CIVL5999: Semester 1, 2020

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Units CIVL5999 Semester 1 2020 [Normal day]

Unit outline_

CIVL5999: Advanced Research and Analysis

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

This unit requires students to use a number of advanced experimental tools and techniques which they learn through project-based learning as well as a structured theoretical lecture program. It will be very useful as co-requisite study for students engaged in an experimental honours thesis topic. It also covers issues of basic electronic circuitry and signal processing, various analysis techniques using both simple and advanced statistics, and advanced data processing methods such as PIV and Fourier filtering. It will also prepare students for further research in industry or academia.

Unit details and rules

Academic unit	Civil Engineering
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	(CIVL2201 OR CIVL9201) AND (CIVL2611 OR CIVL9611) AND (CIVL2410 OR CIVL9410)
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Kapil Chauhan, kapil.chauhan@sydney.edu.au
Lecturer(s)	Kapil Chauhan, kapil.chauhan@sydney.edu.au

Type	Description	Weight	Due	Length
Skills-based evaluation	Laboratory	30%	Multiple weeks	3 lab sessions
Outcomes assessed:
Assignment	Assignments	30%	Multiple weeks	3 assignments
Outcomes assessed:
Presentation	Project: oral exam	20%	Week 13	n/a
Outcomes assessed:
Assignment	Project: report	20%	Week 13	n/a
Outcomes assessed:

Assessment summary

Assignments: Three weekly assignments based on content covered in lectures.
Laboratory: Three lab sessions focussed on a student’s stream (fluids, geomechanics or structures). Students are expected to write a brief lab report for each lab.
Project: Individual project on a self-designed experiment over 8 weeks during the semester. Students will write a report and prepare an oral presentation.

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	Fundamentals of physical measurements	Lecture (2 hr)
Week 02	Basic measurement analysis	Lecture (2 hr)
Week 03	Elements of data acquisition	Lecture (2 hr)
Week 04	Signal conditioning	Lecture (2 hr)
Week 05	Introduction to sensors/instruments	Lecture (2 hr)
Week 06	Communicating with a sensor/instrument	Lecture (2 hr)
Week 07	Feedback mechanisms	Lecture (2 hr)
Week 08	Measurements in geotechnical engineering	Lecture (2 hr)
Week 09	Measurements in fluids engineering	Lecture (2 hr)
Week 10	Measurements in structural engineering	Lecture (2 hr)
Week 11	Data presentation	Lecture (2 hr)
Week 12	Student presentations	Lecture (2 hr)
Week 13	Student presentations	Lecture (2 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.

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. communicate effectively to an engineering audience, through report writing and oral presentations
LO2. plan, conduct and interpret experiments
LO3. design a strategy for completion of the project
LO4. understand the fundamentals of electric circuits and electronics and of their importance to measurement
LO5. understand the importance of measurement in civil engineering and the criteria for appropriate and valid measurements
LO6. understand various analysis techniques and tools
LO7. understand signal conditioning, error analysis, statistical analysis
LO8. demonstrate familiarity with methods and application of measurement
LO9. demonstrate proficiency with common modern instruments used for data acquisition such as accelerometers, strain gauges, load cells, stand pipes, LVDTs, piezometers, velocimetry, proving rings, and others
LO10. collect qualitative data via surveys and/or interview and analyse them.

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.

New labs introduced

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

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