Algorithmic Thinking for Problem Solving

ALGORITHMIC
T H I N K I N G
A PA R A M E T R I C A P P R O A C H T O
P R O B L E M S O LV I N G
STUDIO TUTORS | KUBER PATEL | AHMED ABBAS MOMIN
STUDIO ASSISTANT | MIHIR VASANI
COURSE PEDAGOGY AND STUDENTS WORK

Centre for Environmental Planning and Technology.
Copyright © 2020 by Cept
All rights reserved. No part of this publication may be reproduced,
distributed, or transmitted in any form or by any means, including
photocopying, recording, or other electronic or mechanical methods,
without the prior written permission of the publisher, except in the
case of brief quotations embodied in critical reviews and certain
other noncommercial uses permitted by copyright law.
Faculty of Architecture.
Studio Tutors : Kuber Patel & Ahmed Abbas Momin.
Declaration :
“We certify that this piece of work is entirely of cept students and that
any quotation or Image from the published or unpublished work of
others is duly acknowledged.”
Signature of Tutors:
Kuber Patel Ahmed Abbas Momin

Acknowledgment
It gives us an immense pride to have an opportunity
in compiling this book from our research studio title
“Algorithmic Thinking: a parametric approach towards
problem solving” at Faculty of Architecture, CEPT
University, Ahmedabad. We would like to express our
special thanks of gratitude to professor and dean Surya
Kakani who endorsed this studio along with the useful
suggestions and constructive criticisms during the entire
tenure of this work.
CEPT university believes in expanding its horizon to every
possible design processes being used in our community.
This exposure helps students immensely in being versatile
and being able to choose in which area they prefer
specializing and potentially use in their practice. We thank
the entire CEPT administration for bringing about change
in the education and have the audacity to innovative ways
of spreading knowledge.
We would also like to thank Jwalant Mahdevwala, Kirit
Patel, Sonal Mittal for their constant involvement in the
studio as guest lecturers and juror in motivating students
on how to move forward with their respective projects from
a fresh perspective.
We would also like to thank TLC whose support and
encouragement made this work possible within the limited
time frame. Lastly, we cannot forget all the students whose
hard work and constant engagement made this work in
good flow.

Foreword
The creative endeavor has largely been a fuzzy logic of
its practitioners and algorithmic thinking considered the
preserve of computer science and mathematics has been
making large inroads into the creative process.
Every creative process involves systematic, critical,
creative and holistic thinking, while the typical practitioner
would process this in a non linear mode, Algorithmic
thinking breaks each of these components down through
an iterative and recursive logic allowing reconfiguring of
the collated data in exploring possibilities.
As demands on the design practice begin to get more
rigorous right from conception, to execution and to
experience algorithmic thinking may offer a possibility of
coming to terms with the complex overload of information
that a present day design problem needs to process.
From mapping sites with GIS, to structure and material
science, from a form aesthetic derived purely out of energy
efficiency to using post occupancy studies in enhancing
user experiences all of these together and more may be
de-rigueur in time to come for an architectural production.
In Abbas and Kuber we have two motivated practitioners
and tutors who have chosen to commit their time and
energy in exploring and sharing the potentials of this
method in the production of architecture.
The promise is expectant and the challenges equally
daunting but it is through this continuous process of
academic engagement and encouragement that this
nascent field of c t will see advances, and it is heartening
to note that CEPT anchors this role.
Surya Kakani
professor and dean
faculty of architecture
CEPT university

Preface
Why Algorithmic Thinking is necessary in design ?
The present transformation from CAD to Computational
design methodology is a major turn in design process and
thinking. Computer Aided Tools used for representation
has been replaced by performance analysis tools, and
determining solution is guided by computational processes
of optimization. Using conventional tools and work flows
are no longer sufficient to keep up. Designer should now
rise to the challenge of re-configuring themselves to align
with the system, flow and exchanges that shape a new
area of design and production. Computational design is
an approach to problem-solving that uses algorithms to
synthesize information, imagination, and intent. This book
showcases the work of students attempt to streamline
creativity into an iterative framework addressing different
design solutions in a time-boxed data driven environment.
Work reflects their experience to develop design by
experimenting, analyzing and evaluating results that could
re-integrate into the design process making the final
proposal more intuitive and optimal as per the given set
of aspects they wish to explore. The book puts forward
advancements in fundamental work of establishing novel
design processes theoretically and practically.

Figure I Reference:https://robertbalke.de/wp-content/uploads/2019/02/IMG-2714
Figure I

Many environments are complex because of non linear
and conflicting relations that are interrelated in non linear
ways. It becomes important in design to perceive the
relations for shaping the environment of desired output.
Hence, dealing with such complexities a human mind
should consider large numbers of relations simultaneous.
However, a human mind can consider only limited amount
of information simultaneously (Miller). Therefore, making
sure that a solution found using conventional methods fits
its objective, is very challenging. To handle such complex
design task a proper computation method permits to
accomplish two major subtask.
First, an abstractions of the relations among design
elements using mathematics to generate the model.
Particularly in the field of design it is noted that some
concepts are imprecise as they are subjective and stems
from cognition. Example privacy, openness, functionality,
elegance, claustrophobic and so on. Abstraction of such
soft objectives requires advance computational means.
Second, deriving solutions of those having desirable
relations which full fills the objective of design criteria.
Achieving the desired solutions challenges are large amount
of possible solutions due to combinatorial explosion of
parameters and conflicting objectives.
E.g. Privacy and openness. This also requires computational
intelligence methodologies, in particularly evolutionary
computations.
Introduction

Figure II Reference : https://i0.wp.com/www.interactivearchitecture.org/wp-content/
uploads/2016/02/Picture4.jpg?resize=700%2C325
Figure II

Ahmed Momin
Ahmed Abbas Momin believes in performance-oriented
design, backed by a design approach that takes aspects
like climate, structure and other intangible criteria of design
into consideration. Apart from his professional practice,
Ahmed Abbas also works as a visiting faculty at CEPT
University, teaching Generative Design Studio.
Mihir Vasani (Teaching Assistant)
Mihir Vasani did his undergraduate from K.R.V.I.A (Mumbai)
and completed his masters in Emergence Technologies
and design from AA (2018). His interest is in exploring the
scope of computational design as an approach to regional
architecture. He believes that it can provide opportunities
to establish a new paradigm that is strongly rooted in the
context and solve problems efficiently.
Kuber Patel
Graduating from architectural association school of
architecture in emergent technologies and design, Ar.
Kuber Patel now focuses on data-driven design methods
where humanity can benefit from scientifically designed
built environment. He strongly believes that architecture
should be for serving a sustainable relationship between
mankind and the natural environment.
Tutor Profile

Work Image
Figure III State of the Art Exhibition’ by Kuber Patel and andblack studio, ready- to-assemble
architecture, for Abhay Mangaldas under Darwin light
Figure IV ‘Mosque at Sevalni’ by Ahmed Abbas Momin
Figure III
Figure IV
Figure V
Figure V ‘Office Interior ’ by Mihir Vasani,The Undulation in ceiling is parametrically derived
using pattern based on wood grains.

The studio explored ways of quantifying qualitative data
to be used in the design process. This ensured that every
design decision taken depending on external data is apt
and verified which otherwise stays superficial. The definitive
framework within which this data-driven process works
could give a great amount of control over the minute details
of the project. Since the details are governed by well-defined
parameters, constraints and rules, it is more efficient to
control and articulate at any stage of the design. This design
process gives the flexibility and techniques to drive a project
extensively with multiple key factors as well as with a single
core factor. Once understood, the analytical tools used to
evaluate the design (wallacie) opened up a wider perspective
to study and analyses the design. After completing the Studio,
the student will be able to: To use a digital platform as a tool
that helps inform our design process rather than a medium
for digital representation. How to translate data into possible
design variables that can quantify system optimization based
on its performance or behavior. Streamline your design
workflow into a simple set of rules that define your desired
outcome for tackling a solution. Understand the abstraction
of appropriate parameters and its relationship with the
criteria to iterate a design variable into a set of experiments
that can be used for the final proposal. Approach the final
design proposal combining all experiments done in isolation
for different design variables and make a coherent system
that adds a feedback loop between each system making the
entire design solution highly intuitive.
Learning outcome

Figure VI Iteration showing the iterative Morphologies. (Sampreet Dasgupta - 4thYear B.Arch)

Exercise 1: Bootcamp
1.1 Introduction to design solutions using parametric logic . . . . . . . . . . . . . . . . . . . . . . . 18
1.2 Digital morphogenesis(b)(c)
of spatial configuration and character. . . . . . . . . . . . . . . . 20
1.2.1 Summarizing work-flow using stepwise procedure into set of rules. 22
1.2.2 Creating multiple outcomes defined by a system specific sequence. 24
1.3 Decoding Piet Mondrian painting on impulsive impression. . . . . . . . . . . . . . . . . . . . . 26
1.3.1 Story telling through the overlay between quantitative and qualitative analogy. 28
1.3.2 Summarizing work-flow using stepwise procedure into set of rules. 30
1.3.3 Creating multiple outcomes defined by a system specific sequence. 38
1.4 Students work, monsoon 3rd
semester 2019, Master of Architecture . . . . . . . . . . . . . . 40
1.4.1 Shell geometry derivative by cross referencing points. 40
1.5 Students work, spring 5th
semester 2020, Bachelor of Architecture . . . . . . . . . . . . . . 44
1.5.1 Decoding Piet Mondrian Painting through a set of rules. 44
Exercise 2: Identification of Design Variables
2.1 Abstraction of relations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
2.2 Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
2.2.1 Extension to Bhau Daji Lad Museum 52
2.2.2 Program Evolution of housing Typology 54
2.3 Built environment - character of space through building element . . . . . . . . . . . 56
Exercise 3: Design Drivers
3.1 Translating qualitative into quantitative aspects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.2 Introduction to analytical tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
3.2.1 Axial Analysis 76
3.2.2 Centrality Analysis 78
3.2.3 Isovist 80
3.2.4 Sunlight Hours Analysis 82
3.2.5 Daylight analysis 84
3.2.6 Wind analysis 86
3.3 Social relationship - Defining criteria for quantification . . . . . . . . . . . . . . . . . . 88
3.4 Problem Statement - analyze and evaluate various spaces using criterias. . . . . . 92
Table of Contents

