessment summary

  • Assignment 1: Assignment 1 is assessed as a written report that examines an individual student’s ability to demonstrate effective use of a pre-processor, solver and post-processor. The focus of the report is to be focused on a typical crash scenario.
  • Assignment 2: Assignment 2 is assessed as a written report that examines an individual student’s ability to demonstrate effective use of a pre-processor, solver and post-processor.
  • Assignment 3: Assignment 3 is assessed as a written report that examines an individual student’s ability to demonstrate effective use of a pre-processor, solver and post-processor.
  • Project and group presentation: A group project that focuses on bringing individual skills together in an FEA capstone project involving either a large multi-body crash-simulation or a simulation incorporating multi-physics. Assessment is by way of a presentation and group report.
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

Awarded when students demonstrate the learning outcomes for the unit at an exceptional standard.

Distinction

75 - 84

Awarded when students demonstrate the learning outcomes for the unit at a very high standard.

Credit

65 - 74

Awarded when students demonstrate the learning outcomes for the unit at a high standard.

Pass

50 - 64

Awarded when students demonstrate the learning outcomes for the unit at an acceptable standard.

Fail

0 - 49

Awarded when students do not 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 Non-contact independent work doing research, homework, and working on assignments, group meetings and prior readings across multiple weeks, Independent study (78 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9
Week 01 Introduction to LS-Dyna and explicit codes Lecture and tutorial (4 hr) LO3 LO4
Week 02 Pre and post processors - ETA-PreSys Lecture and tutorial (4 hr) LO4 LO8 LO9
Week 03 Editing keyword files (decks) by hand Lecture and tutorial (4 hr) LO6
Week 04 Elemental theory and usage in LS-Dyna Lecture and tutorial (4 hr) LO7
Week 05 Material theory and usage in LS-Dyna Lecture and tutorial (4 hr) LO8
Week 06 Super Tutorial Lecture and tutorial (4 hr) LO4 LO5 LO6 LO7 LO8 LO9
Week 07 Meshing Lecture and tutorial (4 hr) LO4
Week 08 Contact theory and usage in LS-Dyna Lecture and tutorial (4 hr) LO9
Week 09 Fastener theory and usage in LS-Dyna Lecture and tutorial (4 hr) LO3 LO7
Week 10 Use of NCAC FEM models Lecture and tutorial (4 hr) LO4 LO5 LO6 LO8
Week 11 SPH - smoothed particle hydrodynamics method Lecture and tutorial (4 hr) LO1 LO6 LO7 LO9
Week 12 ALE - arbitrary Lagrangian-Eulerian method Lecture and tutorial (4 hr) LO1 LO6 LO7 LO8 LO9
Week 13 Super Tutorial Lecture and tutorial (4 hr) LO4 LO5 LO6 LO7 LO8 LO9

Attendance and class requirements

All group assessments require you to review your performance and that of your team members using SPARKPLUS.

Individual marks for group assessments will be adjusted based on these reviews.

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

LS-DYNA for Engineers: A Practical Tutorial Book, R. Lee and contributing author P. Latha, 1st Edition, 2019, BW Publications

ISBN 9781703208856

Available from,

https://www.amazon.com.au/LS-DYNA-Engineers-Practical-Tutorial-analysis/dp/1703208854

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. Present findings and results by way of producing a written capstone project at near publication quality.
  • LO2. Visually present and defend findings and results by way of a group presentation or audio embedded Powerpoint presentation.
  • LO3. Develop competentcy in the use of CAD to develop FEA models
  • LO4. Develop skills using a pre/post processor to mesh and apply boundary conditions to an FEA model.
  • LO5. Introduce predefined small FEA automotive models and develop these into a defined virtual environment.
  • LO6. Develop skills in editing and interpreting an LS-DYNA deck and output files.
  • LO7. Develop and master skills in selecting the correct element type when developing an FEA model.
  • LO8. Develop skills in the correct material model when developing an FEA scenario.
  • LO9. Develop skills in the correct contact method when developing an FEA model.

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.

In 2023 the Unit of Study has; 1. Introduced a Lecture and accompanying Tutorial on Post Processing. 2. Introduced a Lecture and accompanying Tutorial on vibration fatigue on structures.

Appeals to assessment results are subject to Clause 2.1 (1) (a), https://www.sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2012/253&RendNum=0,

i.e. 15 working days (3 weeks).

 

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.