11344 Computational Design for Decarbonisation

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Subject handbook information prior to 2025 is available in the Archives.

UTS: Design, Architecture and Building: Architecture
Credit points: 6 cp
Result type: Grade and marks

Requisite(s): 72 credit points of completed study in spk(s): C10413 Bachelor of Design Architecture Master of Architecture OR 72 credit points of completed study in spk(s): C10004 Bachelor of Design Architecture OR 72 credit points of completed study in spk(s): C10325 Bachelor of Design Architecture Bachelor of Creative Intelligence and Innovation OR 48 credit points of completed study in spk(s): C10271 Bachelor of Design Interior Architecture OR 48 credit points of completed study in spk(s): C10322 Bachelor of Design Interior Architecture Bachelor of Creative Intelligence and Innovation OR 48 credit points of completed study in spk(s): C10272 Bachelor of Design Interior Architecture Bachelor of International Studies OR 144 credit points of completed study in spk(s): C09079 Bachelor of Landscape Architecture (Honours)
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.

Description

The most urgent task design professionals face is reimagining the construction and operation of our built environment to respect planetary boundaries. The ability to negotiate many complex constraints and desires and to evaluate populations of possible outcomes both qualitatively and quantitatively offered by computational design processes make them invaluable tools in the transition towards a decarbonised built environment.

Students learn and apply computational design and evolutionary optimisation tools to negotiate solar and structural analysis and for a spatial design task emerging from a precedent case study. This subject is aimed at students from Architecture, Landscape Architecture and Interior Architecture.

Subject learning objectives (SLOs)

On successful completion of this subject, students should be able to:

1.	Demonstrate an ability to understand and interpret a precedent project’s performance in multiple ways.
2.	Demonstrate an ability to model a precedent project parametrically such that key parameters can be varied and the impact of this variation on various aspects of performance can be evaluated.
3.	Demonstrate an ability to implement and interpret solar simulation.
4.	Demonstrate an ability to implement and interpret a computational analysis simulation (eg structural analysis or an agreed alternate simulation appropriate to your discipline).
5.	Demonstrate an ability to design and implement a multi-criteria evolutionary optimisation system that allows for the selection of higher-performing designs from within a population.
6.	Demonstrate an ability to interpret analysis results and define design responses through a process of iterative feedback.
7.	Demonstrate an ability to communicate process and outcomes visually and verbally.

Course intended learning outcomes (CILOs)

This subject also contributes to the following Course Intended Learning Outcomes:

Communicate ideas professionally and effectively through a variety of mediums: oral, written, visual, physical and digital (C.2)
Creatively use architectural media, technologies and materials (I.2)
Understand and challenge disciplinary conventions through an engagement with emergent forms of architectural practice, technologies and modes of production (P.1)
Integrate an understanding of a relationship between form, materiality, structure and construction within design thinking (P.5)
Evidence disciplinary knowledge through the application of physical and/or digital mediums (P.6)
Define, develop and apply an appropriate design method in the execution of an architectural project (R.2)

Contribution to the development of graduate attributes

The term CAPRI is used for the five Design, Architecture and Building faculty graduate attribute categories where:

C = communication and groupwork

A = attitudes and values

P = practical and professional

R = research and critique

I = innovation and creativity.

Course intended learning outcomes (CILOs) are linked to these categories using codes (e.g. C-1, A-3, P-4, etc.).

Teaching and learning strategies

Content will be delivered through project-based learning. People enrolled to the subject will be expected to be actively involved in the tutorials to enrich the knowledge of the class.

This subject will take place in a computer lab. Sessions will involve a mix of guided instruction and demonstrations, student presentations and group-by-group desk-critiques.

Content (topics)

Architecture and Decarbonisation
Population thinking and evolutionary optimisation
Interpreting architectural projects parametrically
Building a Parametric Model
Implementing a simple evolutionary optimisation
Performing and interpreting solar simulations
Performing and interpreting structural simulations
Understanding the possible interrelations, trade-offs and synergies between solar and structural performance
Understanding the differences between quantitative and qualitative evaluation and their respective limits

Assessment

Assessment task 1: Computational Design

Intent:

This task aims to introduce students to the techniques and concepts of parametric modelling and to understanding projects not as static objects but instead as a variable system of possibilities.

Objective(s):

This task addresses the following subject learning objectives:

1, 2, 3 and 7

This task also addresses the following course intended learning outcomes that are linked with a code to indicate one of the five CAPRI graduate attribute categories (e.g. C.1, A.3, P.4, etc.):

C.2, I.2, P.1 and P.5

Type:

Project

Groupwork:

Group, individually assessed

Weight:

40%

Criteria linkages:

Criteria	Weight (%)	SLOs	CILOs
Precedent selection and performance analysis	20	1	P.1
Parametric interpretation and modelling of precedent	40	2	I.2
Analysis interpretation	20	3	P.5
Visual and verbal communication	20	7	C.2

SLOs: subject learning objectives
CILOs: course intended learning outcomes

Assessment task 2: Evolutionary Optimisation

Intent:

This task aims to introduce students to the concepts and techniques of multi-criteria evolutionary optimisation.