Algorithmic Thinking - A parametric approach to problem solving

ALGORITHMIC THINKING 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

COURSE PEDAGOGY AND STUDENTS WORK S T U D I O T U T O R S | K U B E R PAT E L | A H M E D A B B A S M O M I N S T U D I O A S S I S TA N T | M I H I R VA S A N I

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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“We certify that this piece of work is entirely of cept students and that any quotation or Image from the published or unpublished work of others is duly acknowledged.”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

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Ahmed Abbas Momin

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Ac k n o w l e d g m e n t

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.

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Fo re wo rd

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

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Pre f a c e W hy A l g o r i t h m i c T h i n k i n g i s n e c e s s a r y i n d e s i g n ?

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.

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

Figure I

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I n t ro d u c t i o n

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.

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

Figure II

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Tu t o r Pro f i l e

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.

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.

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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 V ‘Office Interior ’ by Mihir Vasani,The Undulation in ceiling is parametrically derived using pattern based on wood grains.

Figure III

Work Image Figure IV

Figure V

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Le a r n i n g o u t c o m e

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.

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

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Ta b l e o f Co n t e n t s E x e rc i s e 1 : B o o t c a m p 1 . 1 I n t ro d u c t i o n t o d e s i g n s o l u t i o n s u s i n g p a r a m e t r i c l o g i c ���������������������������������������������� 1 8 1 . 2 D i g i t a l m o r p h o g e n e s i s ( b ) ( c ) o f s p a t i a l c o n f i g u r a t i o n a n d c h a r a c t e r. ������������������������������ 2 0 1.2.1 1.2.2

Summarizing work-flow using stepwise procedure into set of rules.

Creating multiple outcomes defined by a system specific sequence.

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1 . 3 D e c o d i n g Pi e t M o n d r i a n p a i n t i n g o n i m p u l s i ve i m p re s s i o n . ���������������������������������������� 2 6 1.3.1 1.3.2 1.3.3

Story telling through the overlay between quantitative and qualitative analogy.

Summarizing work-flow using stepwise procedure into set of rules.

Creating multiple outcomes defined by a system specific sequence.

28 30 38

1 . 4 S t u d e n t s wo r k , m o n s o o n 3 rd s e m e s t e r 2 0 1 9 , M a s t e r o f A rc h i t e c t u re ���������������������������� 4 0 1.4.1

Shell geometry derivative by cross referencing points.

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1 . 5 S t u d e n t s wo r k , s p r i n g 5 t h s e m e s t e r 2 0 2 0 , B a c h e l o r o f A rc h i t e c t u re ���������������������������� 4 4 1.5.1

Decoding Piet Mondrian Painting through a set of rules.

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E x e rc i s e 2 : I d e n t i f i c a t i o n o f D e s i g n Va r i a b l e s 2 . 1 A b s t r a c t i o n o f re l a t i o n s ������������������������������������������������������������������������������������������������� 5 0 2 . 2 Pr o g r a m �������������������������������������������������������������������������������������������������������������������������� 5 2 2.2.1 2.2.2

Extension to Bhau Daji Lad Museum Program Evolution of housing Typology

52 54

2 . 3 B u i l t e nv i ro n m e n t - c h a r a c t e r o f s p a c e t h ro u g h b u i l d i n g e l e m e n t ���������������������� 5 6

E x e rc i s e 3 : D e s i g n D r i v e r s 3 . 1 Tr a n s l a t i n g q u a l i t a t i ve i n t o q u a n t i t a t i ve a s p e c t s. �������������������������������������������������������� 7 2 3 . 2 I n t ro d u c t i o n t o a n a l y t i c a l t o o l s ������������������������������������������������������������������������������������ 7 4 3.2.1 3.2.2 3.2.3 3.2.4 3.2.5 3.2.6

Axial Analysis Centrality Analysis Isovist Sunlight Hours Analysis Daylight analysis Wind analysis

76 78 80 82 84 86

3 . 3 S o c i a l re l a t i o n s h i p - D e f i n i n g c r i t e r i a f o r q u a n t i f i c a t i o n ������������������������������������ 8 8 3 . 4 Pr o b l e m S t a t e m e n t - a n a l y z e a n d e v a l u a t e v a r i o u s s p a c e s u s i n g c r i t e r i a s . ���������� 9 2

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3 . 5 H y p o t h e s i s - P a r a m e t e r S t u d y a n d f o r m f i n d i n g �������������������������������������������� 9 6

E x e rc i s e 4 : D e s i g n l i m i t a t i o n 4 . 1 b u i l d i n g s c a l a b i l i t y ��������������������������������������������������������������������������������������������������� 1 0 0 4 . 2 S y n t h e s i s u s i n g p re v i o u s s t u d y a n d c a l c u l a t i n g t h e g i ve n b y l a w s

����������������������� 1 0 2

E x e rc i s e 5 : E v o l u t i o n o f b u i l d f o r m 5 . 1 D e t e r m i n i s t i c t o p ro b a b i l i s t i c s y s t e m d e s i g n e r s ����������������������������������������������������� 1 0 6 5 . 2 I n t ro d u c t i o n t o e vo l u t i o n a r y c o m p u t a t i o n ��������������������������������������������������������������� 1 0 8 5 . 3 M a n d a t e s e t u p i n t o E m e r g e n c e ������������������������������������������������������������������������������� 1 1 0 5 . 4 S y s t e m Lo g i c ����������������������������������������������������������������������������������������������������������� 1 1 2 5 . 5 Ps e u d o c o d e ��������������������������������������������������������������������������������������������������������������� 1 1 4 5 . 6 A n a l y z i n g a l l c r i t e r i a t h ro u g h m u l t i o b j e c t i ve o p t i m i z a t i o n ����������������������������������� 1 1 6 5 . 7 I t e r a t i o n e v a l u a t e d u s i n g g r a p h t h e o r y ������������������������������������������������������������������� 1 1 8

E x e rc i s e 6 : D e s i g n P ro p o s a l Students work • S p r i n g 5 t h s e m e s t e r 2 0 2 0 , B a c h e l o r o f A rc h i t e c t u re. ����������������������������������������������������� 1 2 6 • M o n s o o n 3 rd s e m e s t e r 2 0 1 9 , M a s t e r o f A rc h i t e c t u re. ����������������������������������������������������� 1 3 4

Bibliography

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E xe rc i s e 1 : B o o t c a m p 1.1 Introduction to design solutions using parametric (a) logic

Aim 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.

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.

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

Fig 1-1

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Monsoon Semester 2019 2nd year M.Arch

1.1 Digital morphogenesis (c)(d) of spatial configuration and character.

Objective 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.

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.

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

Fig 1-2

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Monsoon Semester 2019 2nd year M.Arch

1.1.1 Summarizing work-flow using stepwise procedure into set of rules.

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.

STEP 01 : DEFORMATION INTENSITY. Rule: Define reference object with set radius and number of segments.

Parameter: Number of vertical section

with an invert relationship.

Parameter: Depth of section.

vertical

STEP 06 : DEFINING CURVE THROUGH DEFORMED POINTS. Rule: Draw vertical cross section STEP 02 : by interpolating points between DEFINING CROSS SECTION each horizontal section grafted by INTERVALS. Rule: Increments of Fibonacci number of vertical sections. sequence between sections.

Constrain: Spacing between STEP 07 : section.

SURFACE FORMATION. Parameter: Number of horizontal Rule: Creating network surface section. through achieved curves with edge conditions on both sides same as the reference object.

STEP 03 : IDENTIFYING THE DEFORMATION POINTS. STEP 08 : Rule: Alternate point selection on DEFINING HEXAGONAL CELLS. each section with inverted relaParameter: Defining no. of tionship to its neighbors.

Hexagonal divisions.

Constrain: Identifying the deformation points based on the STEP 09 : ascending spiral selection.

DEFINING HEXAGONAL CELL STEP 04 : DIRECTIONAL MOVEMENT OF THE IDENTIFIED POINTS. Rule: Perpendicular movement of deformation points to its section

OPENINGS. Constrain: Opening of the cells on surface becomes smaller as the deformation points moving away from the axis.

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.

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Figure 1-3 Pseudocode- Deformation on tubular surface with relative fenestrations.(Sai kiran - M. Arch 2nd year)

Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Step 7

Step 8

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Monsoon Semester 2019 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.

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 Frequency of the Sin curve : 2 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 Frequency of the Sin curve : 6 Amplitude : +3

ITERATION 05 : Decreasing the height of the curves and increasing the depth of the curve.

For 1st sin curves Frequency of the Sin curve : 10 Amplitude : +1 ITERATION 06 : Decreasing the depth and increasing the depth of sin curves.