3.5 Hypothesis- Parameter Study and form finding . . . . . . . . . . . . . . . . . . . . . . 96
Exercise 4: Design limitation
4.1 building scalability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.2 Synthesis using previous study and calculating the given bylaws . . . . . . . . . . . . 102
Exercise 5: Evolution of build form
5.1 Deterministic to probabilistic system designers . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
5.2 Introduction to evolutionary computation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
5.3 Mandate setup into Emergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
5.4 System Logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
5.5 Pseudocode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
5.6 Analyzing all criteria through multi objective optimization . . . . . . . . . . . . . . . . . . 116
5.7 Iteration evaluated using graph theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
Exercise 6: Design Proposal
Students work
•Spring 5th semester 2020, Bachelor of Architecture. . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
•Monsoon 3rd
semester 2019, Master of Architecture. . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
Bibliography 152

In order to acclimatise students with this new methodology
this two week exercise focuses on a brief understanding of
the new terminologies and digital process used in design.
Inception of work starts with comprehensive introduction
to the core skills and techniques of algorithmic thinking
centered on associative geometric models.
Induction pushes you to assimilate the potential of
algorithmic techniques into design irrelevant of its scale and
application. Every semester is given an objective to develop
design solution through parametric(a)
control,tessellation
of three-dimensional components, precise dimensional
control, constraints(b)
and spatial organization.
Exercise 1 will be supplemented by seminars and tutorials
on using systems that resolve problems using parametric
logic with the use of visual programming tools like
grasshopper. Along with examples of live projects that
used similar design thinking.
Students will become familiar with the necessary exchange
of data between physical and digital realms through the
formalization of the inherent geometric relationships that
characterize the different elements of developed designs.
The exercise will also be supplemented on appropriate
techniques of recording, describing and documenting
digital and physical experiments.
1.1 Introduction to design solutions using parametric(a)
logic
Aim
Exercise 1: Bootcamp
Parameter(a)
is a term used to describe a dimension’s ability to change
the shape of model geometry as soon as the dimension value is modified.
For example various design elements like the length or width manipulation
with in a range of window.
Constrains(b)
enables holistic control over the design logic by establishing
relationship with its morphology. For example the length and width can
be manipulated for a window without increase in total area.

Figure 1-1 Exhibition image showing physical model of
geometrical explorations done by students of 2nd year M. Arch
Fig 1-1

Monsoon Semester 2019
2nd year M.Arch
Determine relationships that affect change in morphology
of a NURBS(e)
surface preferably an enclosure using
parameters. Also, add constraints to the design approach
to maintain certain desired spatial character. The study is
divided into 4 parts - system logic, pseudo code, iterations
and further development / conclusion.
System logic is the simple breaking down of the process of
geometrical exploration with clear overview of design intent
and approach. Students are encouraged to experiment
on simple mathematical principles and gradually evolve
the form through use of rules and strategic relationships
having parametric control.
The four part method helps student use data in a streamline
iterative process for drawing conclusions based on the
understanding of its dependency and relationship of
various rules, constraints and parameters applied.
Use of computational tools become inherently embedded
into the design process as a means of form-finding and
optimization of spatial performance brings upon a new
paradigm of digital morphogenesis.
Objective
NURBS(e)
Non-uniform rational basis spline are mathematical models of
3-Dimensional geometry that accurately describe any shape from simple
2-Dimensional curve to a most complex 3-Dimensional organic free-form
surface or solids.
Morphogenesis(c)
is the biological process that causes an organism to
develop its shape, growth and differentiation.
Digital morphogenesis(d)
is a type of generative art in which complex
shape development or morphogenesis is enabled by computation.
1.1 Digital morphogenesis(c)(d)
of spatial configuration and
character.

Figure 1-2 Final output of Geometrical explorations
done by student of 2nd year M.Arch
Fig 1-2

2nd year M.Arch
1.1.1 Summarizing work-flow using stepwise procedure into set of rules.
STEP 01 :
DEFORMATION INTENSITY.
Rule: Define reference object
with set radius and number of
segments.
Parameter: Number of vertical
section
STEP 02 :
DEFINING CROSS SECTION
INTERVALS.
Rule: Increments of Fibonacci
sequence between sections.
Constrain: Spacing between
section.
Parameter: Number of horizontal
section.
STEP 03 :
IDENTIFYING THE DEFORMA-
TION POINTS.
Rule: Alternate point selection on
each section with inverted rela-
tionship to its neighbors.
Constrain: Identifying the
deformation points based on the
ascending spiral selection.
STEP 04 :
DIRECTIONAL MOVEMENT OF
THE IDENTIFIED POINTS.
Rule: Perpendicular movement of
deformation points to its section
with an invert relationship.
Parameter: Depth of vertical
section.
STEP 06 :
DEFINING CURVE THROUGH
DEFORMED POINTS.
Rule: Draw vertical cross section
by interpolating points between
each horizontal section grafted by
number of vertical sections.
STEP 07 :
SURFACE FORMATION.
Rule: Creating network surface
through achieved curves with edge
conditions on both sides same as
the reference object.
STEP 08 :
DEFINING HEXAGONAL CELLS.
Parameter: Defining no. of
Hexagonal divisions.
STEP 09 :
DEFINING HEXAGONAL CELL
OPENINGS.
Constrain: Opening of the cells
on surface becomes smaller as the
deformation points moving away
from the axis.
Pseudocode(f)
summarizes a program flow, but excludes
underlining details. In figure 1-3 the student is trying to
break down his design process using illustrations and
carefully recording the steps required to develop a tubular
surface with relative fenestrations. This process is then
translated into a script through tools like grasshopper to
generate complex form.
Pseudocode(f)
is a non programming language used to outline a rough
draft of script syntax in simple words by establishing procedure of various
rules, parameters and constraints. It summarizes a program flow, but
excludes underlining details.

Step 1 Step 2 Step 3 Step 4
Step 5 Step 6 Step 7 Step 8
Figure 1-3 Pseudocode- Deformation on tubular surface
with relative fenestrations.(Sai kiran - M. Arch 2nd year)

2nd year M.Arch
1.1.2 Creating multiple outcomes defined by a system specific sequence.
Plethora of Iterations(g)
are generated through manipulation
of parameters. Students give conclusion by observing
change in the behavior of morphology. Also, identifying
dominant and appropriate parameters based on design
intent. In figure 1-4 the student achieves shell geometry
while underlining that the use of sine curve intensity and
intervals helps achieves maximum parametric control over
desired geometry.
Iterations(g)
is the repetition of a process in order to generate a sequence
of outcomes based on the design approach set by specific rules governing
a geometry by parameter and constrain.
ITERATION 01 :
Changing the direction of the
curve.
For all sin curves
Frequency of the Sin curve : 1
Amplitude : +1
ITERATION 02 :
Varying depths of the third
curve.
For 3rd sin curve
Amplitude : +1
ITERATION 03 :
Varying the heights of the
curves and number of
sin curves.
ITERATION 04 :
Increasing the number of sin
curves and
depth of the sin curve.
For 3 rd sin curves
Amplitude : +3
ITERATION 05 :
Decreasing the height of the
curves and increasing
the depth of the curve.
For 1st sin curves
Amplitude : +1
ITERATION 06 :
Decreasing the depth and
increasing the depth of
sin curves.
For 2nd sin curves
Amplitude : +1.5
ITERATION 07 :
Decreasing the depth curve
with one sin curve
count and increasing the depth
of curve.
For 2nd sin curves
Amplitude : +0.5
ITERATION 08 :
Decreasing the depth sin curve
and increasing
the depth of curve.
For 2nd and 4th sin curves
Amplitude : +2

BOOTCAMP: Exploring geometrical configuration through a set of rules.
of rules.
Figure 1-4 Iterations- Exploration of surface through sine
curves.(Tejaswini Walunj - M.Arch 2nd year)

Spring Semester 2020
Final year B.Arch
1.2 Decoding Piet Mondrian painting on impulsive
impression.
Objective
Piet Mondrian was a Dutch painter recognized as one
of the greatest artist of twentieth century pioneering in
abstract art. He believed that in order to achieve spiritual
in art it should be above reality. As a result, his paintings
progressed towards non-representational form. To express
this he limited his vocabulary to primary color, values and
direction.
The students are encouraged to make a compelling
narrative from one of his painting in figure 1-5 and
translate that logic into data. The objective lies in the use
of qualitative aspects of art into quantitative aspects and
making rational conclusion.
The final result should be n-number of outcomes with
dramatic changes in the painting as compared to the original
while maintaining the new population to be offspring of
the same family. Parameters are used to inform change
in the composition based on their narrative and constrain
identifies the key essence that sustains the authenticity of
the painting.
Examples of key essence include features like quantity
of color, dominant proportions, number of subdivision or
location of primary colors and values. Student narrative
coupled with initial intent of the painting influences a fresh
canvas where data creates emergent art through logical
thinking.

