ADAPTIVE DESIGN A Generative Energy Efficient Design Approach | MSc Thesis PBaptista

ADAPTIVE DESIGN A Generative Energy Efficient Design Approach

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Paula Baptista Pontifical Catholic University of Paraná

Professional Diploma in Architecture and Urbanism (2009)

Submitted to the Department of Architecture at Oxford Brookes University in partial fulfillment of the requirement for the Degree of

Master of Science in Sustainable Building: Performance and Design (2012)

This thesis is licensed under a Creative Commons Attribution-NonCommercial- ShareAlike 3.0 Unported License.


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This thesis is licensed under a Creative Commons Attribution-NonCommercial- ShareAlike 3.0 Unported License.

This thesis is being submitted to the Department of Architecture at Oxford Brookes University in partial fulfilment of the requirement for the Degree of

Master of Science in Sustainable Building: Performance and Design.

This thesis is the result of my own independent work/investigation, except where otherwise stated.

Signed............................................................................... Date.............................................. Paula Baptista Borges 28th September 2012

I hereby give consent for my thesis, if accepted by Oxford Brookes University, to be made available to others under the Creative Commons Attribution - NonCommercial - ShareAlike 3.0 Unported License.

The licensor permits others to copy, distribute, display, and perform only unaltered copies of the work and distribute derivative works only under a licence identical to the one that governs the licensor's work. In return, licensees must give the original author credit. Licencees may not use the work for commercial

purposes without the licensor’s permission. More information about this licence at: http://creativecommons.org/licenses/by-nc-sa/3.0/legalcode

Signed............................................................................... Date.............................................. Paula Baptista Borges 28th September 2012


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Submitted to the Department of Architecture at Oxford Brookes University in partial fulfillment of the requirement for the Degree of

Master of Science in Sustainable Building: Performance and Design

ABSTRACT A design paradigm for reaching sustainable solutions that respond to the ever morphing quality of the natural environment and the inert materiality of the built environment has been gaining momentum within the architectural mainstream. In order for these two factors to perform with greater efficiently and in alliance with one another, an alternative approach is being explored to improve the synergy between them. This should allow flexibility for architects to merge environmental design solutions with current and emerging technology and aesthetically complex design.

This thesis will introduce and examine if a design approach called ‘adaptive’, applied via a generative system, can result in the improvement of energy efficient design. The term ‘adaptive’ has a dual utilization in this study. The first use refers to a generative design evolution which adapts according to environmental design parameters. The second use refers to the real-time physical adaptation of the design to the actual surrounding environment based on the previously set parameters.

The adaptive design approach analyses and evaluates if the application of a generative design system can result in the improvement of energy efficiency at the early design phase. The goal is to explore if with the use of graphical algorithm editors and object-oriented programming, designers can be empowered by a more intuitive approach for designing built environments that integrate technology following environmental protocols; ultimately fostering a symbiotic relationship between the natural and built environments. The approach is demonstrated by a case study developed via inter-disciplinary collaboration. The objective of the case study is to demonstrate the adaptive approach’s validity and that it can be realized; in this case, for the development of an optimized design and the creation of a real-time environment-based adaptable prototype with enhanced solar-capture performance.

Thesis supervisor: Nicholas Walliman Title: PhD., Senior Lecturer and Research Associate at the

Oxford Institute for Sustainable Development - Technology Department

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Matter, looked at as an undivided whole, must be a flux

rather than a thing. In this we were preparing the way

for reconciliation between the inert and the living.

Henri-Louis Bergson, 1911

Wireframe by Mark Kelso, 2012

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ACKNOWLEDGMENTS

This thesis would not be possible without the invaluable contribution

of many people.

I am deeply thankful for my supervisor, Dr. Nicholas Walliman for all

his insight and positive support.

I would like to acknowledge the Institute of Advanced Architecture of

Catalonia and the Fab Lab Barcelona team for the amazing summer

workshop which allowed for the material realization of experimental

theories. I would like to thank the whole team of participants for the

great work developed; most specially the computational experts Luis

Fraguada, Guillem Camprodon and Alex Posada; the fabrication

experts Jordi Portell and Anastasia Pistofido; our Tutors Areti

Markopoulou, Tomas Diez and Rodrigo Rubio; the MAA Graduate

Teaching Assistants Emily Sato and Theodoris Grousopoulos; and

workshop team members who significantly made a difference in the

computational aspect of the project such as Guido Hermans and Aline

Vergauwen, as well as in the structure development and fabrication

such as Pedram Seddighzadeh, Jordi Vinyals and Marc Subirana. I

would also like to thank the people that believe in the open source

philosophy, such as Scott Davidson and David Rutten, for developing

and making available the software, plugins and add-ons as well as the

on-line help and tutorials which proved essential for the

development of this work.