For 2nd sin curves Frequency of the Sin curve : 9 Amplitude : +1.5 ITERATION 07 : Decreasing the depth curve with one sin curve count and increasing the depth of curve.

For 2nd sin curves Frequency of the Sin curve : 13 Amplitude : +0.5 ITERATION 08 : Decreasing the depth sin curve and increasing the depth of curve.

For 2nd and 4th sin curves Frequency of the Sin curve : 6 Amplitude : +2

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.

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Figure 1-4 Iterations- Exploration of surface through sine curves.(Tejaswini Walunj - M.Arch 2nd year)

BOOTCAMP: Exploring geometrical configuration through a set of rules. of rules.

Exploration 1: Exploration of surfaces through sine curves

25 TEJASWINI | PG81114| Page MAAD

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.

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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

BOOTCAMP: BOOTCAMP: Decoding Decoding PietPiet Mondrian Mondrian Painting Painting through through a set aofset rules. of rule NARRATIVE NARRATIVE Selected Paintings Mondrian Selected Paintingsby

by Piet Piet Mondrian

Dom

The

The P

Painting 1 Painting 1 a

Painting Painting2 2 b

Painting 3 Painting 3 c

The fi due to exten story

Areas covered colored rectangles with the painting Areas by covered by colored rectangles withrespect respect toto thethe totaltotal area area of the of painting

There is a Dominance There is a Dominance of the of the red color. red color.

Areas Areas covered coveredby by diff different erentcolored colored rectangles rectangles are almost areofalmost of equalequal proportions proportions in in Painting Painting 2 and 2 and Painting Painting 3.

3.

This creates Stability This creates. Stability.

This This creates createsInstability and Chaos.

Instability and Chaos.

Geometric shapesshapes and their meanings Geometric and their meanings

S

R

The o them Page 27 presence of SquarishThe s The The presence of Squarish

Conclusion Conclusion

Spring Semester 2020 Final year B.Arch

1.2.1 Story telling through the overlay between quantitative and qualitative analogy.

Narrative 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

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Figure 1-6 Narrative (Astha Shah final year B.Arch) a) Area covered by the painting Painting 1 precedent with controlPainting 2 it into two opposite stories..Painting 3 b) Painting is here looked as line dividing c) Subdivision of the painting

T

T d e s

Areas covered by colored rectangles with respect to the total area of the painting

rules.

f rules.

ing

ing

f

f

ish inant stable

ion to

ish

There is a Dominance of the red color.

Areas covered by different colored rectangles are almost of equal proportions in Painting 2 and Painting 3.

This creates Stability.

This creates Instability and Chaos.

Control Line a

Control Line

Geometric shapes and their meanings

Conclusion Blue Twin The presence Squarish Control Line of

Control Line

geometry and a Dominant in painting 1 makes it a stable expression in comparion Blue Twin to

Dominant Red

the other two paintings.

Dominant Red

Stability (to pause)

Transit (to move) Yellow Twin The story of Chaos

The story of Simplicity

The Painting here is looked as a Precinct with a Control line dividing the precinct into two opposite stories.

Yellow Twin

The second story is a mayhem of elements. It has The first story is a stable and simple expression The story of Chaos The story of Simplicity two colors having equal areas. There are lines that due to presence of a dominant and only one line aredividing not relating to anything.

Thus, we call stories. it the story extending through thelooked dominant.

Thus, we with call ita the The Painting here is as a Precinct Control line the precinct into two opposite of Chaos. b story of Simplicity.

The second story is a mayhem of elements. It has The first story is a stable and simple expression two colors having equal areas. There are lines that due to presence of a dominant and only one line are not relating to anything. Thus, we call it the story extending through the dominant. Thus, we call it the Area-Blue of Chaos. story of Simplicity.

Common

Subdivision

Common Room of Red Subdivision Story Connector Room of Red Room of Black Story Connector

Room of Blue Room Blue Room of of Yellow

The only line, part of both the stories, connecting

c them is the Story connector.

Room of Black

Room of Yellow

The story connector together with the control line makes 4 rooms giving individual spaces for each The only line, part of both color to move.

Room of redthe & stories, black in connecting story of them is the Story connector. simplicity and room of blue & yellow in story of The story connector together with the control line chaos.

Area-Red (30% of areaprecinct) Area-Red 8A sq. units (30% of areaprecinct) 8A sq. units

A sq. units Area-Blue A sq. units

Area-Yellow A sq. units

Some fixed aspects (CONSTRAINTS) Area-Yellow (1) The control line (2) The location of the colors A sq. units (3) Area covered by the colors (CONSTRAINTS) Some fixed aspects (4) Position of the common subdivision Page 29 (1) The control line (2) Thevariable locationaspects of the colors (PARAMETERS) Some

T t T m c s c T s s

Spring Semester 2020 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) 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.

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

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Spring Semester 2020 Final year B.Arch

Pseudocode 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:

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STEP 01

STEP 02

STEP 03

STEP 04

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Spring Semester 2020 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.

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STEP 05

STEP 06

STEP 07

STEP 08

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Spring Semester 2020 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.

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STEP 09

STEP 10

STEP 11

STEP 12

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Spring Semester 2020 Final year B.Arch

1.2.3 Creating multiple outcomes defined by a system specific sequence.

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.

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Parameters

Constraints

Distant of primary line (l1) Area of colour Percentage of colour

Location of colours No. of Subdivisions

ITERATION 01 : l1: 6 unit area of colour : 20sq.units Perc. of coloured area : 25%

ITERATION 04 : l1: 6 unit area of colour : 16 sq.units Perc. of coloured area : 19%

ITERATION 02 : l1: 6 unit area of colour : 21sq.units Perc. of coloured area : 23%

ITERATION 05 : l1: 6 unit area of colour : 18 sq.units Perc. of coloured area : 21%

ITERATION 03 : l1: 6 unit area of colour : 17sq.units Perc. of coloured area : 20%

ITERATION 06 : l1: 6 unit area of colour : 18 sq.units Perc. of coloured area : 21 %

ON TYPE 2

Figure 1-8 Iterations (Sampreet Dasgupta 4th year B.Arch) ITERATION TYPE 2

ITERATION TYPE 1

iterations thedistance differentof positions of the secondary and tertiary line keeping the primary lines The following iterations show the different positions of the all the lines with respect toThe the following position of the UP show line. The this 6 units from origin. Rest ofbeen the parameters line from the origin changes which changes all other line positions as well. Rest of the parameters andthe constraints have mentionedand constraints have been mentioned in the images themselves in the images themselves.

ITERATION TYPE 2

ing iterations show the different positions of the all the lines with respect to the position of the UP line. The distance of this show the parameters different positions of the all have the lines respect to the position of the UP line. The distance of this he origin changes which changes all otherThe linefollowing positionsiterations as well. Rest of the and constraints beenwith mentioned line from the origin changes which changes all other line positions as well. Rest of the parameters and constraints have been mentioned ges themselves. in the images themselves.

ON TYPE 2

ITERATION TYPE 2

ing iterations show the different positionsThe of the following all the lines iterations with show respect thetodifferent the position positions of the of the UP all line. theThe lines distance with respect of this to the position of the UP line. The distance of this he origin changes which changes all otherline linefrom positions the origin as well. changes Rest ofwhich the parameters changes alland other constraints line positions have as been well. mentioned Rest of the parameters and constraints have been mentioned ges themselves. in the images themselves.

ITERATION 01

ITERATION 04

ITERATION 02

ITERATION 05

THE

THE ITERATION 03

ITERATION 06

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1.3 Students work, monsoon 3 rd semester 2019, Master of Architecture 1.3.1 Shell geometry derivative by cross referencing points.

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.