NARRATIVE
BOOTCAMP: Decoding Piet Mondrian Painting through a set of rule
There is a Dominance of the
red color.
This creates Stability.
The presence of Squarish
Painting 1 Painting 2
Areas covered by colored rectangles with respect to the total area of the painting
Selected Paintings by Piet Mondrian
Geometric shapes and their meanings Conclusion
Painting 3
Areas covered by diﬀerent colored rectangles are almost of
equal proportions in Painting 2 and Painting 3.
This creates Instability and Chaos.
NARRATIVE
BOOTCAMP: Decoding Piet Mondrian Painting through a set of rules.
red color.
Painting 1 Painting 2
Selected Paintings by Piet Mondrian
Painting 3
The
Dom
R
S
The ﬁ
due to
exten
story
The o
them
The s
The P
Figure 1-5 Piet mondrians painting
a) Piet Mondrian Painting 1
Source link -https://www.piet-mondrian.org/tableau-i.jsp
b) Piet Mondrian Painting 2
Source link- https://www.artsy.net/artist/piet-mondrian
c) Piet Mondrian Painting 3
Source link- https://www.artsy.net/artist/piet-mondrian
a b c

Final year B.Arch
The Painting here is looked as a Precinct with a Control
line dividing the precinct into two opposite stories.
The first story is a stable and simple expression due to
presence of a dominant and only one line extending through
the dominant. Thus, we call it the story of Simplicity.
The second story is a mayhem of elements. It has two
colors having equal areas. There are lines that are not
relating to anything. Thus, we call it the story of Chaos.
The only line, part of both the stories, connecting them
is the Story connector. The story connector together with
the control line makes 4 rooms giving individual spaces
for each color to move. Room of red & black in story of
simplicity and room of blue & yellow in story of chaos. The
only subdivision which is a part of both the stories is the
common or neutral subdivision. It is small yet an important
part of the story.
Some fixed aspects (CONSTRAINTS)
(1) The control line
(2) The location of the colors
(3) Area covered by the colors
(4) Position of the common subdivision
Some variable aspects (PARAMETERS)
(1) The story connector
(2) Proportions of all the rectangles
(3) Number of divisions in the story of chaos
(4) Area of black divisions
1.2.1 Story telling through the overlay between quantitative and qualitative analogy.
Narrative

rules.
ish
inant
stable
ion to
ing
The story of Simplicity
Control Line Control Line
Dominant Red
Room of Black Room of Yellow
Area-Red
(30% of area-
precinct)
8A sq. units
Area-Blue
A sq. units
Area-Yellow
A sq. units
Room
of Blue
Common
Subdivision
Story Connector
Room of Red
Blue Twin
Yellow Twin
The story of Chaos
f
The first story is a stable and simple expression
due to presence of a dominant and only one line
extending through the dominant. Thus, we call it the
story of Simplicity.
The only line, part of both the stories, connecting
them is the Story connector.
The story connector together with the control line
makes 4 rooms giving individual spaces for each
color to move. Room of red & black in story of
simplicity and room of blue & yellow in story of
chaos.
Some fixed aspects (CONSTRAINTS)
(3) Area covered by the colors
(4) Position of the common subdivision
Some variable aspects (PARAMETERS)
The Painting here is looked as a Precinct with a Control line dividing the precinct into two opposite stories.
The second story is a mayhem of elements. It has
two colors having equal areas. There are lines that
are not relating to anything. Thus, we call it the story
of Chaos.
f rules.
ish
ing
The story of Simplicity
Control Line Control Line
Dominant Red
Room of Black Room of Yellow
Area-Red
(30% of area-
precinct)
8A sq. units
Area-Blue
A sq. units
Area-Yellow
A sq. units
Room
of Blue
Common
Subdivision
Story Connector
Room of Red
Blue Twin
Yellow Twin
The story of Chaos
f
The first story is a stable and simple expression
due to presence of a dominant and only one line
extending through the dominant. Thus, we call it the
story of Simplicity.
The only line, part of both the stories, connecting
them is the Story connector.
The story connector together with the control line
Some fixed aspects (CONSTRAINTS)
The Painting here is looked as a Precinct with a Control line dividing the precinct into two opposite stories.
The second story is a mayhem of elements. It has
two colors having equal areas. There are lines that
are not relating to anything. Thus, we call it the story
of Chaos.
red color.
geometry and a Dominant
in painting 1 makes it a stable
expression in comparion to
the other two paintings.
Painting 1
Transit (to move)
Stability (to pause)
Painting 2
Painting 3
T
d
e
s
T
t
T
m
c
s
c
T
s
s
T
Figure 1-6 Narrative (Astha Shah final year B.Arch)
a) Area covered by the painting
b) Painting is here looked as precedent with control line dividing it into two opposite stories..
c) Subdivision of the painting
a
b
c

Final year B.Arch
1.2.2 Summarizing work-flow using stepwise procedure into set of rules.
In figure 1-7 the pseudocode(f)
rightly demonstrates the
importance of setting clear design intent for deciding the
hierarchy of steps required to flow through data that may
help achieve a desired outcome. This decision making
process here becomes of paramount importance as the
previous step influence the next step.
Here the student defines constrains of vertical division,
quantity of red & location while uses the horizontal
division, proportions of red, These initial steps established
through parameter, constrain and rules would have a
direct relationship on the behavior of remaining steps in
the pseudocode(d)
.
Setting up domains for your parameter places such a
system at the forefront of probabilistic design where the
result adhere to the designers initial intent supported a
strong logic.
Pseudocode(f)

Figure 1-7 Pseudocode illustrations(Astha Shah final year B.Arch)

Final year B.Arch
STEP 01:
DEFINE A PRECINCT
Defining a rectangle with original proportions i.e. 3:2.
Calculate area of the rectangle. Calculate area of red rectangle
i.e. 30% of total area.
Constraint : The proportion of the precinct.
STEP 02:
DEFINE THE CONTROL LINE TO CREATE TWO STORIES
Divide the rectangle as per the original proportions i.e. 7:5, by a vertical
line into two stories:
The story of Simplicity & The story of Chaos
Constraint: The position of the control line.
STEP 03:
DEFINE THE STORY CONNECTOR
Add a horizontal line that connects both the stories together and
creates the room of red, black and yellow.
Parameter: Position of story connector varies
In Y-axis from 10% to 40% length of the shorter
Axis of the sector.
STEP 04:
DEFINE THE DOMINANT RED
Create the red rectangle of the fixed area (calculated in step 02) by
adding a vertical line in the room of red.
Change this line with respect to the story connector keeping area of
red constant.
Parameter: Position of the line varies in X-axis.
Constraint: Area of the dominant red.
STEP 05:
Pseudocode

STEP 01 STEP 02
STEP 03 STEP 04

Final year B.Arch
DEFINE THE FIRST BLACK COUSIN
Create the black rectangle by adding a vertical line in the room of
black.
Parameter: Position of line varies in X-axis
Maximum area: 15% of area of red.
STEP 06:
CREATE THE ROOM OF YELLOW & BLUE
Calculate the area of room of yellow rectangle.
Create a vertical line that divides the larger void of the chaotic story
into two non-equal parts.
Parameter: The area of room of blue is always greater than area of
room of yellow.
STEP 07:
DEFINE THE BLUE TWIN
Create the blue rectangle of the fixed area by adding a horizontal line
in the room of blue.
Parameter: Position of the line varies in Y-axis.
Constraint: Area of the blue twin.
STEP 08:
DIVIDE THE ROOM OF YELLOW
Create a subdivision in the room of yellow by adding a horizontal line.
The areas of yellow rectangle and blue rectangles are equal. Thus,
they are called twins.

STEP 05 STEP 06
STEP 07 STEP 08

Final year B.Arch
STEP 09:
DEFINE THE YELLOW TWIN
Create the yellow twin of fixed area by adding a vertical line. The
rectangle formed as a by-product is the second black cousin.
Parameter: Position of the line varies in X -axis.
Constraint: Area of the yellow twin equal to
Area of blue twin.
STEP 10:
DEFINE THE COMMON SUBDIVISION (IF TRUE)
Create a subdivision which is a part of both the stories by adding a
horizontal line.
Position of line at original proportions.
Constraint: Position of horizontal line
Creating the common subdivision, if present.
STEP 11:
TRIM THE CONTROL LINE (IF TRUE)
Trim the control line from the common subdivision. Thus, making
the common subdivision as one element present in both the stories
simultaneously.
STEP 12:
INTENSIFYING THE CHAOS (IF TRUE)
Add horizontal and vertical lines in the story of chaos to intensify.
Make subdivisions by adding terminating lines in the voids.
Rule: Paint one rectangle black with addition of every four lines.
Rule: number of horizontal lines added = number of vertical lines
added.

STEP 09 STEP 10
STEP 11 STEP 12

Final year B.Arch
Iterations of the painting were created by changing the
identified parameters. Constraints are defined to retain
the characteristic of the painting. The following iterations
creates family of painting by changing the position of
primary and secondary lines.
ITERATION 01 :
l1: 6 unit
area of colour : 20sq.units
Perc. of coloured area : 25%
ITERATION 02 :
l1: 6 unit
ITERATION 03 :
l1: 6 unit
1.2.3 Creating multiple outcomes defined by a system specific sequence.
Parameters
Distant of primary line (l1)
Area of colour
Percentage of colour
Constraints
Location of colours
No. of Subdivisions
ITERATION 04 :
l1: 6 unit
area of colour : 16 sq.units
ITERATION 05 :
l1: 6 unit
ITERATION 06 :
l1: 6 unit
Perc. of coloured area : 21 %

Figure 1-8 Iterations (Sampreet Dasgupta 4th year B.Arch)
ITERATION 01 ITERATION 04

Illustration that follow in this section are work samples of
various outputs by the students in boot-camp with the aim
and structure mentioned in section 1.1. For the monsoon
semester 2019 our objective for the exercise is stated in
section 1.2 intended for master students who has higher
level skills.
In figure 1-9 the student is looking at developing a shell
like structure by crossing referencing points on the base
circle interpolated with point in the z-axis forming a doubly
curved surface. A neat example of data driven design
where simple rules can potentially create complex forms.
Parameters such as distance between points, number
of points with constrains such maximum height, number
of point to be interpolated etc with relational rules helps
explore various geometric configuration. As the project
develops further, the surface evolves into fluting surface
achieved by adding parameters the manipulate depth
from the base curve radially and width of the fluting curve.
1.3.1 Shell geometry derivative by cross referencing points.
1.3 Students work, monsoon 3rd
semester 2019, Master of
Architecture

LVING
e point set into two equals
d Set B)
(Parameter 1)
(Constraint 2)
(Parameter 2)
06
aint 4)
of Set A, Set C and Set
ect in sequence to form
c
Figure 1-9 Shell structure genetated by cross referencing points (B Athira 2nd year M.Arch)

2nd year M.Arch
Step 1 :
Divide base circle into a set of even number of
points - Base set
Step 2
Define sequence 1 - Alternate points of each set to
offset radially
Split base point set into two equals
(Set A and Set B)
(Parameter 1)
(Constraint 2)
(Parameter 2)
02
riable radius
et 2x count
Split base point set into two equals
(Set A and Set B)
(Parameter 1)
(Constraint 2)
(Parameter 2)
03
Iterations
Pseudocode
Iteration 1
Parameter 1 - Points of one set to move together
in a direction with variable distance
Iteration 2
Parameter 1 - Points of setB to move
together in a direction with variable distance)

