Outline

Overview

This unit of study consolidates students' knowledge of advanced concepts in digital modelling, visualisation media and digital fabrication techniques available for architectural design. The unit develops conceptual understanding of generative geometric logic through a case study analysis followed by a small design project. Students will explore the practical applications of the digital geometry they create using commercial modelling and rendering packages in conjunction with the digital fabrication equipment available in DMaF. It will help students: generate sophisticated digital geometry through pre-packaged techniques and scripting processes, assign colour and texture information, generate sophisticated images for visualization purposes and fabricate prototypes. At the conclusion of this unit students should be conversant with 3D modelling, photo-rendering and digital fabrication terminology and be able to generate complex 3D models. Class preparation: 3 hours/week, assessment preparation 8 hours/semester.

Unit details and rules

Academic unit	Architecture
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Anastasia Globa, anastasia.globa@sydney.edu.au
Tutor(s)	Tracy Du, yuqing.du@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	3. Interactive Bio-Environmets Canvas Submission: 19/11/24 Project Presentation: 19/11/24	40%	Formal exam period Due date: 19 Nov 2024 at 23:59	20-page PDF, 3D Print, Poster, Present
Outcomes assessed:
Assignment	1. Biological relationships Assignment	30%	Week 04 Due date: 23 Aug 2024 at 23:59	20-page PDF, 3D Print, Video 15 sec
Outcomes assessed:
Assignment	2. Bio-Inspired Prototypes Project presentation: 17/09/2024 Canvas Submission: 17/09/2024	30%	Week 08 Due date: 17 Sep 2024 at 23:59	20-page PDF, 3D model, Presentation
Outcomes assessed:
= group assignment ?

Assessment summary

Biological relationships: Working individually, students will produce a series of 3D digital models using Grasshopper which, describe your biological typology assembly based on your reference research. Students will be required to define the parametric logic and attributes of the assembly using diagrams, line drawings, shaded renders and text.
Bio-Inspired Prototypes: Students will need to demonstrate the development of their bio typologies at the scale of the body. An understanding of how the study operates as a performative structure in relation to the body will be investigated through diagrams, line drawings, renders, basic animation, text and a physical model.
Interactive Bio-Environments: Students will work within their team to further develop their bio-form-making strategy and their performative capabilities. Students will test their proposals through a series of chosen computational design strategies. Further to this, students will output their findings to a gaming engine and test a number of spatial scenarios. Students will present their work to the class in the form of a video presentation / or game play.

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:

Late submission penalties will apply as per the universities policy.

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Formal exam period	[Task 3.5] Assignment 3 Final Presentation.	Presentation (3 hr)
Week 01	[Task 1.1] The Biological Typology & Pattern Variation Introduction to tutors & semester brief. Introduction / Museum Visit	Tutorial (3 hr)
Week 02	[Task 1.2] Spatial Arrays Intermediate Grasshopper and design workflow. Continuation of component relationships, datasets and data trees.	Tutorial (3 hr)
Week 03	[Task 1.3] Spatial Composites Expanding on the booklet structure, content, layout and design for Assessment 1 submission. Progress Review Session.	Tutorial (3 hr)
Week 04	[Task 1.4] Fields and forces – Assessment 1 (30%) Due. Introducing Assessment 2: Bio-Inspired Prototypes	Tutorial (3 hr)
Week 05	[Task 2.1] Iterations + AI Progress review session	Tutorial (3 hr)
Week 06	[Task 2.2] Bio-Prototypes. Advanced computational concepts.	Tutorial (3 hr)
Week 07	[Task 2.3] Rendering Introduction Intro to the rendering within Rhino developing strategies for material mapping and lighting and animation	Tutorial (3 hr)
Week 08	[Task 2.4] Bio-Inspired Prototypes - Assignment 2 Submission due. Presentation	Presentation (3 hr)
Week 09	[Task 3.1] Hybrid or Chimera of bio typologies applied on a different scale – as the responsive spatial environment.	Tutorial (3 hr)
Week 10	[Task 3.2] Animation and Intercations. Interactive environments, Rhino + AI applications.	Tutorial (3 hr)
Week 11	[Task 3.3] Immersive environments & Group Feedback	Tutorial (3 hr)
Week 12	[Task 3.4] Preparation for Submission of Assignment 3. Submission due.	Tutorial (3 hr)