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set of points into two equal

e point set into two equals d Set B)

Define sequence 1 - Alternate points of each set to offset radially (Constraint 2)

Offsetby cross radius is a variable distance Figure 1-9 Shell structure genetated referencing points (B Athira 2nd year M.Arch)

individual set to move n X, Y or Z axeses with stance of max half radius of - x/2 (Parameter 1)

equence 2 - 3 point aint 4)

of half radius of base circle - -x/2 to +x/2 in XY plane and/or Z axis (Parameter 2)

06

Form shell geometry (continuous polysurface) with all the arcs

of Set A, Set C and Set ect in sequence to form c

LVING

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Monsoon Semester 2019 2nd year M.Arch

Pseudocode

02

02

03

03

Define sequence 1 - Alternate Split Base set of points into two equal nto a set of Step 1 : Step 2 sequence of each set1 to -offset radially ts - Base Split set Base setsubsets Definepoints Alternate of points into two equal Divide base circle into a set of even number of Define sequence 1 Alternate points of each set to (Constraint 2) Split base point set into two equals points of each set to offset radially subsets points - Base set (Set A and Set B) offset radially (Constraint 2) Split base point set into two equals Offset radius is a variable distance riable radius (Set A and Set B) of individual set to move of half radius of base circle - -x/2 Points variable +x/2 in isXYa plane and/ordistance Z axis et 2x count Iterations together in X, Y or Z axeses with Offsetto radius (Parameter 2) radius of base circle - -x/2 variable distance half radius of of half Points of individual set oftomaxmove base circle x/2 (Parameter 1) to +x/2 in XY plane and/or Z axis together in X, Y or Z axeses with

variable distance of max half radius of base circle - x/2 (Parameter 1)

(Parameter 2)

06

05

05

Iteration 1 Parameter 1 - Points of one set to move together in a direction with variable distance

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06

Iteration 2 Parameter 1 - Points of setB to move together in a direction with variable distance)

variable distance of max half radius of base circle - x/2 (Parameter 1)

04

(Parameter 2)

06

05 05

06

Define set C with same number of

Defining Sequence 2 - 3 point Form shell geometry (con Step 4 arc(Constraint 4) polysurface) with all the Form Sequence shell geometry (continuous Defining 2 - 3 point polysurface) with all the arcs arc(Constraint 4) and Form shell geometry Nth point of Set A, Set C and Set Set C with series points at cenNth of point of Set A, Set C and SetB to connect in sequence to form oints at cenB towith connect inseries sequence to form3 point arc ter of base circle Step of Step of series point arc in an arithemetic3 sequence nce with variable ranging from 0 to 10 m 0 to 10 (Parameter 3)

Step 3 points as number of Define Defining Sequence 2 - as 3 point set C with same number of points set A set A and set B arc(Constraint 4) and set B

ALGORITHMIC THINKING : A PARAMETRIC APPROACH TO PROBLEM SOLVING PARAMETRIC APPROACH TO PROBLEM SOLVING

Iteration 3 Parameter 2 - Offset radius of sequence 2

Iteration 4 Parameter 2 - Offset radius of sequence 2

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1.4 Students work, spring 5th semester 2020, Bachelor of Architecture 1.4.1 Decoding Piet Mondrian Painting through a set of rules.

Narrative 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.

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Horizon

Earth: Blue part in the painting indicates waster, red part indicates the human settelment and the rest of the part indicates roads/ground/empty patches of land covered in the painting.

Landscape with Silhouetted Young Tree. w.karstenschubert.com/news/57/

Earth

The artist has captured a certain area / amount of water, sun, human settelment, 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.

more part of earth in the painting.

Horizon

Birds

Figure 1-10 Narrative (Gelani Khushali 5th year B.Arch) Sun a)PietPietMondrian - Tableau I Clouds Mondrian - Ditch Clouds near Landzicht Farm Horizon Source link -https://www.piet-mondrian.org/tableau-i.jsp Source link - https:// have different areas and are indication of b)Each rectangle www.artlyst.com/news/ piet-mondrian-earlyLandoriginal Land painting. interpretation in referenceLandto the paintings-on-display-atdavid-zwirner-london/

g the sceneries into basic horizontal and low - he stated that he was starting to define the

et of rules.

Human settlement

Water Each rectangle have different areas and are indication of my interpretation in refrence to the original painting.(below)

Sign of INFINITY indicated by removing the boundaries of the painting.

My interpretation : When i see the painting, i see a stricking line that divides the whole rectangle into two parts. It is the on d by a HORIZON. the rectangle horizontally. Hence, i call this divider as HORIZON line. Here i am looking at the painting Piet Mondrian - Apple Tree, Blossoming the horizon as Sky and the part below the horizon as Earth. All the other terminating line further divid i- Source link - https://medium.com/signifier/piet-mondrians-tree-paintings-cef4ccac881 different parts. These parts form up the rest of the scenery that involves sun, cloudes, water, human sett Sky: The sky consists of yellow, black and white colour indicating sun,birds and clouds respectively.

Earth: ht Piet Mondrian - Composition with large red plane, Blue part in the painting indicates waster, red part indicates the human yellow, black, grey and blue. n- Source link - https://www.wikiart.org/en/piet-monsettelment and the rest of the part indicates roads/ground/empty o- drian/all-works#!#filterName:all-paintings-chronologically,resultType:masonry patches of land covered in the painting. not use rectangles of same area in the same ge did Tree.

ing.

Horizon

The artist has captured a certain area / amount of water, sun, human settelment, Khushboo | UA2215 etc in his painting, but extended with a change of vision, he tried to remove the frame. He, in his painting, has given the hint o boundaries from the painting.

Birds

Sun

iet Mondrian - Ditch ear Landzicht Farm

ource link - https:// ww.artlyst.com/news/ iet-mondrian-earlyaintings-on-display-atavid-zwirner-london/

zontal and rting to define the

ossoming om/signifier/piet-mon881

a

Piet Mondrian - Tableau I Source link -https://www.piet-mondrian.org/tableau-i.jsp

Clouds

Clouds

Land

Horizon

Land

Land

Human settlement

Water Each rectangle have different areas and are indication of my interpretation in refrence to the original painting.(below)

b

Sign of INFINITY indicat the painting.

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Spring Semester 2020 Final year B.Arch

Psuedocode

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 4 - Shifting of the sub-divisions Area of the sub-divisions are fixed. Subdivisions of sky cannot shift to earth and vise-versa.

Sub-dividions of sky can be located differently

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 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 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.

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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.

Figure 1-11 Psuedocode illustrations (Gelani Khushali 5th year B.Arch)

ainting through a set ofPainting rules. through a set of rules. ecoding Piet Mondrian

A.

A

STEP 3

STEP 3

A

Shifting of the sub-divisons

Shifting of the sub-divisons

Area of the sub-divisions are fixed. Sub-divisions of sky cannot shift to earth and vise-versa.

Location of the sub-divisions are not fixed.

Shape of the sub-divisions is also not fixed.

Hence, the sub-dividions of sky can be located differently and shape can vary according to the area fixed for sub-divisions in SKY. Similarly the sub-dividions of earth can be located differently and shape can vary according to the area fixed for sub-divisions in EARTH.

Area of the sub-divisions are fixed. Sub-divisions of sky cannot shift to earth and vise-versa.

Location of the sub-divisions are not fixed.

Shape of the sub-divisions is also not fixed.

Hence, the sub-dividions of sky can be located differently and shape can vary according to the area fixed for sub-divisions in SKY. Similarly the sub-dividions of earth can be located differently and shape can vary according to the area fixed for sub-divisions in EARTH.

A

t as shown.)

A+A A+A A+A

A+A

A

A

A

A

A A+A/2 A AA AA A+A/2 A A A+A/2 O A

A

A

A

A A+A/2 A

A

A

A

New shape

A

left to right.

own. It stays fixed

STEP 4

STEP 4

Colours

Colours

Area of coloured rectangles are fixed too but the sizes can be different according to the fixed areas.

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.

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 5

STEP 2 1

4

2

3

5

STEP 5 Infinity

ed into 5 parts. vided into 6 parts.

n constant in both 4 cannot be 2

61

3

4

ange according to

5

New shape

STEP 4

STEP 1

3

Original shape

4

5

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 Sky6will remain intact along with the horizon line and vice-versa.

STEP 5 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.

2 5

STEP 3

STEP 6

Khushboo | UA2215

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Khus

Spring Semester 2020 Final year B.Arch

Iterations

Iteration 1 constant : Sky elements Variable : Earth elements(60%) Iteration 2 constant : Sky elements Variable : Earth elements(40%) Iteration 3 constant : Sky elements Variable : Earth elements(80%) Iteration 4 constant : Earth elements Variable : Earth elements(30%) Iteration 5 constant : Sky elements Variable : Earth elements(40%) Iteration 6 constant : Sky elements Variable : Earth elements(30%)

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BOOTCAMP: Decoding Piet Mondrian Painting through a set rules.

BOOTCAMP: Decoding Piet Mondrian Painting through a set of of rules.

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

ITERATIONS ITERATIONS

Iteration 1

Iteration 4

Iteration 2 Iteration 5

Iteration 3

Iteration 6

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E xe rc i s e 2 : I d e n t i f i c a t i o n o f D e s i g n Va r i a b l e s ( 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.

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.

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Figure 2-1 Chart showing Proximity chart of spaces within 1km radius (.(Sai kiran - 2nd year M.Arch) Site study -Social provisions

4.8.0 SOCIAL PROVISIONS - PROXIMITY CHART Chart showing proximity chart of spaces with in the 1km radius starting from bhau daji museum entrance, mumbai.

