‘This is a wonderful book that should be on the desk of every architect and planner. It shows how

Technology considerations
• 
Ensuring flexibility, expansion and adaptability for new technology in plan layout.
• 
Avoiding technical complexity to reduce risks of failure and avoid maintenance costs.
• 
Considering testing experimental green technologies.
• 
Designing for future upgrading and downsizing of mechanical equipment.
• 
Ensuring back-up mechanical equipment (where required) is not over-specified.
• 
Using automatic windows for night-time chilling of the structure.
• 
Using smart windows that shade automatically and generate electricity.
• 
Using photovoltaic cells that are integral to the roof or walls to generate electricity.
Construction process considerations
• 
Demanding minimal packaging of materials and products that are delivered to the
site.
• 
Evaluating relative eco-efficiency of on-site/off-site assembly of building components.
• 
Using performance-based contracting systems to provide incentives for eco-solutions.
• 
Ensuring that construction processes are eco-efficient, as well as building operation.
• 
Developing a comprehensive waste management plan for the construction process.
• 
Ensuring a construction safety plan is developed and implemented.
• 
Ensuring energy conservation measures are checked and fine-tuned after use.
• 
Conducting post-occupancy evaluation to ensure equipment operates properly.

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307
Boxes
Box 23 Digital Modelling for Sustainability
Professor Robin Drogemuller and Professor John Frazer 
Digital modelling tools are the next generation of computer aided design (CAD) tools for 
the construction industry. They allow a designer to build a virtual model of the building 
project before the building is constructed. This supports a whole range of analyses, and the 
identification and resolution of problems before they arise on-site, in ways that were previ
-
ously not feasible.
The current state of digital modelling tools for sustainability reflects the current structure of 
the construction industry. The CAD systems and analysis tools used by the various design 
disciplines are not well integrated and do not support whole-of-life analysis for buildings. The 
flows of information are disjointed and inefficient, and there are large gaps in the informa
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tion required to design buildings that are sustainable. However, there are indications that 
the situation is starting to improve. The building construction industry is in the process of 
moving from two-dimensional drawing to three-dimensional modelling. Three-dimensional 
(3D) CAD systems have been available for two decades but the uptake within the construc-
tion industry has been slow.
Those sectors of the industry that have been using 3D CAD are moving towards 3D model-
ling. For the present discussion, 3D CAD produces drawings and images that look correct to 
humans but only contain information on shapes, patterns and textures. There is no embedded 
information that allows walls to be differentiated from roofs or windows, for example. In 3D 
modelling systems, the ‘type’ of an object is defined within the system, along with informa
-
tion on the construction of the component. Modelling systems can also add intelligence by 
automatically joining walls where they touch each other, cutting openings in walls for windows, 
etc. This additional intelligence is important in supporting ease of use and also accuracy within 
the model.
The companies that develop 3D modelling software are following two complementary
approaches to improving the flow of information. Some companies are building suites of 
software that support a range of users and that all share the same data format.
1
Second, there 
are industry efforts to develop standards for interoperability (seamless information exchange) 
between software systems from different software companies. Interoperability is important 
since no one software company will ever have computer programs that cover every possible 
type of design or analysis problem.
Another parallel development is the emergence of parametric and constraint-driven digital 
modelling systems. These allow a range of alternative designs to be modelled using key 
parameters. For example, the number and capacity of lifts in a building could be a function 
of the number of people who will occupy the building, which can be derived from the area 
of the building and activities that will occur within it. These parameters can then be varied 
to move towards an optimal design across the range of design solutions. Recent designs 
by Frank Gehry using Digital Project show what can be achieved with this type of digital 
modelling system. 
The major technical impediment to sustainable building designs lies in analysing sustainability 
itself. Some areas of sustainability analysis, such as operational energy performance, are well 
served by analysis tools and the necessary data to run them. Other areas, such as analysing 
embodied energy, greenhouse gas emissions, biodiversity, health, etc, are poorly served by 
analysis tools and data.
Integration of analysis tools with digital models of the buildings would substantially reduce the 
time required to perform analyses, and would consequently allow sustainability to be consid
-
ered earlier in the design process. If sustainability analyses can be performed with minimal 
extra effort and within a reasonable amount of time, then a series of analyses of alternatives 
could be used to guide design at important stages within the design process.

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308
Positive Development
There are a number of significant technical developments that are needed before digital model
-
ling tools can support design for sustainability in a seamless manner:
•
Accurate data for sustainability for those areas of analysis that are poorly supported, 
such as whole-of-life impact assessment for the full range of materials and components 
used in buildings, embodied energy, assessing design for deconstruction and re-use, 
biodiversity, impact of site works, etc.
•
A wider range of analysis tools to improve support for areas such as embodied 
energy, pollutant emissions, and other factors involved in manufacturing, maintenance 
and recycling. These will need to support the inclusion of individual materials, single 
components and assemblies of components. These analysis tools will also need to 
support multiple stages of the design process by allowing ‘high’-level descriptions of 
entire assemblies, such as a timber truss roof with metal deck cladding and plasterboard 
ceiling and 100mm of fibreglass insulation at the early design stage, through to a full 
3D model of the roof framing system with individual members and connectors at the 
documentation stage of design.
•
Libraries of sustainability solutions that can be ‘dragged and dropped’ into digital 
modelling environments to allow rapid evaluation of alternatives.
•
Better integration of digital modelling and analysis tools to reduce the time required to 
prepare data for analysis. For example, LCADesign
2
uses a 3D building model as the 
basis for an eco-efficiency assessment of the building. The user spends between 30 and 
60 minutes entering specific data to the standard CAD model and then exports this 
information as an IFC
3
file. This file is then read in to LCADesign for analysis. Various 
substitutions can be made within LCADesign, such as changing non-load-bearing wall 
systems or floor coverings, so that a range of related alternatives can be explored in a 
few hours. LCADesign does not support major substitutions which have wide ranging 
implications, however, such as alternative structural systems (eg concrete frame versus 
load-bearing brickwork) or entire system options (eg ducted-air versus chilled-water 
air-conditioning systems).
The improvements described above are achievable within the current state of understanding 
of the building design process and the current capabilities of computer software. If we are to 
build high performance building optimization tools, it is necessary to link building information 
modelling with active design tools and generative and evolutionary design and analysis tech-
niques to form an iterative building performance optimization loop. 
Currently data and parametric functions and logical operators are all entered manually into a 
building information model, usually in an unstructured manner lacking any rigorous theoreti
-
cal basis. This is inefficient and labour intensive. Every building becomes a one-off prototype 
(a concept unthinkable in, say, the aircraft industry). The lack of structure in the model leads 
to later difficulties in changing the model or accessing the data efficiently in complicated 
models.
The output data could be subject to analysis of performance, structure, cost, etc. This can occur 
inside the system (such as with FEA analysis within Catia), or data can be exported with IFCs 
and subject to external analysis. But what happens to the results of the analysis? In most cases 
it requires tedious manual manipulation of the variables of the parametric model followed by 
a re-iteration of the whole process.
To improve the entire situation it is necessary to provide:
•
A theoretical framework which structures the building of the model so that it facilitates 
later change and improves data access
•
A methodology for automating or semi-automating the model building process 
•
The potential for automatic modification of the parameters on the basis of feedback 
from the analysis and evaluation step 
Of course, having the technology and capability is not enough. The social and commercial 
imperatives must also exist before the technology is used widely.

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309
Boxes