Iteration 3
Parameter 2 - Offset radius of sequence 2
Step 3
Define set C with same number of points as set A
and set B
Step 4
Defining Sequence 2 - 3 point
arc(Constraint 4) and Form shell geometry
ALGORITHMIC THINKING : A PARAMETRIC APPROACH TO PROBLEM SOLVING
Set C with series of points at cen-
ter of base circle
(Parameter 3)
04
(Constraint 4)
Nth point of Set A, Set C and Set
B to connect in sequence to form
3 point arc
Iteration 4
Parameter 2 - Offset radius of sequence 2
PARAMETRIC APPROACH TO PROBLEM SOLVING
oints at cen-
(Parameter 1)
(Parameter 2)
06
(Constraint 4)
Nth point of Set A, Set C and Set
B to connect in sequence to form
3 point arc

Here the Painting is depicted as scenery by the student
and observe a horizon line that divides the whole rectangle
into two parts. Part above the horizon as Sky and the part
below the horizon as Earth. All the other terminating line
further dividing the sky and earth into different parts that
form up the rest of the scenery including sun, clouds,
water, human settlement, ground, birds, etc.
Sky: The sky consists of yellow, black and white color
indicating sun,birds and clouds respectively.
Earth: Blue part in the painting indicates water, red part
indicates the human settlement and the rest of the part
indicate roads/ground/empty patches of land covered in
the painting.
The artist has captured a certain area / amount of water,
sun, human settlement, etc in his painting, but knowing the
fact that scenery can be extended with a change of vision,
he tried to remove the frame. He, in his painting, has given
the hint of INFINITY by removing certain boundaries from
the painting.
Narrative
1.4 Students work, spring 5th semester 2020, Bachelor of
Architecture
1.4.1 Decoding Piet Mondrian Painting through a set of rules.

Piet Mondrian - Tableau I
undaries from the painting.
Sun
Clouds
Clouds
Land Land Land
Human
settlement
Water
Birds
Horizon
a)Piet Mondrian - Tableau I
Source link -https://www.piet-mondrian.org/tableau-i.jsp
b)Each rectangle have different areas and are indication of
interpretation in reference to the original painting.
a
b
Figure 1-10 Narrative (Gelani Khushali 5th year B.Arch)

Final year B.Arch
STEP 1 -Draw reference grid
Here, O is the origin point.
Total Length of the rectangle is 16.5A.
Total Width of the rectangle is 11A.
(where A is the unit of measurement as
shown.)
STEP 2 -The Horizon
From the origin take a point from :
Yaxis - 8A
Xaxis - 16.5A
Join the points and make a line from left
to right.
This is the Horizon line. Horizon line does
not move up or down. It stays fixed in its
position.
STEP 3 - Sub-divisions
Part above the horizon (sky) is divided
into 5 parts.
Part below the horizon (earth) is divided
into 6 parts.
The number of sub-divisions remain
constant in both above and below the
horizon. Th ere cannot be 2subdivision of
the same size.
STEP 4 - Shifting of the sub-divisions
Area of the sub-divisions are fixed. Sub-
divisions of sky cannot shift to earth and
vise-versa.
Sub-dividions of sky can be located
differently
STEP 5 - Colours
Area of coloured rectangles are fixed too
but the sizes can be different according
to the fixed areas.
Red color and blue colour should always
be below the horizon, in the earth.
Yellow and black should always be
above the horizon, in the sky.
STEP 6 Infinity
For every movement, one part of the
painting would be fixed as it is in order
to retain the original painting.
So,if changes of sizes are being done in
Earth, then all the divisions of Sky will
remain intact along with the horizon line
and vice-versa.
Psuedocode

A
A
A
A
A+A
A+A
A+A
A+A
A A
A+A/2
O
1
1
2
2
3
3
4
4
5
6
5
A+A/2 A+A/2
A A A A A
A A A A
d
ts.
h
o
Original shape
New shape
STEP 1
STEP 4
STEP 2 STEP 5
STEP 3 STEP 6
Figure 1-11 Psuedocode illustrations (Gelani Khushali 5th year B.Arch)

Final year B.Arch
Iterations
Iteration 1
constant : Sky elements
Variable : Earth elements(60%)
Iteration 2
Iteration 3
Iteration 4
constant : Earth elements
Iteration 5
Iteration 6

Figure 1-12 Iteration illustrations (Gelani Khushali 5th year B.Arch)
Iteration 1 Iteration 4
Iteration 2
Iteration 5
Iteration 3
Iteration 6

Design Variables(h)
are aspects that shape model properties to used
for design optimization. A parameter is use to adjust the model behavior
specific to a criteria while variable the model state. For example, length of
the window is a parameter to adjust while window is the variable of study.
Exercise 2: Identification of Design Variables(h)
2.1 Abstraction of relations
Establishing variables and their impact on design provides
important information in achieving the design objectives.
For example (fig 2-1) location and type of activities in the
museum is controlled by the proximity and importance of
surrounding functionality near the museum area and further
helps in determining the area and inner connectivities
between different activities. Variables play an important
role in rationalizing design decisions and allow generating
different outcomes when values are changed. It helps in
abstracting the different relationships and their properties
for defining the environment. In computational design
these variables are put in the form of parameters using
mathematics as a tool for modeling the space. Each
and every relations are hence decoded in the form of
parameters that are interrelated with each other and
gives different output. This complex nature of non linear
relationships can be understood by abstraction using
advanced computational means and algorithmic thinking.

<
3
0
0
m
r
a
d
i
u
s
EDUCATION
HOSPITALS
SOCIAL AMENITIES
HOTELS
RESTAURENT & BAR
RELIGIOUS SPACES
Proximity map is organised in 3 segments based on the radius.
1) Below 300m radius
2) 300m-600m radius
3) 600m and above.
Units: distance (meters)
Figure 2-1 Chart showing Proximity chart of spaces
within 1km radius (.(Sai kiran - 2nd year M.Arch)

2nd year M.Arch
Creating a new dynamic identity for itself as a cultural hub in
Mumbai by designing its north wing expansion. Museums
in India have traditionally been viewed as graveyards,
relics of history that are of little consequence in the daily
lives of the people. The Museum’s new expansion intents
to change this perception and ensure that the Museum
plays a constructive role in communicating across the
generations and society and engaging in long term
relationships with visitors. To do this we must offer a
meaningful and refreshing discovery of Mumbai’s history
and culture, as well as interrogate contemporary issues
and create a platform for cultural dialogue. All solutions
given through the design process will be quantified with
its context, culture and experience using morphological,
climatic and spatial aspects. (Mumbai city museum, north wing
design competition, 2013)
Mission Statement
To serve the community as an institution dedicated to
excellence in cultural education through exhibitions and
different visual and intellectual media
To engage the community, especially children
To promote a greater appreciation of Mumbai’s artistic,
cultural and economic history and development
To promote cross cultural understanding and cultural
awareness at all levels
2.2 Program
2.2.1 Extension to Bhau Daji Lad Museum
Objective
d

Figure 2-2 Bhau Daji Lad Museum images(Mumbai city museum north wing design competition, 2013)
a)Bird eye view
b) view of Central atrium
c) Ground floor gallery
d)First floor gallery
d
c
b
a

Final year B.Arch
The studio aims at understanding how the design of
dwellings can facilitate their adaptability in reference
to Site context and scale using computational design
methodology. The design process should seek to promote
flexibility in the design of housing and, wherever possible,
maximize opportunities for resident choice in relation to the
use of Spaces. The design should consider environmental
aspects such as shadow, solar radiation, daylight,
ventilation etc. Each student is given a well-known city
block from different regions of the world. The aim is to study
existing block typology and re-imagining it in consideration
with current scenarios. As part of computational design
methodology, design variable is defined and morphologies
are generated using parameters, rules and constraints.
Iterations are then evaluated using the given Criteria.
Breaking down the building into values that can add logic
to further justify the problem statements. For example,
the total percentage of building vs open, opening vs total
building area for N,E,W,S facing facades, Proportion of
LxB, LxH. This method should help make relationships if
certain sizes are too big or small with respect to its climate
and social needs. Hence, the approach to change them
would make sense moving forward into design. Further
students will explore the evolution of block form and
system adaptability by adding scale.
2.2.2 Program Evolution of housing Typology
Objective

Figure 2-3 Housing topologies given to students
a)Shibam - 16th century Yemen
b) Bruno Taut - Carl Legien Estate [1928] Berlin
c) Patrick Hodgkinson - Brunswick Centre [1972]
d) Microrayon - Soviet Union (Siberia) [20th Century]
e) Fes el Bali - Fes,Morocco
a b
c d
e f
g h
i j
f) Manhattan Commissioners’ Plan - 1811
g) Ildefons Cerda - Example [1859] Barcelona, Spain
h) Kowloon Walled City - Hak Nam - 1898 Hong Kong
i) Hutong courtyard houses - Beijing [15th century]
i) Le Corbusier - Ville Contemporaire [1922] Utopian Planning

2.3 Built environment - character of space through building
element
Creation of argument behind the designers intend and
current use of the given built environment with the current
social fabric. Every architectural element would have its
purpose for the space provided in relation to the social
environment. Identify key character of the space which
governs the major relations of the environment and
defining the strong narrative for developing the concept in
the form of hypothesis. Areas of concerns are highlighted
along with the intuitive ideas of design strategy, defining
variables and parameter range in order to maintain the
social acceptability in terms of scale, lighting quality,
exposure, visual connectivity etc.
Figure 2-4(a) shows importance of plaza size in reference
to the street size and accessibility from surrounding
dwellings. Student further defines the character of plaza
space with reference to its size, orientation, number of
occupancy ,time of engagement, seasonal use, specific
element like standing balconies over the plaza by
establishing relationship with the space.