PROXIMITY CHART

ius rad 00m <3

QUANTITY OF SPACES EDUCATION HOSPITALS SOCIAL AMENITIES HOTELS

Units: distance (meters)

RESTAURENT & BAR RELIGIOUS SPACES

18

Proximity map is organised in 3 segments based on the radius.

21 1) Below 300m radius 2) 300m-600m radius 3) 600m and above.

50 | Algorithmic thinking studio: Monsoon-2019

5 3

6

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Monsoon Semester 2019 2nd year M.Arch

2.2 Program 2.2.1 Extension to Bhau Daji Lad Museum

Objective 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

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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

a

b

c

d

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Spring Semester 2020 Final year B.Arch

2.2.2 Program Evolution of housing Typology

Objective 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.

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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

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

a

b

c

d

e

f

g

h

i

j

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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.

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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 The Cluster e) Daily activity in plaza during evening

80m

60m

a

Chosen cluster Shared walls House openings towards the internal streets.

Plaza Street Medium height High height Low height b

c

Mostly shorter side of build Height of the buildings arou to shade the plaza.

d

e

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Monsoon Semester 2019 2nd year M.Arch

Built environment - character of space through building element

Example

Student : Saadiya Rawoot

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.

c

oints

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DRIVERS FOR EXPERIMENT 1

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)

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

Proposal

Existing museum

a

1. MORPHOLOGICAL ASPECT- Minimize the extents of the building foot-print

2. SPATIAL ASPECT- Maximizing Field of View

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b

Monsoon Semester 2019 2nd year M.Arch

Built environment - character of space through building element

a

DATA REVIEW

Intensity of people every 5 minutes 1600 1400 1200

1000 800 600

400 200 0

STRETCH 1 STRETCH 2 STRETCH 3 STRETCH 4 STRETCH 5 STRETCH 6 (2 m) (4.5 m) (1.2 m) (2.5 m) (0 m ) (1.8 m) Intensity of people every 5 minutes

b

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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 2 : 4.5 m

Stretch 4 : 2.5 m

Stretch 5 : 3.2 m

Stretch 3 : 1.2 m

Stretch 6 : 1.8 m c

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Spring Semester 2020 Final year B.Arch

Built environment - character of space through building element

Example

Student : Sampreet Dasgupta

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

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Figure 2-7 Identification of Architecture Variables (Sampreet Dasgupta - 4thYear B.Arch)

Interior Facade

subparts

urtyard

building

street

el shape

Manzana Subdivision

Setback

Manzana Part

Chamfer Depth

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Spring Semester 2020 Final year B.Arch

Built environment - character of space through building element

ARCHITECTURAL VARIABLES 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 socioeconomic 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.

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

ES

ACK DISTANCE

master plan was the creation of the structure that had been meticulously ginally, each manzana was to be built with a depth of 20 m and a height of 16 side would measure 113.3 m with a m.

ilt-up sides a recreational green space um amount of sunlight and ventilation in the manzana while simultaneously the entire city in all cardinal directions.

y with an open layout became closed, built up rather than remaining as open es eventually allowed for buildings to , considerably increasing the density of ks today have varying building forms, n of ordinances over time.

113.3m

20m

A R CH I T E CT U R A L VA R I A BL E S

M A N Z A N A D E P T H & S E T B A CK D I S T A N CE 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.

Orig inally, each m anz ana was t o b e b u ilt up o n o nly 2 o r 3 sid es, wit h a dThree ept h sided of 2 0 m and with a hecentral ight opublic f 16 m . Thspace e lenas g tCerda h o f eproposed a ch s i d e manzanas green wo u ld m easu re 11 3.3 m wit h a p rec ise area o f 12, 3 70 sq .m . The set b a c k d is t a n c e v a r ie d f r o m 1 t o 2 m d e p e n d in g o n s t r e e t w id t h

a

THREE SIDED MANZA GREEN SPACE AS CER

The typical blocks initially with an open layout became closed, and the courtyards were built up rather than remaining as open space.

Chang ing o rd inanc es eventu ally allo wed f o r bu ild ing s to g ro w in heig ht and d ep th, co nsid erab ly inc reasing the d ensit y o f the p lan.

A s a r e s u l t , t h e E X P O S U RE o f t h e c o u r t ya r d r e d u c e d c o n s id e r a b l y.

MAN ZANA H EIGH T 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.

Du e to m od if ied/inc reased height of t he m anz ana, the sunlig ht reac hing t he f loo r su rf ac es and int erio r co u rt yard s is very lo w. T he F AR also chang ed d rast ic ally, in o rd er to acco mm od at e the in c r e a s in g p o p u l a t io n .

T his red uc t ion g reat ly af f ec t s t he po pu lat io n esp ec ially d u ring wint er mo nt hs when the sun ang le is qu it e low and rays cannot p e n e t r a t e c e r t a in f a c a d e s a s w e l l a s t h e s t r e e t s .

The image on the far right shows that, roofs receive maximum sunlight whereas it hardly penetrates into the courtyard

b

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Spring Semester 2020 Final year B.Arch

Built environment - character of space through building element

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

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Figure 2-9 Architecture Variables (Sampreet Dasgupta - 4thYear B.Arch) a) Image show shadow cast on to the street b) 45 degree chamfer of Manzana

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b

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Spring Semester 2020 Final year B.Arch

Built environment - character of space through building element

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.

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Figure 2-10 Architecture Variables (Sampreet Dasgupta - 4thYear B.Arch) a) Elevation of selected block showing windows and fenestrations. b) Alternate niches break away from conventional square facade

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Elevation of selected blocks showing windows and fenestrations Elevation of selected blocks showing windows and fenestrations

a

Alternate niches break away from the conventional square facade Alternate niches break away from the conventional square facade

b

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d. In edp.inIn g p i ng

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Spring Semester 2020 Final year B.Arch

Built environment - character of space through building element

UNIT PLAN ANALYSIS 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

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Figure 2-11 Architecture Variables (Sampreet Dasgupta - 4thYear B.Arch) a) Unit plan Analysis

e d

r

r

Entrance

2BHK

Façade Stagger

CENTRAL SHAFT

h

6 WINDOWS

5 WINDOWS

4 WINDOWS

3 WINDOWS

a

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E xe rc i s e 3 : D e s i g n D r i ve r s ( f ) 3.1 Translating qualitative into quantitative aspects

Traditionally, designer use the logic of CAD (computeraided 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.

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.

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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

b

c

d

e

f

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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, depthmap, 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.

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Figure 3-2 Analytical tools a) Solar Radiation Analysis (Source Link : https://knowledge.autodesk.com/akn-aknsiteckeditor-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

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Syntactical Technique

3.2.1 Axial Analysis

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.

Connectivity 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) Integration 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) Depth Map 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)

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

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Syntactical Technique

3.2.2 Centrality Analysis

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.

Degree centrality Degree defines the number of links to a particular Segments Betweenness Centrality Betweenness centrality is number of times a node act as bridge along shortest path between two other nodes.

Closeness Centrality 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.

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

a

b

c

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Syntactical Technique

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.

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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

(b)

(a)

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Environmental Technique

3.2.4 Sunlight Hours Analysis

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.

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

Evaluation Criteria Selection – Ground Exposure (Plaza) Existing Plaza Exposure

Social Gathering is an imp hence they have plazas wi gather and spend time.

Months for analysis : Time chosen for analysis :

Existing big plaza

Existing small plazas Existing Area of plaza (combined) : 308.43m2 Plaza exposure : Small plaza get sunlight of about 97hrs and below. Bigger plaza has 35% plaza with sunlight for 146- 219hrs whereas rest 65% part gets sunlight for 97-24hrs.

FAR : 5.7 POP : 857 Open space : 36% Total built-up area : 64%

Total number of hours : Existing big plaza is gets su part. Whereas small plaza So creating many small pla arrangement of building b communal interaction.

Target Plaza exposure : 50% part get sunlight for 73hrs or le Sunlight should not rise ab FAR : 4.7 to 5.3 POP : around 1200

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Environmental Technique

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.

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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

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Environmental Technique

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.

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Figure 3-8 WindAnalysis 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.

a

b

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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.

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ht of as 35% ereas s.

plaza’s for spending time.

Total number of hours : 244 hours Existing big plaza is gets sunlight for more than 146hrs in its 30% part. Whereas small plazas get sunlight of about 97-73hrs.

Existing big plaza So creating many small plazas rather than one big plaza by arrangement of building blocks to have more shaded plazas for Existing small plazas communal interaction.