I would like to dedicate this thesis to Malu for her support, faith and

persistent encouragement in the pursuit of my dreams; to Diogo for

keeping me levelled with perspective; and to Alex for his love and

caring presence through this all.

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TABLE OF CONTENTS

ACKNOWLEDGMENTS .................................................................................................................................. ii TABLE OF FIGURES ....................................................................................................................................... iv 1. INTRODUCTION ............................................................................................................................. 1 1.1. Research Aims and Methods .......................................................................................................... 3 2. DEFINITIONS .................................................................................................................................. 5 2.1. Generative Design .......................................................................................................................... 5 2.1.1. Definition of Generative Design ..................................................................................................... 5 2.1.2. Generative Design Approach ......................................................................................................... 6 2.1.3. Generative Design Systems ............................................................................................................ 6 2.1.4. Generative Design Techniques ....................................................................................................... 8 2.1.5. Generative Design Examples ........................................................................................................ 10 2.2. Energy Efficient Design ................................................................................................................. 11 2.2.1. Definition of Energy Efficiency ..................................................................................................... 11 2.2.2. Energy Efficiency and Sustainable Development ......................................................................... 11 2.2.3. Energy Efficient Design Orientation Systems ............................................................................... 13 2.2.4. Energy Efficient Design Example .................................................................................................. 14 2.3. Generative Energy Efficient Design .............................................................................................. 15 2.3.1. Definition of Generative Energy Efficient Design ......................................................................... 15 2.3.2. Generative Energy Efficient Design Example ............................................................................... 16 3. ADAPTIVE DESIGN: A Generative Energy Efficient Design Approach ......................................... 17 3.1. Definition of Adaptive Design ...................................................................................................... 18 3.2. Adaptive Form and Performance ................................................................................................. 19 3.2.1. Adaptive Form: Morphogenetic Evolution ................................................................................... 20 3.2.2. Adaptive Performance: Symbiotic Homeostasis .......................................................................... 21 3.3. Adaptive Design Approach ........................................................................................................... 22 3.3.1. Prerequisites for Utilizing the Adaptive Design Approach ........................................................... 22 3.3.2. Adaptive Design Phases ............................................................................................................... 24 3.3.3. Potential Benefits of the Adaptive Design Approach ................................................................... 26 3.4. The Role of the Architect ............................................................................................................. 27 4. ADAPTIVE DESIGN PARADIGM: Case Study ................................................................................ 29 4.1.1. Case Study Approach ................................................................................................................... 30 4.2. Case Study Background ................................................................................................................ 33 4.2.1. Case Study Location and Solar Data Brief .................................................................................... 33 4.2.2. Software Interface, Computing Platform and Materials .............................................................. 35 4.3. Case Study Profile ........................................................................................................................ 39 4.3.1. Seed Phase ................................................................................................................................... 39 4.3.2. Genotype Phase ........................................................................................................................... 40 4.3.3. Phenotype Phase.......................................................................................................................... 41 4.3.4. Embryogene Phase ....................................................................................................................... 41 4.3.5. Synthesis Phase ............................................................................................................................ 42 4.4. Prototype Testing ......................................................................................................................... 44 4.5. Observed Results.......................................................................................................................... 45 5. CONCLUSIONS .............................................................................................................................. 46 5.1. Further work ................................................................................................................................ 50 CITATIONS AND BIBLIOGRAPHY ................................................................................................................. 52 APPENDIX ................................................................................................................................................... 56 NOTE ON COPYRIGHT AND PERMISSIONS .................................................................................................. 76