Attendance and class requirements

Online software modules: In this course, students, will be learning how to use the Rhino software for 3D modelling and its associated visual programming using Grasshopper. The course material delivered in class will be supplemented by the online courses offered by the Archistar Academy. Archistar has Essentials, Designer and Advanced modules for both Rhino and Grasshopper and a number of other programs, which are comprised of a collection of short and easy-to-follow video tutorials. At the end of each training module, there is an online exam offered by Archistar, which students must pass in order to obtain a certificate of completion. These certificates are recognised by the Australian Institute of Architects and can be included as part of a CV for employers. Students must complete the Essentials, Designer and Advanced modules for both Grasshopper in order to pass MARC6102. The modules must be completed outside of class time and certificates submitted as part of assessments 1 and 2.

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

Leah, N, Farahi, B, 2017, 3D Printed Body Architecture, John Wiley & Sons.
Aranda, B. & Lasch, C. 2006, Pamphlet Architecture 27: Tooling, Princeton Architectural Press.
Burry, J. & Burry M. 2010, The New Mathematics of Architecture, Thames & Hudson.
Burry, M. 2013, Scripting Cultures: Architectural Design and Programming, John Wiley & Sons.
Carpo, M. 2011, The Alphabet and the Algorithm, MIT Press.
Hensel, M. & Menges, 2008, Versality and Vicissitude, John Wiley & Sons.
Terzidis, K. 2006, Algorithmic Architecture, Oxford Press.
Kolarevic, B. 2003, Architecture in a Digital Age; Design and Manufacturing, Spoon Press

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. exercise critical thinking to empirically and creatively research and replicate a pre-existing system/precedent
LO2. demonstrate competency in 3D modelling, digital fabrication, computational design concepts and associated software literacy
LO3. utilise an understanding of the computational process in order to produce multiple imaginative solutions to a design problem
LO4. utilise rendering and simulation software as well as post-production techniques to produce a carefully crafted visualisation.
LO5. integrate knowledge gained on computational strategies into the design process to enable creative and innovative interactive solutions at various scales

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
	National Standard of Competency for Architects - 3.1. Design response integrates the objectives of brief, user intent and built purpose. 3.2. Application of creative imagination, aesthetic judgement and critical evaluation in formulating design options.
	National Standard of Competency for Architects - 3.8. Application of manual and digital graphic techniques and modelling to describe three-dimensional form and spatial relationships.
	National Standard of Competency for Architects - 3.5. Exploration and application of ordering, sequencing and modelling of three-dimensional form and spatial content.
	National Standard of Competency for Architects - 3.5. Exploration and application of ordering, sequencing and modelling of three-dimensional form and spatial content. 3.8. Application of manual and digital graphic techniques and modelling to describe three-dimensional form and spatial relationships.
	National Standard of Competency for Architects - 3.2. Application of creative imagination, aesthetic judgement and critical evaluation in formulating design options. 3.5. Exploration and application of ordering, sequencing and modelling of three-dimensional form and spatial content.

Responding to student feedback

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

Increased the proportion of individual assessments and work vs group work

Additional information

Additional costs

Additional costs will be incurred for physical outputs using the digital fabrication equipment in DMAF (3D printing).

Work, health and safety

Students will be required to use 3D printing for their assignments.

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

Support for students

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

Work, health and safety

Disclaimer

On this page

Useful links

MARC6102: 3D Computer Design Modelling

Semester 2, 2024 [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

Support for students

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

Work, health and safety

Disclaimer

On this page

Useful links