Target Figure 3-9 Social relationship (Khushboo Makwana - 4th yearpart B.Arch) Plaza exposure : 50% of ground should a) Gathering in plaza (Social activity) get sunlight for 73hrs or less then that. b) Identifying various types of plaza Sunlight should not rise above 122hrs.

FAR : 4.7 to 5.3 c) Existing Plaza exposure (Criteria) POP : around 1200

Activities

ain plaza

Streets exposed to sun

Criteria Selection – Ground Exposure (Plaza)

Plaza Exposure

mbined) : 308.43m2

b

Social Gathering is an im hence they have plazas gather and spend time.

Months for analysis

Time chosen for analysi

Existing big plaza

Existing small plazas

c

Total number of hours Existing big plaza is gets part. Whereas small pla So creating many small arrangement of buildin communal interaction.

TargetPage - 89 Plaza exposure : 50% p

Spring Semester 2020 Final year B.Arch

Social relationship - Defining criteria for quantification

Example

Student : Gelani Khushali

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.

Different activities in courtyard Living space Gathering pace Children play area Small garden for vegetation Different activities in courtyard Gathering and sitting pace Morning break fast Small garden for vegetation

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Area 8 to 9 sq m 8 to 9 sq m 9 sq m 6 sq m Area 6 to 9 sq m 9 sq m 6 sq m

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

b

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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.

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

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Monsoon Semester 2019 2nd year M.Arch

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.

a

b 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.

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Figure 3-12 Axial line analysis (Tejaswini Walunj - 2nd sem M.Arch ) isovists at 1.5 Over lapping isovists at 5 meters a)Over Bird lapping eye view : Baudaji ladmeters Museum b) Identification of tree species and radius of its foliage c) field of view at various height using isovist

Over isovists at 20 meters lapping isovists atlapping 10 meters

Isovist at 1.5 m 66 MAAD | MONSOON SEMESTER MAAD| |PG181114 MONSOON SEMESTER | PG181114

Isovist at 20 m 70 MAAD| PG181114 | MONSOON SEMESTER | PG181114 MAAD | MONSOON SEMESTER

Over lapping isovists at 15 meters

Isovist at 3 m

68

67 MAAD | MONSOON SEMESTER MAAD| |PG181114 MONSOON SEMESTER | PG181114

Isovist at 15 m 72

c

71 MAAD| PG181114 | MONSOON SEMESTER | PG181114 MAAD | MONSOON SEMESTER

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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.

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

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Hypothesis- Parameter Study and form finding

Example

Student : Sampreet Dasgupta

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

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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

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E xe rc i s e 4 : D e s i g n l i m i t a t i o n 4.1 Building scalability

Aim 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.

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

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4.2 Synthesis using previous study and calculating the given bylaws

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.

FAR | Volume | POP/Ha Comparison 9.00 165811.5 159905.6

8.00

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7.00 618

608

592

586

6.00

602

570

538 485

5.00

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490

480

90733.3

87012.4

88370.7

92722.5

88736.0

92046.1

4.00

3.00

2.6

2.6

2.4

2.3

Iteration 17

Iteration 21

2.4

2.3

2.5

2.4

2.3

2.4

Iteration 47

Iteration 65

Iteration 82

Iteration 90

2.00

1.00

0.00

Iteration 5

Iteration 30 Volume

Page 102

Iteration 38 FAR

Iteration 40

POP/Ha Achieved

POP/Ha Average

Figure 4-2 Comparing Volume/FAR/pop.ha of generated iterations (Sampreet Dasgupta- 5th year students B.Arch)

Facade exposure

Ground exposure

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

Page 103

E xe rc i s e 5 : E vo l u t i o n o f b u i l d fo r m 5.1 Deterministic to probabilistic system designers

Aim 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.

Page 104

Figure 5-1 Comparison of Morphologies for maximum exposure on courtyard and open terraces. (Gelani Khushali5th year students B.Arch)

Page 105

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.

Page 106

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

Page 107

5.3 Mandate setup into Emergence

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.

Page 108

System Logic

Pseudo Code

Parameters

Design Drivers

Desired Solutions Mutation

Constrains

Limitation

Analysis

Evolutionary Computation Iterations

Evaluation

Solutions

Emergence [Fittest Solutions] Page 109

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) 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.

Page 110

Figure 5-3 System Logic.(Mishal Dodia 5 year B. Arch)

SYSTEM

LOGIC

1 - Demarcate the location of

2 - Outdoor activity zones as

3 - Optimizing footprint based

Outdoor Activities along the edge.

repulsion points, to establish

on Field of View study along the

ground footprint.

Activity zones & Isovist from the main Entry.

SYSTEM

L O G I C - MORPHOLOGY

MISHAL | PG180544 | MAAD | SEM - III

a

b

c

Incrementally sloping roof as per the

Extending and projecting roof to

Modulating the roof towards Plaza to

optimum walking gradient.

create canopy for Outdoor Activity

merge it with the Landscape

Zones

MISHAL | PG180544 | MAAD | SEM - III

Page 111

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) 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.

Page 112

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

Page 113

5.6 Analyzing all criteria through multi objective optimization

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

Page 114

Fig 5-1

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

Page 115

5.7 Iteration evaluated using graph theory

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.

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.

Page 116

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

Page 117

Spring Semester 2020 Final year B.Arch

Example

Student : Khushboo Makwana

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.

Experiment 1 (Fittest 9 iteration for Criteria 1 )

A

B

C

Total Open S

Total Built-U

Big Building

Small Buildin

D

E

F

Total numbe

Boundary bl

Centre block

riteria 1 )

G

B

C

H

I Total Open Space (%) Total Built-Up (%) Big Building Facades (%) Small Building Facades (%)

E

Conclusion : The criteria majorly gets affected by number of blocks, heights of buildings and built-up vs. open space areas. (%)IT -I : Built-up area is less in IT-A and also number For e.g.Total : If weOpen look atSpace IT -A and of blocks are less in IT-A than in IT-I, but still IT-A has least ground Total number of blocks exposure because the buildings have higher heights there.

Total Built-Up (%)

F

Big Building Facades (%) Small Building Facades (%)

Page 118

Total number of blocks Boundary blocks height (avg. in m)

Boundary blocks height (avg. in m) Centre blocks height (avg. in m)

Total Built-up Space (%)

C. 32

B. 28

A. 37

POP/Ha : 1367 F.A.R : 5.3

POP/Ha : 1317 F.A.R : 4.8

POP/Ha : 1204 F.A.R : 4.6

Figure 5-9 Analysis showing relationship between criteria and parameters.(Khushboo Makwana 5 year B.Arch)) 44 a)Pie charts showing comparative study of parameters of selected iterations 46 49 b)Iterations with the facade exposure ,FAR and Pop/Ha. 50

tion for Criteria 2 )

Total no.of blocks

D. 7

38

17

C. 32

B. 28

POP/Ha : 1367 F.A.R : 5.3

POP/Ha : 1317 F.A.R : 4.8

G. 43

I. 45

H. 26

POP/Ha : 1317 F.A.R : 5.1

B. 28

Experiment Experiment Experiment 1 (Fittest 1 (Fittest 1POP/Ha (Fittest 9 iteration 9 :iteration 9 iteration for Criteria for Criteria for Criteria 2) 2) 2) 1317 Experiment 1 (Fittest 9 iteration for Criteria 2) 2) 2) F.A.R : 94.8 Experiment Experiment 1 (Fittest 1 (Fittest iteration 9 iteration for Criteria for Criteria E. 42Experiment Experiment 1 (Fittest 9 iteration for Criteria 2 ) F.249 Experiment 1 (Fittest 1 (Fittest 9 iteration 9 iteration for Criteria for Criteria ) 2)

44 46 49 50

Total no.of POP/Ha : 1302 F.A.R : 4.9 blocks

POP/Ha : 1165 F.A.R : 4.4

POP/Ha : 1144 F.A.R : 4.2

Exposure grid: 4m x 4m

POP/Ha : 1208 F.A.R : 4.6Total Built-up Space (%)

POP/Ha : 1144 F.A.R : 4.2

t 1 (Fittest 9 iteration for Criteria 2 )

4

F. 49

E. 42

POP/Ha : 1338 F.A.R : 5.0

Total Open Space (%)

C. 32

POP/Ha : 1367 F.A.R : 5.3

Total Open Space (%)