Chosen cluster
Shared walls
Street
House openings towards
the internal streets.
Medium height
High height
Low height
Plaza
Figure 2-4 Identification of building elements and social activities(Khushboo Makwana - 5thYear B.Arch)
a) Image showing the open plaza
b) Characteristics of Plaza
c) Children playing in plaza
d) Gathering in plaza
e) Daily activity in plaza during evening
a
b
c d e

2nd year M.Arch
The example is from the student work of extension to Bhau
Daji Lad Museum, engaged in developing a strong character
around pedestrian of museum. Regulating the pedestrian
activity around the site to increase the museum’s inlet
and increase visual connectivity from outside to inside.
Following are design strategies for creating character of
space through openings.
1. Identify the ideal pause points as per visibility. (a)
2. Identify the desired intensity of pedestrians at each
of these pause points as it would affect the number of
openings at each pause point. (b)
3. Use this system to identify the ideal location for the
“planes of curiosity”(c)
Example
c
Student : Saadiya Rawoot
Built environment - character of space through building
element

Figure 2-5 Influence of museum on pedestrian activities (Saadiya Rawoot - 2nd year M.Arch)
a) Identifying various pathways around museum
b) Image shows Visual connectivity between museum and pathways
c) Identification of pause points on pathways
a
b

2nd year M.Arch
0
200
400
600
800
1000
1200
1400
1600
STRETCH 1
(2 m)
STRETCH 2
(4.5 m)
STRETCH 3
(1.2 m)
STRETCH 4
(2.5 m)
STRETCH 5
(0 m )
STRETCH 6
(1.8 m)
Intensity of people every 5 minutes
Intensity of people every 5 minutes
a
b
element

Figure 2-6 Detail study of pedestrian pathway (Saadiya Rawoot - 2nd year M.Arch)
a) Collage showing Activities on Pathways
b) Graph Showing intensity of people every 5 min.
c) Illustrations showing the identified stretches based on its width.
Stretch 1 : 2 m
Stretch 4 : 2.5 m Stretch 5 : 3.2 m Stretch 6 : 1.8 m
Stretch 2 : 4.5 m Stretch 3 : 1.2 m
c

Final year B.Arch
The Example is a district of Barcelona between the old city
and what were once surrounding small towns constructed
in the 19th and early 20th centuries. The Example is
characterized by long straight streets, a strict GRID
PATTERN crossed by wide avenues, and square blocks
with CHAMFERED CORNERS. This was a visionary,
pioneering design by Ildefons Cerdà, who considered
traffic and transport along with sunlight and ventilation in
coming up with his characteristic octagonal blocks
A group of 9 blocks have been considered as one
module. Modules from various parts of the city have been
considered for determining key variables and domain for
parameters.
TERMINOLOGY
MANZANA – Block
MANZANA DIVISION – Each manzana divided into 20 sub-divisions.
MANZANA PARTS – Each manzana has been divided into 4 parts
INTERIOR FACADE – Facades of the manzana facing the courtyard
SETBACK DISTANCE – The distance between the building boundary
and plot boundary
MANZANA DEPTH – The depth of the perimeter block
CHAMFER DEPTH – The distance of the chamfer from the street
INTERWAY– Passage in between block in a C, L or a parallel shape
Example Student : Sampreet Dasgupta
element

Interior Facade
Manzana Subdivision Setback Manzana Part Chamfer Depth
Figure 2-7 Identification of Architecture Variables (Sampreet Dasgupta - 4thYear B.Arch)

Final year B.Arch
MANZANA DEPTH & SETBACK DISTANCE
At the core of Cerda’s master plan was the creation of the
manzana a city block structure that had been meticulously
studied and detailed. Originally, each manzana was to be
built up on only 2 or 3 sides, with a depth of 20 m and a
height of 16 m. The length of each side would measure
113.3 m with a precise area of 12,370 sq.m. The set back
distance varied from 1 to 2 m depending on street width
The typical blocks initially with an open layout became
closed, and the courtyards were built up rather than
remaining as open space. Changing ordinances eventually
allowed for buildings to grow in height and depth,
considerably increasing the density of the plan. As a result,
the EXPOSURE of the courtyard reduced considerably.
MANZANA HEIGHT
Cerda’s initial plan proposed that buildings should have an
average height of 16m from the ground level. The maximum
height allowed would be 20m(approximately 4-5 stories).
However, during construction due to political and socio-
economic issues, buildings went up to 9 floors in height.
Due to modified/increased height of the manzana, the
sunlight reaching the floor surfaces and interior courtyards
is very low. The FAR also changed drastically, in order to
accommodate the increasing population. This reduction
greatly affects the population especially during winter
months when the sun angle is quite low and rays cannot
penetrate certain facades as well as the streets.
ARCHITECTURAL VARIABLES
element

113.3m
20m
Figure 2-8 Architecture Variables (Sampreet Dasgupta - 4thYear B.Arch)
a) Manzana Depth and setback distance
b) Building height map
a
b

Final year B.Arch
MANZANA ORIENTATION
The blocks have been arranged in NW-SE directions
to maximize solar access and wind flow.
The benefits reaped in the winter are more light for daily
activities and insulation of buildings, which means
energy savings. In the summer, shadows are cast into
all the streets, cooling down the city. Glorious sunlight
has a psychological benefits as well.
If the orientation is modified in certain ways so as to further
increase the sunlight received, it would greatly benefit
the people senior citizens especially during the colder
months.
THE 45 DEGREE CHAMFER DEPTH
Unique to Cerda’s manzana was the 45 degree chamfer of
each corner of the city block. Cerda believed that the steam
tram would come to dominate the future of transport in
Barcelona, and as such the 45 degree chamfer was
designed to accommodate for the tram’s turning radius.
The chamfered corners create ample turning radius
for vehicles and also provide space for parking or for
development of a plaza
element

a) Image show shadow cast on to the street
b) 45 degree chamfer of Manzana
a
b

Final year B.Arch
WINDOW PLACEMENT
The number of windows affects the total exposure of
the manzana facade. Window area or window-to-wall
ratio (WWR) is an important variable affecting energy
performance in a building.
Window area will have impacts on the building's heating,
cooling, and lighting, as well as relating it to the natural
environment in terms of access to daylight, ventilation and
views.
The example shows WWR of a group of 5 blocks. The
average WWR is 31% Greater the WWR, greater is the
solar exposure and natural light received by the building.
By using number of windows and window size as a
parameter, we can modify the amount of light received
which is an important factor for social mindset especially
during long cold winters.
ALTERNATE NICHES (Not existing)
An interesting idea to increase flexibility within the Manzana
SUBDIVISIONS is to have alternate niches within them
such that the conventional square block turns into a more
interactive alternate facade.
This change will allow for the courtyard area to be reduced.
In other words, depth of the building can be increased
while keeping Open Space Ratio constant.
element

a) Elevation of selected block showing windows and fenestrations.
b) Alternate niches break away from conventional square facade
a
b

Final year B.Arch
The plans have been severely modified over the years.
As a result of this modifications, Cerda’s initial inputs and
presence of Gaudi’s monuments, several hybrid blocks
already exist.
STAGGER PATTERN IN PLANS
The interior facade of the modified Eixample plan also
shows a stagger pattern in the interior facade which faces
the courtyard. Starting from the entrance, the subdivision
length increases consecutively till the other side, from
where it starts again. This creates a stagger in the interior
façade creating a CLOCKWISE PATTERN.
SPACE ANALYSIS
As seen in the unit plan, the BLUE region depicts a 2BHK
apartment for a family of 4 people. The entire unit consists
of 4 such apartments making the total population within a
unit to be 16.
The ORANGE region shows the central shaft in every
unit used for services and also for allowing natural light
to penetrate the building Vertical Circulation within the
subdivision block is also centrally located. Provisions for
lifts have been made in the more modern buildings.
OPENING ANALYSIS
The number of windows or openings on the facade usually
falls within the limit of 3-6 windows.
As such plans can be classified based on the number of
windows, each unit has. The different types of units have
been shown on the right
UNIT PLAN ANALYSIS
element

Entrance
Façade Stagger
2BHK
CENTRAL SHAFT
6 WINDOWS 5 WINDOWS 4 WINDOWS 3 WINDOWS
a) Unit plan Analysis
a

Exercise 3: Design Drivers(f )
3.1 Translating qualitative into quantitative aspects
Design Drivers(f)
are the principles required in an algorithms to make
an informed decision using aspects such as criteria, parameters and
constrains with set with rules governed by the designer.
Traditionally, designer use the logic of CAD (computer-
aided design) or BIM (building information modeling), to
draw or model the result and choose the ultimate result.
The idea behind algorithmic thinking is that, if humans can
describe the principles driving the design process such as
requirements, character or overall objective in a form that
the computer can understand (i.e. as an algorithm), then
the tools can begin to take on a way larger role within the
design process, becoming not just a recipient of the info
but also a generator of it, creating multiple outcomes from
the principles the designers set. This shift is what marks
Computational Design as distinct from the traditional use
of computers in conventional design exercise.
This 3 week exercise aims to transition from qualitative
design aspects into quantitative aspects with the use of
analytical tools defined as evaluation criteria. Students
need to analyze existing building element re-appropriate
its purpose identify if a problem needs to be resolved or
made better.
Once the above process are set in motion they should be in
a position to create hypothesis of the design solution and
conclude its performance after basic analysis. At the end
of this exercise, further development should have rational
selection of parameter, constrains and system logic that
could potentially help them achieve desired solution.

Figure 3-1 Various type of Quantitative analysis
a) Isovist (Ashwatha Chandran - 2nd year M.Arch )
b) Surface exposure (Sampreet Dasgupta - 4thYear B.Arch)
c) Wind flow analysis- interior)(Abhishek Thakai - 2nd year
M.Arch )
d) Wind flow analysis - Exterior
e) network integration
f) Vertical isovist
(Abhishek Thakai - 2nd year M.Arch )
a
c
e
b
d
f

3.2 Introduction to analytical tools
This exercise is supplemented with master lectures of all
the analytical tools in the market. However, we limit to
specific tool and type of analysis for the purpose of this
exercise as the domain of quantifiable tools available is
huge. The master lecture gives clear insight on why a
certain type of analysis is required based on the objective
of the designer. What data to evaluate and how to make
conclusion regarding the same.
This exercise limits the analytical potential to experiential
behavior and performance of space through environmental
and syntactic(i)
aspects.
Environmental analytical techniques include sun light
hours, daylight hours, wind flow analysis. While the
syntactic tools include connectivity, integration, depth-
map, isovist, closeness centrality, betweenness centrality
and degree centrality
Syntactic(i)
uses a method that associates spatial configurations in
architecture and built environment with behavioral pattern of people.
Coined by Bill hiller and Julienne Hanson to develop insights into mutually
constructive relation between and human and space.

