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Unit outline_

DESC9674: Building Information Management

Semester 1, 2022 [Block mode] - Camperdown/Darlington, Sydney

This unit will introduce students to the theory and practice of building information management and modelling. The unit starts with building management, which brings knowledge and skill on how to operate buildings to optimise performance. It also introduces Building Information Modelling (BIM), which is a digital representation of physical and functional characteristics of a facility. Building information models are shared knowledge resources about a facility, forming a reliable basis for decisions during its life-cycle from earliest conception to demolition. The unit explores the wider use of building information models not only in design but also in construction management, facility management, post construction evaluation, and retrofitting. By bringing together the building management and the information modelling, the unit responds to emergent requirements within the building sector for new tools and practices to offset the growing complexity in the design and construction of high performance buildings.

Unit details and rules

Academic unit Architectural and Design Science
Credit points 6
Prerequisites
? 
DESC9200 and DESC9014
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Jungsoo Kim, jungsoo.kim@sydney.edu.au
Lecturer(s) Gavin Crump, gavin.crump@sydney.edu.au
Type Description Weight Due Length
Assignment Modelling and interoperability
Modelling
40% Week 08
Due date: 13 Apr 2022 at 23:59
n/a
Outcomes assessed: LO2 LO3 LO4
Assignment Model and design analysis
Design, analysis and report
60% Week 13
Due date: 25 May 2022 at 23:59
1000 word
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6

Assessment summary

 

  • Modelling and Interoperability: Utilising tools in Revit, the student will follow step by step instructions from the instructor to model a ‘Basic house’ for a hypothetical client. The model will be exported into Rhinoceros where materials will be applied and when complete will be connected to an Augmented Reality app (Fologram and/or Shapediver). Various solutions will be explored to enable the transfer of BIM data to the Rhino model so it can be taken advantage of in the AR experience scripting. Students will submit their model and dataset(s) for review, enabling them to showcase their AR creation to their client on a mobile device or tablet.

  • Model and design analysis: The student will optimise the building from assessment 1 in regard to thermal comfort and energy performance, whilst considering other aspects such as view aspect. Utilising a Revit base model as well as their choice of environmental analysis software (with the demonstrated option being Grasshopper/Ladybug tools), the student must demonstrate a proposal in answer to the client brief through a report supported with numerical and visual data produced via the BIM and/or analysis software.

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

Work of outstanding quality, demonstrating mastery of the learning outcomes assessed. The work shows significant innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or exceptional skill.

Distinction

75 - 84

Work of excellent quality, demonstrating a sound grasp of the learning outcomes assessed. The work shows innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or superior skill.

Credit

65 - 74

Work of good quality, demonstrating more than satisfactory achievement of the learning outcomes assessed, or work of excellent quality for a majority of the learning outcomes assessed.

Pass

50 - 64

Work demonstrating satisfactory achievement of the learning outcomes assessed.

Fail

0 - 49

Work that does not demonstrate satisfactory achievement of one or more of the learning outcomes assessed.

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:

Work submitted after the deadline will incur a penalty of 5% of the total marks earned for the assessment per calendar day. Work submitted 20 calendar days or more after the deadline will not be assessed and will receive a mark of zero.

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
Week 01 1. Unit introduction; 2. What is BIM; 3. Digital model authoring; 4. Digital model analysis Lecture (7 hr) LO1 LO3
Week 02 1. BIM framework and standards; 2. Computation; 3. Prototyping and DFMA 4. Training 1/2 day - model federation/coordination Lecture and tutorial (7 hr) LO1 LO2 LO3
Week 04 Training day: Revit modelling, Rhino interoperability, ancillary model uses Tutorial (7 hr) LO1 LO2 LO3 LO4 LO5
Week 07 Digital engineering - 1. Planning and briefing; 2. Civil/Survey; 3. Structural MEP; 4. Construction; 5. Facilities Management Lecture (7 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 11 Training day: Revit model adjustment, Revit data extraction, Cloud-based environmental/energy analysis Tutorial (7 hr) LO1 LO2 LO3 LO4 LO5 LO6

Attendance and class requirements

Please refer to the Resolutions of the University School: http://sydney.edu.au/handbooks/architecture/rules/faculty_resolutions.shtml

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 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. apply knowledge of BIM workflows into real-world practices
  • LO2. use Revit and interoperate outputs with other software
  • LO3. apply knowledge of digital tools into real-world practice
  • LO4. demonstrate an understanding of emerging technologies and future trends
  • LO5. apply skills of modelling to evaluate sustainable design proposals
  • LO6. present and report outcomes of design analysis.

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.

The curriculum was adjusted significantly in 2020, however is kept in similar structure for 2021 on the back of generally positive student feedback. Some minor changes are implemented based on feedback however, including: • Updates to some slides/case studies in the lectures to capture changes over the past year • Updates to some regulation/framework references to capture changes over the past year • Greater freedom for choice of modelling techniques/scope in Assessment 1 (student’s choice) • Introduction of Shape diver as an optional tool to explore during Assessment 1 • Introduction of Speckle systems as an optional tool to explore during Assessment 2 • Optional ability to collaborate in a team during the first Lab if on campus (unmarked) • Introduction of Python/API teaching to the final lab session (unmarked)

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.