Total Built-up Space (%) Khushboo UA2215

Exposure grid: 4m x 4m

POP/Ha : 1208 F.A.R : 4.6

44 46 49 50

Total no.of blocks

A. 37 A. 37 A. 37 A. 37 POP/Ha POP/Ha :37 POP/Ha 1204 : 1204 : 1204 E. 42 A. A. 37 A. 37 F.A.R F.A.R : 4.6 F.A.R : 4.6 : 4.6 POP/Ha :37 1204 A. A. 37 POP/Ha POP/Ha : 1204 : 1204 POP/Ha : 1144 H. 26 POP/Ha : POP/Ha 1204 F.A.RPOP/Ha : 4.6 1204 : 1204 F.A.R : 4.2 F.A.R F.A.R : 4.6 : 4.6 POP/Ha ::1165 F.A.RF.A.R : 4.6F.A.R 4.6: 4.6 F.A.R ::4.4

B. 28 B. 28 B. 28 B. 28 POP/Ha POP/Ha : B. POP/Ha 1317 : 1317 : 1317 F. 49 B. 28 28 B. 28 F.A.R : 4.8 : 4.8 : 4.8 POP/Ha : F.A.R 1317 B. 28 B. 28 POP/Ha POP/Ha : 1317 : 1317 POP/Ha : 1208 I.F.A.R 45 POP/Ha : POP/Ha 1317 F.A.RPOP/Ha : 4.8 1317 : 1317 F.A.R : 4.6 F.A.R F.A.R : 4.8 : 4.8 POP/Ha :: 1302 F.A.RF.A.R : 4.8F.A.R 4.8: 4.8 F.A.R :: 4.9

Exposure grid:

4m x 4m C. 32 C. 32 C. 32 C. 32 POP/Ha POP/Ha : C. POP/Ha 1367 : 1367 : 1367 C. 32 32 C. 32 F.A.R F.A.R : 5.3 : 5.3 : 5.3 POP/Ha : F.A.R 1367 C. 32 C. 32 POP/Ha POP/Ha : 1367 : 1367

POP/Ha : POP/Ha 1367 F.A.RPOP/Ha : 5.3 : 1367 : 1367 F.A.R F.A.R : 5.3 : 5.3 F.A.RF.A.R : 5.3F.A.R : 5.3: 5.3 Khushboo UA2215

TotalTotal Open Total OpenOpen SpaceSpace (%)Space (%)Open (%) Total Open Total Total Open Total Open SpaceSpace (%)Space Total Total Open (%)Open (%) SpaceSpace (%)Space (%) (%) TotalTotal Built-up Total Built-up Built-up SpaceTotal Space (%)Total Space (%)Built-up (%) Total Built-up Built-up Total Built-up SpaceTotal (%)Total Built-up Space Space (%)Built-up (%) SpaceSpace (%)Space (%) (%)

44 44 44 46 46 46 44 44 44 49 49 46 44 49 46 44 46 44 50 50 49 50 46 49 46 49 46 50 Total TotalTotal no.of no.of no.of 49 50 49 50 49 50 blocks blocks blocks Total no.of 50 no.of 50 TotalTotal no.of

Total no.of blocks Total Total no.ofno.of blocks blocks blocks

H. 26 D. 7D. 7D. 7 D. 7 POP/Ha POP/Ha :7D. POP/Ha 1338 : 1338 POP/Ha : 1165 D. 7: 1338 F.A.R : 4.4 D. 7F.A.R F.A.R : 5.0 F.A.R : 5.0 : 5.0 POP/Ha : 1338 D. 7 D. 7 POP/Ha POP/Ha : 1338 : 1338

I. 45 E. 42 E. 42 E. 42 E. 42 POP/Ha POP/Ha : E. POP/Ha 1144 : 1144 : 1144 POP/Ha : 1302 E. 42 42 F.A.R : 4.9 E. 42 F.A.R F.A.R : 4.2 F.A.R : 4.2 : 4.2 POP/Ha : 1144 E. 42 E. 42 POP/Ha POP/Ha : 1144 : 1144

F. 49F. 49 F. 49 F. 49F. POP/Ha POP/Ha : F. POP/Ha 1208 : 1208 : 1208 49 49 F. 49POP/Ha F.A.R F.A.R F.A.R : 4.6 : 4.6 POP/Ha : POP/Ha 1208 F.: 4.6 49 F. 49 : 1208 : 1208

G. 43 G. 43 G. 43 G. 43 POP/Ha POP/Ha POP/Ha 1317 : 1317 : 1317 G. :43 G. 43 G. F.A.R43 F.A.R : 5.1 F.A.R : 5.1 : 5.1 POP/Ha :43 1317 G. G. 43 POP/Ha POP/Ha : 1317 : 1317

H. 26 H. 26 H. 26 H. 26 POP/Ha POP/Ha POP/Ha 1165 : 1165 : 1165 H. :26 H. 26 H. F.A.R26 F.A.R : 4.4 F.A.R : 4.4 : 4.4 POP/Ha :26 1165 H. H. 26 POP/Ha POP/Ha : 1165 : 1165

I. 45I. 45I. 45 I. 45POP/Ha POP/Ha : POP/Ha : 1302 : 1302 I. 45 I.1302 45 I. 45POP/Ha F.A.R F.A.R F.A.R : 4.9 : 4.9 POP/Ha : POP/Ha I.: 4.9 45 I.1302 45 : 1302 : 1302

POP/Ha :POP/Ha 1338 F.A.RPOP/Ha : 5.0 : 1338 : 1338 F.A.R F.A.R : 5.0 : 5.0 F.A.RF.A.R : 5.0F.A.R : 5.0: 5.0

POP/Ha : POP/Ha 1317 F.A.RPOP/Ha : 5.1 : 1317 : 1317 F.A.R F.A.R : 5.1 : 5.1 F.A.RF.A.R : 5.1F.A.R : 5.1: 5.1

POP/Ha : POP/Ha 1144 F.A.RPOP/Ha : 4.2 : 1144 : 1144 F.A.R F.A.R : 4.2 : 4.2 F.A.RF.A.R : 4.2F.A.R : 4.2: 4.2

POP/Ha : POP/Ha 1165 F.A.RPOP/Ha : 4.4 : 1165 : 1165 F.A.R F.A.R : 4.4 : 4.4 F.A.RF.A.R : 4.4F.A.R : 4.4: 4.4

blocks blocks Exposure Exposure grid: Exposure grid: grid: 4m x 4m 4m xgrid: 4m 4m x 4m Exposure Exposure Exposure grid: grid: 4m x 4m Exposure 4m xgrid: 4m 4m xgrid: 4m grid: Exposure Exposure 4m x 4m 4m x 4m 4m x 4m

POP/Ha : POP/Ha 1208 F.A.RPOP/Ha : 4.6 : 1208 : 1208 F.A.R F.A.R : 4.6 : 4.6 Khushboo UA2215 F.A.RF.A.R : 4.6F.A.R : 4.6: 4.6

POP/Ha : POP/Ha 1302 F.A.RPOP/Ha : 4.9 : 1302 : 1302 F.A.R F.A.R : 4.9 : 4.9 F.A.RF.A.R : 4.9F.A.R : 4.9: 4.9

Khushboo Khushboo Khushboo UA2215 UA2215 UA2215 Khushboo UA2215 Khushboo Khushboo UA2215 UA2215 Khushboo UA2215 Khushboo Khushboo UA2215 UA2215

Page 119

E xe rc i s e 6 : D e s i g n Pro p o s a l

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.

Page 120

PAGE

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

ENTRY 03

68 ALGORITHMIC THINKING ALGORITHMIC THINKING

Fig 6-1 01 ENTRY

Fig 6-2

PAGE 69

Page 121

Monsoon Semester 2019 2nd year M.Arch

Design Proposal Example The student proposal shows existing museum palladian create minimal architecture openings for more flexibility both internally and externally.

Student : Sai kiran

Breakaway from architecture to with optimized of surface area

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

Page 122

Fig 6-4

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

Page 123

Design Proposal Example Student : Sampreet Dasgupta 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.

Figure 6-8 detail unit plan Figure 6-9 Arrangement of unit plans Figure 6-10 Render shows the

Fig 6-8

Page 124

Fig 6-9

Fig 6-10

Page 125

Students work, spring 5th semester 2020, Bachelor of Architecture KOWLOON WALLED CITY HONG KONG

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.

Page 126

Student : Astha Shah

Page 127

Spring Semester 2020 Final year B.Arch

Defining Parameters, rules and Constrains.

Page 128

Pseudocode

Page 129

Spring Semester 2020 Final year B.Arch

Evaluation Criteria’s and targets.