Figure 3-2 Analytical tools
a) Solar Radiation Analysis (Source Link : https://knowledge.autodesk.com/akn-aknsite-
ckeditor-image-uploads/d8f6e3a2-26a0-4f78-81c7-3b763e1647e7.jpg
b) Daylight analysis(Sai kiran - 2nd sem M.Arch)
c) Depthmap( Source Link :https://www.ucl.ac.uk/bartlett/architecture/sites/bartlett/files/
styles/non_responsive/public/depthmapx.png?itok=q4nDg7Ae )
a
b
c

3.2.1 Axial Analysis
Connectivity
Integration
Depth Map
The integration value, is a global property describing
the degree of connectedness of an axial line to all other
axialliness of an axial map. The higher the integration value
of an axial line, the easier it is to get to the line from all
other lines. (Rashid, 2006)
In space syntax, the depth of an axial line is the number
of steps needed to go from the given axial line to all other
axial lines in a map. A line with a high depth value will have
a low integration value. (Rashid, 2006)
The connectivity value of an axial line is the number of
axial lines directly connected to the line. The higher the
connectivity of an axial line, the greater is the number of
choices of movement from the line. (Rashid, 2006)
Axial line analysis is done to measure the accessibility
of the space. The axial map of a layout is a set of the
minimum number of longest straight lines needed to cover
every space in the layout without crossing any physical
objects. Each of these straight lines is known as an axial
line, and the complete set of lines covering the layout as
an axial map.(Rashid, 2006)
Degree of connectivity, integration and Depth can be
calculated using the axial line analysis.
Syntactical Technique

Figure 3-3 Axial line analysis(Athira - 2nd sem M.Arch )

Degree centrality
Betweenness Centrality
Closeness Centrality
Betweenness centrality is number of times a node act as
bridge along shortest path between two other nodes.
The more central a node is, the closer it is to all other nodes
In the given diagram the red dot has the highest closeness
centrality.
Degree defines the number of links to a particular
Segments
Centrality defines how central the space is. centrality of a
node is a measure of centrality in a network, calculated as
the sum of the length of the shortest paths between the
node and all other nodes in the graph.
3.2.2 Centrality Analysis

Figure 3-4 Image showing various centrality analysis
a) Degree centrality
b) Betweenness centrality
c)Closeness Centrality
a
b
c

3.2.3 Isovist
Isovist(g)
measure the extent of visibility of a space. An
Isovist(g)
is defined as the area that can be seen from a
single vantage point. Benedikt (1979) suggested several
properties that can be derived from an Isovist(j)
polygon for
the characterization of spatial situations i.e. area, perimeter,
compactness, and occlusivity. Using multiple vantage
points will most likely generate a different understanding
of the environment.
(ESUM Urban Sensing Handbook,2017)
Area: is the unobstructed radial polygon. Higher the area
more the space revealed increasing you awareness and
possibly understanding of the building.
Perimeter: Length of the edges of all space visible from
a location. Observing the minimum and maximum extents
of the length of different vantage points help effectively
make design decision of space function. For example, if
the extent is reduced you are entering a more private,
hidden, or enclosed area.
Compactness: Ratio of area to perimeter (related to an
ideal circle). It represents the relative dispersal of points
from the vantage point. For example region of plan in
which an observer’s spatial experience is consistent if the
dispersal of point is less.
Occlusivity: Length of occluding edges. Occlusion occurs
when vision is not constrained by a simple surface but
by the edge of a surface which hides something from
the view. For example, higher the level of occlusion in a
n isovist perimeter, the greater the sense of mystery. or
spatial ambiguity.
Isovist(j)
value measures the extent of visibility of a space. An Isovist is
defined as the area that can be seen from a single vantage point. Isovist
can be evaluated by its area, perimeter, compactness, occlusivity.

Figure 3-5 (a) Isovist Source Link : https://en.wikipedia.org/wiki`/File:Isovist.svg
(b) sourcelink:https://link.springer.com/referenceworkentry/10.1007%2F978-3-319-70658-0_5-1
(a)
(b)

Sunlight hour analysis calculates the number of hours of
direct solar exposure received by input geometry using sun
vectors from the Sun Path component. This component
can be used to evaluate the number of hours of sunlight
received by vegetation in a park or the hours where direct
sunlight might make a certain outdoor space comfortable
or uncomfortable.
For the purpose of this exercise it is strongly suggested to
use tools like ladybug available in grasshopper as a plug
in to have a parametric control. Ladybug imports standard
Energy Plus weather files (.EWP) into Grasshopper and
provides variety of 3D interactive graphics to aid the
design-making process during initial stages of design.
The weather data used for the purpose of this study
are approved source by the World Meteorological
Intergovernmental Organization.
It takes inputs like north, geometry, context grid size,
orientation, time giving larger parameter control over the
final output that is color chart of number of sunlight hours.
3.2.4 Sunlight Hours Analysis
Environmental Technique

Figure 3-6 Sunlight hour analysis (Sampreet Dasgupta - 4th year B.Arch)

3.2.5 Daylight analysis
Daylight factor calculation are a recognized method
for evaluating the light levels inside different rooms of
a building block annually or a specific concerned time
frame. Although this study is similar to sunlight hours
it is recommended for interior spaces as it considers
reflectivity from complex surfaces, understands material
giving accurate results.
For the purpose of this exercise it is strongly suggest to
use tools like ladybug available in grasshopper as a plug
in to have a parametric control. Ladybug imports standard
Energy Plus weather files (.EWP) into Grasshopper and
provides variety of 3D interactive graphics to aid the
design-making process during initial stages of design.
The weather data used for the purpose this study
are approved source by the World Meteorological
Intergovernmental Organization.
It takes inputs like north, geometry, context grid size,
orientation, time give larger parameter control over the
final output that is color chart of number of sunlight hours.

Figure 3-7 Daylight analysis
a) Form finding through day light analysis(The Edge / PLP Architecture, Source Link : https://images.adsttc.com/
media/images/5718/)
b) Day light Analysis ( Sai kiran 2nd sem M.Arch)
a
b

3.2.6 Wind analysis
Computational fluid dynamic allows the study of indoor,
outdoor airflow pattern & comfort by evaluating the wind
velocity of the site with its context. Certain aspects like
wind vortex(k)
allows us to see if certain quality of wind
speed can be retained for longer wind comfort.
Other features include wind drag or air resistance to study
the type of friction between air and the surface. Additionally,
surface pressure for projects experiencing certain extreme
wind velocity conditions can be used to understand if the
building has any deflections. Such study is a mandate for
skyscrapers.
For the purpose of this exercise wind pattern is of focus
using tools provided like Autodesk Flow design and
Butterfly plug in for grasshopper. Both allow live results
allowing the designer explore the geometry more critically
in the initial stage and make informed decisions.
Vortex(k)
a whirling mass of fluid or air, especially a whirlpool wind that is
characterized by rapid movement round and round.

a)Airstream results around the Architectural Institute of Japan from wind simulation
https://clqtg10snjb14i85u49wifbv-wpengine.netdna-ssl.com/wp-content/uploads/2019/05/pedestrian_wind_comfort_wind_simulation.png
b)Form optimization through wind analysis
https://preview.redd.it/ncuaxng1itl41.
Figure 3-8 WindAnalysis
a
b

3.3 Social relationship - Defining criteria for quantification
After identifying character of space through building
elements in figure 3.9 and in coherence with the aim
mentioned in exercise 3 students elaborate on the potential
criteria for quantification. Criteria selected for analysis are
based on the need of particular space and the student
need to justify the need for such an intervention.
Clarity of link between social behavior and the performance
of the space can only be establish with the understanding
of appropriate criteria. The student needs to go back and
forth on their hypothesis before arriving to a conclusion.
For the purpose of this studio we encourage taking at least
three contradicting criteria.
Demonstrate critical breakdown of the use of criteria
for evaluation with reference to the space. For example,
in figure 3.9(b) the student observes open plaza and
streets having two distinct activity and hence, demanding
different quality of sun exposure. The plaza required sun
during evenings due to mass gather before praying while
the streets required exposure due to the narrow width and
high walls of the adjoining building.
The exercise needs to focus on finding appropriate domain
of number of hours that may be required for the space, time
and specify months that might be a problem after analysis.
At least, 3 spaces should be abstracted with the relative
criteria for evaluation before approaching an experiment
for developing a system.

Existing big plaza
Existing small plazas
Figure 3-9 Social relationship (Khushboo Makwana - 4th year B.Arch)
a) Gathering in plaza (Social activity)
b) Identifying various types of plaza
c) Existing Plaza exposure (Criteria)
a
b
c

Final year B.Arch
Different activities in courtyard Area
Living space 8 to 9 sq m
Gathering pace 8 to 9 sq m
Children play area 9 sq m
Small garden for vegetation 6 sq m
Different activities in courtyard Area
Gathering and sitting pace 6 to 9 sq m
Morning break fast 9 sq m
Small garden for vegetation 6 sq m
Courtyard of the space seemed to be the nucleus of the
space with three different variety of activities simultaneously.
The objective was to keep the women drying area exposed,
children play area minimal and the seating area to be least
exposed. Winter sun path seemed to be a major concern for
the afternoon and evening time zone.
Social relationship - Defining criteria for quantification
Example Student : Gelani Khushali

Figure 3-10 Analyzing various spaces based on social activities (Khushboo Makwana - 4th year
B.Arch)
a) Existing Solar exposure in courtyard
b) Plan showing various Social activities.
c-d)image showing Social activities on terraces.
c) Existing Plaza exposure (Criteria)
a
c
b

3.4 Problem Statement - analyze and evaluate various spaces
using criterias.
The studio only considers a problem statement upon
analysis of all concerned spaces identified in exercise
2.3 with the established social relationship by means of
criteria in exercise 3.3. The values generated by using
analysis like exposure on spaces like plaza, facade, floor
slab, visual vista, integration etc helps set the foundation
of the projects and its design solution through a rational
evaluation of results.
Certain aspects of design upon case study may seem
a problem but with intervention through appropriate
criteria the approach is better informed towards a design
solutions. In figure 3.11 initial case study revealed that
certain exhibits in the museum have lesser engagement
compared to others. The analysis of integration(l)
revealed
that it is difficult to get to the furtherest point of the site
while moving around the space due to the placement of
certain exhibits.
Defining upon a justifiable problem statement the student
could now know what caused the issue and make a smarter
hypothesis of how to arrive at a design solution. As per
figure 3.11 the student focuses on space planning strategy
of the placement of exhibit using the above criteria as the
dominant design driver along with maximum visitor time,
entry, age group, type of visitors, highly engaged exhibits
as attractor point to re-direct traffic to other exhibits. The
synergy of a well distributed exhibit layout where the entire
floor area is utilized as well visitor engage with all exhibits
is the goal of the designer.
Integration(l)
value if a global property describing the degree of
connectedness of an axial line to all other axial lines in a map. The higher
the integration value of axial line, the easier it is to get to the line from all
the other lines.

