computers, design, generative design, software

1. GENERATIVE
DESIGN
A NEW PHASE IN DESIGN

2. INTRODUCTION
 Generative Design, in particular, an algorithmic approach, is an
efficient, rigorous, controllable, and flexible tool that allows, with
reduced time and effort, the production of several different models
to explore design variations addressing different types of change
 It is a design method in which the output – image, sound,
architectural models, animation – is generated by a set of rules or
an Algorithm, normally by using a computer program.

3. WHY USE ALGORITHM ???
 Algorithmic code is good for creating very complex geometries with
small amounts of data. It works very well with the way nature
constructs using cellular components. The fractal (or self similar)
nature that you see in trees and leaf veins and arteries is due to
this. But the code here is embedded in the cell itself and cells
organize themselves to create complex forms based on of relatively
simple code.

4. Typically, generative design has:
 A design schema
 A means of creating variations
 A means of selecting desirable outcomes
 It deals with the creation of images by using codes. An image is no
more created manually but through a visual idea which is translated
into a set of rules and then implemented in a programming
language in the form of source code. The consequence is that such
a program can not only create a single image but also completely
re-design visual worlds by changing the parameters.

6. ADVANTAGES
 Produce unique designs and
achieve variation of the same
design.
 In the traditional use of CAD tools,
when changes are needed, it
requires too much time and effort to
modify models & just one solution is
represented and the exploration of
different solutions requires manual
changes to the model. But in GD,
algorithms are translated in a
programming language and defined
parametrically, they automatically
embrace change
CHANGE IN SHAPE OF
WINDOW

7.  Algorithmic approach lays in the possibility of fast and effortless
generation of a wide range of solutions, exploring different design
approaches.
 The process logic rules however must be maintained up to dated
and ready for use. This provides the process planner with an
assurance that the processes generated will reflect state-of-the-art
technology.

8. CHANGE IN SHAPE OF THE BUILDING
AFTER INTRODUCING SEVERAL CHANGES

9. DISADVANTAGES
 It lacks a clear theoretical framework in generative design.
 if manual changes are made to the generated model, these
changes will be lost when the program is re executed and the model
regenerated.
 it requires an obvious initial investment

10. SERPENTINE GALLERY PAVILLION, 2002CASE STUDY 1

11. Facts and figures
 Structural Engineer : Arup Advanced Geometry
 Location : London
 Project Objective : Create a temporary
pavilion for visitors for a
short period of 2-3 months
exploration.
 Architects : Toyo Ito, Cecil
Balmond

12. INTRODUCTION
 The Serpentine Gallery Pavilion 2002 appeared to be an extremely
complex random pattern that proved to derive from an algorithm of
a cube that expanded as it rotated. The numerous triangles and
trapezoids formed by this system of intersecting lines were clad to
be either transparent or translucent, giving a sense of infinitely
repeated motion.
OPENING
S
CLADDIN
G

13. GENERATION BY
ALGORITHM
 The idea was that of a flat roof composed exclusively of random
cross lines and supported only by the line of the exterior walls, in all
forming an absolute box.

14. EXPLANATION
The algorithm used in the building involves the rotation and scaling
of squares in a central axis. Each square is smaller and embedded
in the previous one but rotated. By extending the lines of the
squares, a dense field of lines is created with numerous trapezoids
and triangles. Then, these are folded over one box. The lines are
materialised by choosing the size of the steel and the algorithm
defines the specific areas to be panelised.
Thereafter, the pattern is adapted for larger openings like entrance.

16. THE NATIONAL SWIMMING CENTRE , CHINACASE STUDY 2:

17. INTRODUCTION
 The National Swimming Centre, known as
Water Cube, is the product of a competition
entry by PTW Architects, China State
Construction and Engineering Corporation
(CSCEC), from Beijing, and ARUP .
 Generative Design was integrated in the
design process as well as the various
benefits it provided, both in terms of time
and cost compared to a traditional approach
to modeling
 The first challenge of the project was to
decide the form of the structure and the look
of the cladding the “Weaire-Phelan foam”,
that derives from the structure of water
bubbles in the state of aggregation found in
foam. the “Weaire-Phelan foam”, that derives
from the structure of water bubbles in the
WEAIRE-PHELAN
FOAM:

18. DESIGN PROCESS
FORM
PRISM SHAPE WAS
ACHIEVED WITH
RANDOM
APPEARENCE
REPETION OF FORM
CREATED A BASIC
SHAPE OF BOX WITH
SAME EXTERNAL
SIZE OF THE
STADIUM
SLICED BY 2
HORIZONTAL
PLANES AND ONE 4
VERTICAL PLANE TO
OBTAIN THE FORM
THE MAJOR
INTERNAL VOLUMES
WERE REMOVED
MODEL CONVERTED
TO WIRE FRAME
GEOMETRY OF
STRUCTURED
DEFINED

19. SCHEMATIC ILLUSTRATION OF THE GEOMETRY FORMATION

20.  This structure contains more than
22000 steel beams and 12000 nodes
which weigh tons which would then
present a challenge for its optimization
 Analyzing the structure and make the
necessary changes, as many times as
needed, would be an extremely
accurate process as well as very time
consuming. To overcome these issues,
ARUP developed a script to
automatically select the member sizes
through an optimization process. The
optimization code was written using a
genetic algorithm and the alternative
solutions were evaluated in Strand7
Software.
THE STRUCTURE OF THE WATER CUBE
UNDER CONSTRUCTION

21.  The algorithm iteratively
checked the entire structure
by allowing the team to test
different design configurations
and receive feedback within
25 minutes.
 Thus, it allowed the creation
of a complex structure that
could be structurally
optimized and which,
compared with traditional
approaches to modeling.

22. CONCLUSION
Generative Design is an example of a well-established research
area that can provide new ways of thinking generative design is a
better option for future prospects because it enables us to think
more creatively while autocad restricts our thoughts to some
extend. All designs are prone to change because designers do not
just build their first idea. GD supports change but it also requires an
initial investment. Thus, it is important to balance this investment
with the benefits we extract from it.
SHEENA CHERIAN

23.  Generative design though still in its infancy , is fast being adopted
by designers and architects due to its potential of creating designs
with the fast upcoming technology. It possess the power of
generative design tool that can guide down on an exploring path.
 Even if it has a lack of clear theoretical framework in the generative
design ,it provides a chance for new ideas and possibilities to
explore.
Nishita

24. Generative design is the creation of complex structures through the
use of simple algorithms. It focuses more on ideas and visual
thoughts rather than keeping engineering in mind.
Although provides a great range for exploration and design evolution,
it lacks the understanding of clear theoretical framework. Also, the
evolution of design solely through algorithms can be challenging
too.
Generative design in short is far ahead of its time.
Riya

25.  As we have discusse above that generative design is a method in
which the output- image , sound,architectural models, animations is
generated by a set of rules but still it is very difficult to ubderstand
and we are unable to judge the framework
 As we all know everything has both positive and negative side so its
positive side is that we can built complex forms through this
software.
Palak