Page 130

Page 131

Spring Semester 2020 Final year B.Arch

Evolution of Build form

Page 132

Page 133

Students work, monsoon 3 rd semester 2019, Master of Architecture Extension to Bhau Daji Lad Museum

Student : Mishal Dodia

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 RATIO BETWEEN BUILT AND UNBUILT MISSSION cultural institutions, with strong links to itsSTATEMENT sister museum, the V&A in London.

To serve the community as an institution dedicated to excellence in cultural education through exhibitions and different visual and At the heart of the new wing will be a permanent gallery to intellectual media.

showcase contemporary Mumbai, focusing on important milestones the city’s especially development and highlighting its To engage theincommunity, children. cultural achievements, as well as temporary exhibition To promote a greater appreciation of Mumbai’s cultural and space to international standards capable artistic, of taking largeeconomic history and development. scale touring exhibitions.

The new galleries, education and social facilities will To promote cross cultural awareness at give us valuable extraunderstanding space and and alsocultural the opportunity toall levels rethink the landscaping of the whole site, in this, a rare gr een pocket of south Mumbai.

UNBUILT

BUILT

BUILT

nical gardens and the zoo

Page 134

UNBUILT

City Museum is the third oldest museum in India and the oldest in the city MISHAL | PG180544 | MAAD | SEM - III

CONTEXT

To serv in cultu intellect

To enga

To prom econom

To prom levels

VIRMATAdelightful JIJABAI UDYAN CAMPUS setting in the lush surroundings of the city’s botanical gardens and the zoo

next door.

Page 135

City Mu the city

Monsoon Semester 2019 2nd year M.Arch

INTERVENTION IDEAS

Intervention 1 landscape as prominent site feature needs to be preserved. and need to reconnect the garden and museum. need to conserve the usability of site as an open accessible public space. need to establish relationship with the existing built and other site features as a part of master plan. to use this intervention as an opportunity to weave the existing site morphology.

Intervention 2 to enliven the urban edge by engaging the passerby with the museum, and make it a part of their everyday. to add to the character of street-scape. Distinct Outdoor space quality of Inner plaza and outer edge. to make building porous and physically accessible from multiple breakout points.

Intervention 3 Maximum use of controlled Daylight for galleries and exhibition spaces.

The required Scale and ambiance for the specific nature of exhibition will be achieved by modulating the roof.

Strategy to maximize the floor area for free standing exhibits and wall area for gallery spaces.

Page 136

NTION

gy to respond e a series of ities.

such that the an landscaped n existing and

Isolated Superblock typology

Well integrated Perimeter block typology

Disconnection | Pockets of spaces

Continuity | Alcoves of spaces

Intervention 1 MISHAL | PG180544 | MAAD | SEM - III

2

Building as a modulated Landscape with accessible green roof. Roof-scape to merge with its surrounding.

JUXTAPOSE IN RELATION TO EXISTING

MODULATED GREEN ROOF

New wing connected to the old to provide a continuum to the sequence of exhibition.

+

ACCESSIBLE ROOF & PLAZA AS INTER PHASE

FRAGMENTS ORIENTED TO CAPTURE DAYLIGNT FROM A SINGULAR LIGHT SOURCE.

=

MODULATING ROOF TO MERGE WITH LANDSCAPE

OUTDOOR SPACE QUALITY & INTERIOR SPACES

CONTINOUS ROOF WITH PROTUDING FRAGMENTS MISHAL | PG180544 | MAAD | SEM - III

Intervention 2

Intervention 3 MISHAL | PG180544 | MAAD | SEM - III

Page 137

Monsoon Semester 2019 2nd year M.Arch

Design Experiment 1

INTRODUCTION The exercise intends to generate a set of possible design iterations by running a series of experiments, using the information and conditions formulated in the previous exercise.

Based on the intervention ideas, the sequence of experiments and the targets to be achieved in each experiments are prioritized. The relevant drivers, strategy, targets and criteria are selected from the pool of information collected in previous exercise and a precise setup is created to run the experiment.

The pseudocode is prepared, that defines the step by step procedure to generate a definition with certain relationship between parameters and criteria.

The parameters and criteria for each experiments are identified such that to create a conflicting relationship to determine the highly optimized design iterations at the end of the experiments.

Further the design is developed by combining the most optimal iteration of each experiment and a final design proposal is formulated.

Page 138

STRATEGY

1 GENERATE FOOTPRINT Generate a base footprint considering site constraints and edge conditions. Extrusion and modulation of roof in the range of accessible slope gradient.

2 DERIVE SPATIAL FRAGMENTS Defining of space layout within the derived footprint and volume, based on the data abstracted from syntactical analysis.

3 FACADE & ROOF MODULATION

Further modulation of roof profile and space fragments to capture optimal daylight. Deriving facade articulation in response to the climatic condition and lighting requirements.

MISHAL | PG180544 | MAAD | SEM - III

Page 139

Monsoon Semester 2019 2nd year M.Arch

SYSTEM

LOGIC

1 - Demarcate the location of

2 - Outdoor activity zones as

3 - Optimizing footprint based

Outdoor Activities along the edge.

repulsion points, to establish

on Field of View study along the

ground footprint.

Activity zones & Isovist from the main Entry.

CRITERIA 40% MISHAL | PG180544 | MAAD | SEM - III

40%

20% more than 3500 sqm

de ca Fa ild ing Bu

pe

ca

t-s ree St

1 - Maximize Building Footprint

Adjacent activity

area (ground cover) (MORPHOLOGICAL)

3 - To achieve the visual continuity between activity points.

(SPATIAL)

2 - Maximize Visual exposure

a

of the plaza & Museum activities from Main entrance of the campus.

(SPATIAL)

tangential projection towards adjacent activity

(62 degree-a) / 2 MISHAL | PG180544 | MAAD | SEM - III

Page 140

PARAMETERS random shuffle of activity location along the defined set of points to find the appropriate condition with respect to criteria. range : Random Criteria : 3 - Field of View

01

21

Control the boundary condition of building footprint by changing the radius of Tangent Arcs connecting different activities

02

along the edge. range : Random Criteria : 3 - Field of View 1 - Area of Footprint

MISHAL | PG180544 | MAAD | SEM - III

Diameter of the plaza is variable to control the Footprint area, and its visual exposure from main entrance.

03

Range : 18 - 28 m.

Criteria : 1 - Area of Footprint 2 - Visual exposure of Plaza

The Set of Activity Locations can be Displaced radially in an inverse direction from each other.

04

Range : 0 - 6 m.

Criteria : 3 - Field of View 1 - Area of Footprint

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Monsoon Semester 2019 2nd year M.Arch

PSUEDOCODE

1

2

3

Offset the site boundary

Set of points are demarcated along the line which indicates the location of outdoor activity areas along the edge.

Set of activities of varying magnitude are assigned to respective set of locations which are to be shuffled within that constraint

MISHAL | PG180544 | MAAD | SEM - III

4

5

6

Tangent arcs are developed connecting each activity zones in sequence, to generate outer

Building footprint is restricted based on clear field of view from the main entrance.

Generate field of view from each activity zone orienting towards the adjacent zones.

boundary of building footprint.

Inner boundary as predefined Plaza.

Manipulate the outer boundary of building footprint based on the weighted criteria assigned to the field of view.

MISHAL | PG180544 | MAAD | SEM - III

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eld of View

Street scape (max.40%) : 30%

ITERATIONS 01

Field of View 1. Street scape (max.40%) : 30% 3. Bldg. Facade (max.20%) : 12%

Area of Footprint : 4000 sqm Visual exposure of Plaza area of isovist : 15000 sqm Random Shuffle of activity radius of boundary arc Depth of outdoor activity Visual exposure of plaza Random Shuffle of activity

ITERATIONS 03

Field of View 1. Street-scape (max.40%) : 33%

01 02

Field FieldofofView View

3. Bldg. Facade (max.20%) : 16% 1.1.Street Streetscape scape(max.40%) (max.40%): 30% : 32% 2.2.Adj. Adj.Activity Activity(max.40%) (max.40%): 32% : 29%

Bldg. Facade (max.20%) : 12%

3.3.Bldg.

Bldg.Facade Facade(max.20%) (max.20%): 12% : 15%

Visual exposure of Plaza Area AreaofofFootprint Footprint: 4000 : 3600sqm sqm

sual exposure of Plaza

Visual VisualShuffle exposure exposure ofofPlaza Plaza Random of activity

ea of isovist : 15000 sqm

area areaofofisovist isovist: 15000 : 17000sqm sqm

area of isovist : 15000 sqm

radius of boundary arc

ndom Shuffle of activity

Random Shuffle ofof activity Random Shuffle activity Depth of outdoor activity

dius of boundary arc

radius radius ofof boundary boundary arc arc Visual exposure of plaza

pth of outdoor activity

Depth Depth ofof outdoor outdoor activity activity

sual exposure of plaza

Visual Visual exposure exposure ofof plaza plaza

ndom Shuffle of activity

Random Shuffle of activity

03 04

Field FieldofofView View 1.1.Street-scape Street scape(max.40%) (max.40%): 33% : 29%

Adj. Activity (max.40%) : 35%

2.2.Adj. Adj.Activity Activity(max.40%) (max.40%): 35% : 25%

Bldg. Facade (max.20%) : 16%

3.3.Bldg.