Figure 3-11 Axial line analysis(Athira - 2nd sem M.Arch )

2nd year M.Arch
Isovist(j)
a
b
Problem Statement - analyze and evaluate various spaces
using criterias.
Example Student : Tejaswini Walunj
Here the student finds the dense foliage on the site as a
gift against the harsh sun of Mumbai but is concerned
with visibility from inside and outside between the context
and the site after evaluating isovist(g)
analysis. The designer
and the client’s mission statement both believed that view
plays a major role in increasing visitor into the museum.
Upon study of isovist(j)
the designer could now focus on a
design approach keeping in mind specific view points as
well as height.

Figure 3-12 Axial line analysis (Tejaswini Walunj - 2nd sem M.Arch )
a) Bird eye view : Baudaji lad Museum
b) Identification of tree species and radius of its foliage
c) field of view at various height using isovist
Isovist at 20 m
Isovist at 1.5 m
Isovist at 15 m
Isovist at 3 m
c

3.5 Hypothesis- Parameter Study and form finding
The student approach design intervention by changing single
parameters affecting dramatic change in the morphology. A
hypothesis emerges from this exercise as the student analyze
each manipulation in the morphology on the set area in the
problem statement against the criteria established through
social relationship. Although the scope of area for evaluation
are larger the initial analysis takes into consideration local
level changes to see what parameters have larger response
on the criteria.
The exercise also promotes exploring different know systems
that have been instrumental in solving similar problems like
use of louvers as sun breakers. Also, abstracting parameters
that might dominant in generating solutions closer to the
fitness criteria. For example, rotation along of a single axis
is the key driver in influencing exposure for a louver system.
Parametric logic allows such understanding to help evolve
a potential system like in the hypothesis is breaking the
body plan of the louvers into more segments allowing better
response to the sun exposure.
The overall system hypothesis is a culmination of various
elements and parameters that hold a holistic value with the
project in terms of its aesthetic appeal, contextual response,
creativity, innovation , geometrical exploration and spatial
behavior.

Figure 3-13 Collage of various analysis done on housing typologies (Final year students B.Arch)

Building typology of manzana in Barcelona is used for this
intervention where the student explores all possible facade
system that allow better daylight into the building. It also
adhere to the holistic aspect of the morphology that might
be possible to combine and create a system hypothesis.
Following through the process in figure 3.14 the designer
checks the various facade system in all direction mostly
concerned with the overall daylight into the building.
The building is a mixed use typology with offices and
residences.
The target was to allow adequate light but for different time
period in both residence and office as well specific spaces
like staff area and bedroom. All the window of the facade
need to behave differently in coherence with the function
of the space motivating the student to serve each purpose
while also creating a aesthetically creative design solution
Hypothesis- Parameter Study and form finding

Figure 3-14 Image shows facade experiment for the better daylight Condition
(Sampreet Dasgupta - 4th year B.Arch)
a)Facade with existing window
b)Facade with Verticle louvers
c)Facade with horizontal louvers
a
b
c

Exercise 4: Design limitation
At this stage setting of specific values of FAR and Pop/Ha
is established and why those values are important needs
to be defined. Elaborating on how setting these value will
better help in controlling the scale of the project for e.g.
FAR with only 60% land cover will never allow a skyscraper
in the set rules of design during an iterative process. Such
sensitivity on how the given values where selected to
control the scale and respect the social fabric is paramount
in the project and sets the foundation of design target for
their project. Making conclusion based on the study of the
existing form and what could be causing problem with the
building’s FAR & Pop/ha was established.
4.1 Building scalability
Aim

Figure 4-1 KOWLOON WALLED CITY HONG KONG (Astha Shah - Final year students B.Arch)

Parameters are the soul for controlling the design.
Understanding of which parameters are important and
how it might help in achieving desired criteria and maintain
the design target of volume, FAR and Pop/Ha. Making it
clear that the domain selected is in accordance to the set
design target and population density before focusing on
optimizing exposure. Relationship between each step is
of prime importance here. The system can truly can only
be intuitive if its understands each other behaviors. Basic
understanding of how a combination of all rules with
parameters and constraints generated their morphologies
and whether the overall performance is accepted or not.
The iterations are selected should be best of minimum
or maximum based on the set target values of criteria.
Abstract from the graphs which parameter performed
better compared to other and which is most redundant
parameter or needs to be changed. Students go back and
forth during this experiments as it is not a linear process.
There is synthesis of all the components of this new design
process and at every stage their is feed back between
parameters, design target and design criteria making the
system evolved and smart.
4.2 Synthesis using previous study and calculating the given
bylaws
159905.6
92552.8
87012.4
165811.5
90733.3
88370.7
156702.1
92722.5
88736.0
92046.1
2.6
2.4 2.3
2.6
2.4 2.3
2.5 2.4 2.3 2.4
485
608
538
490
618
586
480
592 602
570
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
Iteration 5 Iteration 17 Iteration 21 Iteration 30 Iteration 38 Iteration 40 Iteration 47 Iteration 65 Iteration 82 Iteration 90
FAR | Volume | POP/Ha Comparison
Volume FAR POP/Ha Achieved POP/Ha Average

Iteration 5
Volume : 159905
FAR: 2.6
Pop/Ha: 485
Iteration 21
Volume : 87012
FAR: 2.3
Pop/Ha: 538
Iteration 30
Volume : 165811
FAR: 2.6
Pop/Ha: 480
Iteration 47
Volume : 156702
FAR: 2.5
PoP/Ha: 480
Facade exposure Ground exposure
Figure 4-2 Comparing Volume/FAR/pop.ha of generated iterations (Sampreet Dasgupta- 5th year students B.Arch)

Exercise 5: Evolution of build form
5.1 Deterministic to probabilistic system designers
System design is a set of things working together as parts
satisfying specific requirements interconnected forming
a complex whole. System design requires a coherent
approach preferably Bottom-up or Top-Down to take into
account all related variables of the design. Students set
up a system in this exercise based on the information
collected from there hypothesis prepared in exercise 3.5
and run experiments for multi-objective optimization.
The tool used for this optimization is based on the principles
of evolutionary computation explained in exercise 5.2.
The structure involves social logic of evaluation criteria,
system logic based on the parameter study, pseudo code
that explains the rules of execution and use of evolutionary
computation to abstract rational selection of fittest iteration
from n-number of solution.
Ambition of this exercise is the ability of students in using a
research based data-driven methodology for their project.
Such an iterative process helps students to develop
evolutionary algorithms by quickly giving feedback to
system as they progress with new generations developing
a robust scientific design process to solve multiple
conflicting objectives that hold no clear single solution.
Aim

Figure 5-1 Comparison of Morphologies for maximum exposure on courtyard and open terraces. (Gelani Khushali-
5th year students B.Arch)

5.2 Introduction to evolutionary computation
Evolutionary Algorithms have been used extensively in
recent years to mimic the principles of evolutionary science
to solve common real-world problems through search and
optimization procedures of single or multiple objectives.
Ranging from the fields of economics to politics and music
to architecture, evolutionary algorithms have proven to
be an efficient problem-solving technique to find multiple
trade-off solutions for problems that possess multiple
‘fitness criteria’ (objectives) that are in conflict with one
another.
The aim of the seminar is to introduce the concepts
of multi objective optimization as well as to develop an
understanding of their application in design primarily
through the development of building tissues. The seminar
will provide necessary knowledge for the utilization of multi
objective evolutionary algorithms across a range of scales
as well as varying degrees of complexity.
It is inspired from biological evolution following the logic
of natural selection each new iteration is produced by
stochastically(j)
removing less desired solutions and
introducing small random changes like mutation. As a
result, the iteration will intuitively evolve towards solution
based on the selected fitness criteria. For the purpose of
this exercise we limit to using Wallacei as the multi-objective
optimization engine to run simulations in Grasshopper 3D.
Stochastic(l)
having randomly probability distribution or pattern that may
be analyzed statistically but may not be predicted precisely.