Bldg.Facade Facade(max.20%) (max.20%): 16% : 10%

rea of Footprint : 3900 sqm

Area AreaofofFootprint Footprint: 3900 : 4300sqm sqm

sual exposure of Plaza

Visual Visualexposure exposureofofPlaza Plaza

ea of isovist : 15000 sqm

area areaofofisovist isovist: 15000 : 13000sqm sqm

ndom Shuffle of activity

Random Random Shuffle Shuffle ofof activity activity

dius of boundary arc

02

Area of Footprint : 3900 sqm

rea of Footprint : 4000 sqm

Street-scape (max.40%) : 33%

04

2. Adj. Activity (max.40%) : 35%

Adj. Activity (max.40%) : 32%

eld of View

02

2. Adj. Activity (max.40%) : 32%

04

radius radius ofof boundary boundary arc arc

pth of outdoor activity

Depth Depth ofof outdoor outdoor activity activity

sual exposure of plaza

Visual Visual exposure exposure ofof plaza plaza

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Monsoon Semester 2019 2nd year M.Arch

Design Experiment 2

SPATIAL CONFIGURATION

1) Define an optimized circulation loop along the inner perimeter of the building footprint.

2) Spatial hierarchy based on the functional relationship between different programs.

3) Spatial and volumetric disposition based on the nature and type of exhibits in the space.

- Voluminous space with more floor space, abundant daylight & outside exposure for large free standing exhibits.

- Outdoor display amidst the open landscape for robust sculptural exhibits.

- Linear space with maximum wall display area for Paintings, maps, Coins or other small exhibits.

a

b

c Section : a

Section : b

G.F. Plan

Section : c

N MISHAL | PG180544 | MAAD | SEM - III

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SPACE

PLANNING

01

02

CRITERIA Visual Connectivity between Indoor and outdoor Activity.

LAYOUT

CONSTRAINTS Footprint area and profile of ground floor.

03

PARAMETERS Changing of outdoor activity location

ITERATIONS MISHAL | PG180544 | MAAD | SEM - III

MISHAL | PG180544 | MAAD | SEM - III

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Monsoon Semester 2019 2nd year M.Arch

Design Experiment 3 Building envelop 1) Identifying points to modulate roof to create shade through overhangs.

2) To get maximum area of wall Display, by avoiding openings on side.

3) Introduce light pockets within the footprint to maximize the use of natural light.

CRITERIA

CONSTRAINTS

IDENTIF

Number o

1:6 - 1:10

the Variab

relation

1 - Achieve maximum building height with Least slope gradient.

(MORPHOLOGICAL)

Generate high

through a serie

2 - Utilize rain run-off water from modulated roof & collect it as Water feature in central plaza.

(CLIMATIC)

Number of Control points along the footprint profile to be manipulated to generate morphology.

1 - Walkab Gradient

PARAMETERS min. 2m

3 - Maximum Usable floor area with more than 2 m. Headroom.

(MORPHOLOGICAL)

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Number of Control points Incremental Height of the control points.

Roof Curvature along the shorter width.

Slope.

2 - Maxim

with minim

3 - Collec

SYSTEM

L O G I C - MORPHOLOGY

a

b

c

Incrementally sloping roof as per the

Extending and projecting roof to

Modulating the roof towards Plaza to

optimum walking gradient.

create canopy for Outdoor Activity

merge it with the Landscape

Zones

MISHAL | PG180544 | MAAD | SEM - III

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Monsoon Semester 2019 2nd year M.Arch

STRUCTURE

1

2

Lattice exoskeleton of Steel tubular sections as a primary facade structure.

GFRC panels & diffused glazing as an infill to create a dynamic facated facade.

MISHAL | PG180544 | MAAD | SEM - III

3

4

Lattice exoskeleton further continues to form the primary roof structure.

Skylights are added and green roofscape is created to merge with landscape.

MISHAL | PG180544 | MAAD | SEM - III

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4.3.7 S T R U C T U R A L

SYSTEM

Sky li roo ghts a fsc r ape e add lan ed dsc is c and ape rea g ted . to m reen erg ew

ith

Lat tice to f e orm xosk ele the t prim on fu rth ary roo er co n f st ruc tinues tur e.

GF RC p infi ll to anels & cre ate diffus e ad yna d gla zin mic fac g as a ete d fa n cad e.

Lat tice sec exo tion s s a keleto sa n prim of S tee ary l tu fac ade bular stru ctu re.

99

MISHAL | PG180544 | MAAD | SEM - III

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Monsoon Semester 2019 2nd year M.Arch

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Relationship of outdoor activities with roof & facade.

MISHAL | PG180544 | MAAD | SE

Inside - Outside relationship.

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Monsoon Semester 2019 2nd year M.Arch

CONCLUSION & FURTHER DEVELOPMENTS

Before conducting the final experiments it becomes necessary to attempt the series of smaller definitions to understand the relationship between the rules and definition. This helps to further refine the pseudocode.

There has to be certain amount of freedom within the conditional framework, to enable the system to generate enough possibilities and iterations. The highly deterministic framework gives the most obvious solution, and which cannot be evaluated for its optimization in the system.

There is need to identify the most dominant parameter, which is conditioned by more than one criteria, to create a contradicting evaluation outcomes. This allows system to identify the most balanced solution amongst the defined criteria, to optimize and achieve the fittest iteration.

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BIBLIOGRAPHY

Schumacher, K. (2012) The autopoiesis of architecture Vol-II, A John Wiley & Sons, Ltd., Publication, 2012.

Zoa Li, Brief analysis of spatial constitution and functional organization of museum; A case study on museums in Hefei City.

Abdulmalik Abdulmawla, Decodings-paces Toolbox for Grasshopper Kolarevic, B. (2014) ‘Computing the Performative’, in Oxman, R. and Oxman, R. (ed.) Theories of the Digital in Architecture, Abingdon and New York: Routledge.

Leitão, A., Castelo Branco, R. and Cardoso, C. (2017) ‘Algorithmic-Based Analysis - Design and Analysis in a Multi Back-end Generative Tool’,. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi’an Jiaotong-Liverpool University, Suzhou, China, 137146 Hensel, M. (2013) Performance-Oriented Architecture: Rethinking Architectural Design and the Built Environment, Wiley.

Renata, Al. MAY (2017) Integrated Algorithmic Design UID/CEC/50021/2013 Terzidis, K. (2006) Algorithmic Architecture, Oxon and New York: Architectural Press.

Weronika, D. 2014 Space syntax analysis – methodology of understanding the space Nourian, P., Rezvani , S., Sariyildiz, S. (2013). A Syntactic Design Methodology . Proceedings of 9th Space Syntax Symposium.

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Varoudis T. 2017 Visibility, accessibility and beyond Next generation visibility graph analysis\ Rashid M,Kampschroer K, Wineman J, Zimring C (2006) Spatial layout and face-to-face interaction in offices - A study of the mechanisms of spatial effects on face-to-face interaction, Environment and Planning B Planning and Design · November 2006, DOI: 10.1068/b31123 · Source: RePEc Mumbai city museum, north wing design competition, U.R.L : www.malcolmreading.co.uk ESUM Urban Sensing Handbook 2017, Component, Assembly and Operational Guide: Sensor backpack & 360° Videos. http://esum.arch.ethz.ch/ Centrality U.R.L https://en.wikipedia.org/wiki/Centrality Mumai Development Plan, URL : https://portal.mcgm.gov.in Spatial Accessibility & Human Behaviour - Designing places for People, Space Syntax - Christchurch (2013).

URL: http: // www. spacesyntax. com/ Design Tech - Technology for designing the future URL:https://www.designtechsys.com/articles/parametricmodelling Michael J.Ostwald, Michael J.Dawes (2018) ‘Isovists: Spatio-Visual Mathematics in Architecture.

URL:https://link.springer.com/ McElhinney,S.(2018), ‘Isovist_2.2: a basic user guide’, v1.4 URL: https://isovists.org/user_guide/

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I m a g e c r e d i t - Sai kiran - M. Arch 2nd year