Figure 5-2 Iterative Morphologies (Source LInk : Emergence Seminar , http://pr2014.aaschool.ac.uk/submission/
uploaded_files/EMERGENT-TECHNOLOGIES/Emergence%20and%20Design-Ale-faisal-Shahad_jose-1.jpg

A checklist of ingredients required before starting the
experiments. Student needs to elaborate on each part
and make sense of the entire intervention based on the
hypothesis set with a probabilistic idea of how the system
would behave upon change by its parameters, relationships
between building elements as the design morphs into a
form and its performance through evaluation criteria.
The flow chart explains the core structure of this studio
on the premise of ‘Algorithmic Thinking-A parametric
approach to problem solving’. Studio tutors put together
this streamline process based on the duration of this course
and level of students with the hope to introduce students
to a new paradigm of computational design. The process
can work as the foundation to explore such a process at
various scale and application from product to urban scale.
The phenomenon of ‘Emergence’ presents itself at the
foreword of such a design process whereby a higher order
functionality is created out of larger number of smaller
scale interactions. In Architecture, the term represents a
design philosophy where the final design outcome is not
decided by the designer but generated through a careful
process of data gathering and translation.
5.3 Mandate setup into Emergence

System Logic
Pseudo Code
Parameters
Analysis
Design
Drivers
Evolutionary
Computation
Desired
Solutions
Mutation
Constrains
Iterations
Limitation
Evaluation
Solutions
Emergence
[Fittest Solutions]

5.4 System Logic
System logic explains the schematics of the project in
brief that the student wishes to execute for performing
the experiment. The underlining illustration should clearly
demonstrate the procedure that governs the morphological
intent. The project should also consider all design limitation
of the site. A holistic debate on how such a system plays
a larger role with the form, function and space should be
part of the intervention.
In figure 5.3 the project is an extension of an existing
museum where the student wants to manipulate edge
condition of the building allowing different quality of
view i.e. building to site, building to context, space to
neighborhood. The building is envisioned as a crescent
adjoining the existing museum that gradually rises from its
landscape. The inner core is concentrated while the outer
periphery has distributed spaces.
As mentioned in exercise 1 in a system design each
procedure informs the previous steps hence deciding
the key drivers of the design become of paramount
importance. In figure 5.3 the student designs inside out
by first establishing floating point representing outdoor
space in a loop. Furthermore, the size of the space based
on the occupancy and finally, the radial displacement of
the space achieving a solution that targets quality of view
from all spaces by using criteria isovist(j)
.
Isovist(j)

a
Incrementally sloping roof as per the
optimum walking gradient.
b
Extending and projecting roof to
create canopy for Outdoor Activity
Zones
c
Modulating the roof towards Plaza to
merge it with the Landscape
1- Demarcate the location of
Outdoor Activities along the edge.
2- Outdoor activity zones as
repulsion points, to establish
ground footprint.
3 - Optimizing footprint based
on Field of View study along the
Activity zones & Isovist from the
main Entry.
Figure 5-3 System Logic.(Mishal Dodia 5 year B. Arch)

5.5 Pseudocode
Pseudocode(f)
summarizes a program flow, but excludes
underlining details. In figure 5.4 the student is trying to
break down their design process of a housing cluster by
simple set of rule and procedure. It is important to have at
least six parameters for manipulation of the morphology
and three constrains for the purpose of this exercise.
Exercise 5.5 assess the ability to decide possible
parameters that could help the criteria, constrains to
capture keep essence of the space and limitation that
cannot be ignored for the project. The pseudocode(d)
must be a hybrid model designed by the tests executed in
exercise 3.5 as it combines multiple design elements into
one system. Every space should be informed of its role
in the system by giving relationships and parameters that
can increase the performance of the space.
Using evolutionary computation, multi objective
optimization intuitively evolves the system as each aspect
of the space is manipulated from different scale trying to
reach set fitness criteria.
In figure 5.4 the student sets up a housing typology
informed by its plaza spaces. Procedure includes defining
a boundary, subdividing the periphery blocks, depth of
staggering, defining the inner cluster, subdividing the
block, depth of staggering and finally height of the block
relative to its size.
Pseudocode(f)

Figure 5-4 Pseudocode.(Khushboo Makwana 5 year B.Arch)

For the purpose of this exercise use at least three
contradicting criteria as per exercise 3.4. The criteria are
chosen from the problem statement however, in case of
multiple area of concern students need to decide criteria
that is major character of site. For example evaluating
balconies rather courtyard due to its higher use in the
building typology.
Each criteria need to either maximize or minimize based on
the targets. Revisiting exercise 3 criteria should be defined
with expectable target domain, duration of analysis,
total number of hours and methods of evaluations after
analysis. In figure 3-10 exposure of the courtyard is set to
maximize but the fitness of the iteration is to evaluate area
for number of hours into three parts to provide adequate
exposure based on activity of drying, seating and playing.
The criteria can be syntactical or environmental aspects
but limited to the analytical tools mentioned in exercise 3.2
Fig 5-1
5.6 Analyzing all criteria through multi objective optimization

Figure 5-5 Isovist at multiple location on site to identify maximum field of view.(Ashwatha Chandran 2nd sem M.Arch)
Figure 5-6 Solar exposure analysis performed on courtyard and facade.(Sampreet Dasgupta 4th year B.Arch)
Figure 5-7 Maximizing solar exposure on internal facade by angular movement( Dhruv Bhatia 5th year B.Arch)
Fig 5-2
Fig 5-3

Plethora of Iteration(g)
are generated using evolutionary
computation in this section of the exercise. Students need
to evaluate the results of the criteria and abstract the fittest
iteration from a list of at least 100 iteration. The experiment
could either be successful or failure based on the selection
of parameter, constrians and rule s used to approach the
system.
5.7 Iteration evaluated using graph theory
Integration(g)
value if a global property describing the degree of
connectedness of an axial line to all other axial lines in a map. The higher
the integration value of axial line, the easier it is to get to the line from all
the other lines.

Figure 5-8 Iterations( Abhishek Thakai Final year M.Arch)

Final year B.Arch
Example Student : Khushboo Makwana
A B C
D E F
G H I
Total Open Space (%)
Total Built-Up (%)
Big Building Facades (%)
Small Building Facades (%)
Total number of blocks
Boundary blocks height (avg. in m)
Centre blocks height (avg. in m)
The Analysis shows the realtionship
between criteria and parameters.
Criterias majorly gets affected
by number of blocks, heights of
buildings and builtup vs. open space
areas.
For e.g. : If we look at IT A and IT I : Built
up area is less in IT A and also number of
blocks are less in IT A than in IT I , but still
IT A has least ground exposure because
the buildings have higher heights there.

Figure 5-9 Analysis showing relationship between criteria and parameters.(Khushboo Makwana 5 year B.Arch))
a)Pie charts showing comparative study of parameters of selected iterations
b)Iterations with the facade exposure ,FAR and Pop/Ha.
A. 37
POP/Ha : 1204
F.A.R : 4.6
B. 2
D. 7
POP/Ha : 1338
F.A.R : 5.0
E
G. 43
POP/Ha : 1317
F.A.R : 5.1
H.
B. 28
POP/Ha : 1317
F.A.R : 4.8
C
P
F
E. 42
POP/Ha : 1144
F.A.R : 4.2
F.
P
F
H. 26
POP/Ha : 1165
F.A.R : 4.4
I. 4
P
F
C. 32
POP/Ha : 1367
F.A.R : 5.3
Exposure grid:
4m x 4m
Total Open
Space (%)
Total Built-up
Space (%)
44
46
49
50
Total no.of
blocks
F. 49
POP/Ha : 1208
F.A.R : 4.6
I. 45
POP/Ha : 1302
F.A.R : 4.9

Exercise 6: Design Proposal
Architecture is a field having large scale projects
encapsulating many variable in to a building. The studio
only focuses on the key aspects as the goal is to develop
a new design thinking using computational tools. Design
proposal acts like the final pitch of the project taking into
account all secondary design requirements that simply
cannot be neglected for composing a sensible project.
Visual representation and documenting the entire project
is closely monitored in this exercise as the final outcome
should generate interest and demonstrate the intense
thought process that went into the design. Algorithmic
techniques are quite extensive and a proper methodology
of explanation through illustration, videos, render is crucial
to do justice to the student work.
The system design of the student make consideration of
space and its potential function while running the algorithm.
However, a plan need to be generated at this stage to see
what changes could be integrated in the system while
further development. Developing one holistic system that
informs all variables is not a practical task for introductory
courses hence, understanding of how to keep provision
and certain tolerance in the system design become very
important.

Figure 6-1 Render showing entrance to museum
Figure 6-2 Render showing entrance to museum
Fig 6-1
Fig 6-2

2nd year M.Arch
The student proposal shows Breakaway from
existing museum palladian architecture to
create minimal architecture with optimized
openings for more flexibility of surface area
both internally and externally.
Program of the museum is devised through
the light sensitivity required for each space.
Outdoor movement pattern became reference
to museum indoor activities and divided the
spaces in to 3 major zones. Three major zones
were guided by the outdoor core activities.
The block is divided to create better
integration of the site Activities. Also helps
to break the mass for fine urban grain and
distribute the pedestrian flow across the site.
Fig 6-3
Fig 6-4
Example Student : Sai kiran
Design Proposal
Design Proposal

Figure 6-3 Piet mondrians painting
Figure 6-4 Render showing facade as exhibit space
Figure 6-5 Section showing the volume of spaces, light quality and Exhibit arrangements.
Figure 6-6 Image showing Temporary exhibit space
Figure 6-7 Image showing gallery space
Fig 6-5
Fig 6-6
Fig 6-7

Student has Selected the final
iteration considering the given
criterias and Developed a design
proposal. Various facade systems
are implemented based on the
experiments performed in exercise
3.5(fig 3-14). Additionally planning
is done considering the different age
groups and the orientation of the
unit.
Design Proposal
Figure 6-8 detail unit plan
Figure 6-9 Arrangement of unit plans
Figure 6-10 Render shows the
Fig 6-8

Studio aims at understanding how the design
of dwellings can facilitate their adaptability
in reference to Site context and scale using
computational design methodology. Here
student has taken Kowloon walled city which
was the epitome for dense urbanization. Aim
is to Study existing block typology and identify
various issues considering the given criteria’s.
Here Student has addressed the problem
regarding the sunlight at the street level and
re-imagined it in consideration with current
Scenarios.
KOWLOON WALLED CITY HONG KONG Student : Astha Shah
Students work, spring 5th semester 2020, Bachelor of
Architecture

Final year B.Arch
Defining Parameters, rules and Constrains.

Final year B.Arch
Evaluation Criteria’s and targets.

Final year B.Arch
Evolution of Build form

City Museum is the third oldest museum in India and the oldest in
the city
Project Brief
The Mumbai City Museum, also known as the Dr. Bhau
Daji Lad Museum (Dr. BDL Museum), is in the process
of creating a new dynamic identity for itself as a cultural
hub in Mumbai. It is one of India’s most outward-looking
cultural institutions, with strong links to its sister museum,
the V&A in London.
At the heart of the new wing will be a permanent gallery to
showcase contemporary Mumbai, focusing on important
milestones in the city’s development and highlighting its
cultural achievements, as well as temporary exhibition
space to international standards capable of taking large-
scale touring exhibitions.
The new galleries, education and social facilities will
give us valuable extra space and also the opportunity to
rethink the landscaping of the whole site, in this, a rare gr
een pocket of south Mumbai.
Student : Mishal Dodia
Extension to Bhau Daji Lad Museum
Students work, monsoon 3rd
semester 2019, Master of
Architecture

CONTEXT
delightful setting in the lush surroundings of the city’s botanical gardens and the zoo
next door.

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