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TABLE OF FIGURES

Figure 1 and 2 - Radiolaria . ........................................................................................................................ 5 Figure 3 - One of Durand’s generative pattern studies in Précis des Lecons d’Architecture ...................... 6 Figure 4 – Upside down view of one of Gaudi’s suspended structural models........................................... 7 Figure 5 – Hand drawn evolution drawing by William Latham, 1985 ......................................................... 7 Figure 6 - Conus textile exhibits a cellular automaton pattern on its shell. ................................................ 8 Figure 7 - Rule 30 is of special interest because it is chaotic ....................................................................... 8 Figure 8 – Examples of plant like structures generated by L-systems; image via Joost Rekveld. ................ 8 Figure 9 – Voronoi diagram by Ivan Delgado. ............................................................................................. 9 Figure 10 – The Golden Ratio is a rudimentary fractal.. .............................................................................. 9 Figure 11 – Form finding development using shape grammar via mesh based system. ............................. 9 Figure 12 - Frei Otto, Stuttgart Train Station.. ........................................................................................... 10 Figure 13 – Preliminary urban planning analysis sequence using voronoi diagram technique................. 10 Figures 14, 15, 16 and 17 – a multi-scalar analysis and detailing at the regional level ............................ 12 Figure 18 and 19 – Multi-scalar, climatic analysis and detailing at the building level............................... 12 Figure 20 – Anatomy of the City Protocol. ................................................................................................ 13 Figure 21 and 22 –Fondazione Renzo Piano. ............................................................................................. 14 Figure 23 – Media TIC; photos author’s own. ........................................................................................... 16 Figure 24 – Detail of envelope layout (Geli, 2007). ................................................................................... 16 Figure 25 - Sancho D´Avila Façade (Geli, 2007). ........................................................................................ 16 Figure 26 - A spider web silk strings adapts .............................................................................................. 17 Figure 27 – A beaver dam goes through continuous structural morphosis .............................................. 17 Figure 28 – Ernst Haeckel's drawings of the evolution of vertebrate embryos (Haeckel, 1874). ............. 25 Figure 29 – Eixample city block, Barcelona; image source: Density Atlas (2011). ..................................... 33 Figure 30 - Image displaying the historic centre of El Poblenou. .............................................................. 33 Figure 31 – The Eixample .......................................................................................................................... 33 Figure 32 – Representation of the Eixample building cross section. ......................................................... 34 Figure 33 – The Eixample L shaped city blocks layout (De Decker, 2012). ................................................ 34 Figure 34 – The Eixample block and resulting solar path (De Decker, 2012). ........................................... 34 Figure 35 – Average sunshine hours per day in selected European cities................................................. 34 Figure 36 – A graphical illustration of an isotropic, exclusive and biased selection mechanism .............. 36 Figure 37 – A graphical representation of a genome map. ....................................................................... 36 Figure 38 – Crossover coalescence, blend coalescence and relative fitness coalescence mechanisms ... 37 Figure 39 – A genome graph representing point mutation. ...................................................................... 37 Figure 40 – Front and back of one of the Thin Film Photovoltaic Panels used in the prototype .............. 38 Figure 41 – Team of participants; source: workshop participant. ............................................................. 39 Figure 42 - Group 4 presentation; source: workshop participant. ............................................................ 39 Figure 43 – Sketches of a participant analysing the structural concept chosen ....................................... 39 Figure 44 – Workshop participant demonstrating the potential flexibility of the chosen structure ........ 39 Figure 45 – Potential twisting movement direction relative to solar incidence in the X and Y axis. ......... 40 Figure 46 – Potential bending movement direction relative to solar incidence in the Z axis. .................. 40 Figure 47 – Graphical representation of the full structure analysis and results. ...................................... 41 Figure 48 - Graphical representation of the analysis for where the solar sensors will be positioned. ..... 41

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Figure 49 – Graphical representation of the morning, midday and evening analysis. ............................. 41 Figure 50 – The 1:5 scale final model and the connections from the model ribs. ................................... 42 Figure 51 – The final 1:5 model. ................................................................................................................ 42 Figure 52 –Arduino Uno board platform, the breadboard, the energy source and an RC servo motor ... 42 Figure 54 – Schematic: RC servo motor with the Arduino board and a potentiometer. ........................... 43 Figure 55 – Schematic: RC servo motor with the Arduino board and a photocell receptor ..................... 43 Figure 56 –Arduino Uno board platform, the breadboard, the energy source and an RC servo motor ... 43 Figure 57 – The 1:1 scale final HelioCell prototype ................................................................................... 44 Figure 58 – Flexible photovoltaic panels were connected to the prototype structure. ............................ 44 Figure 59 – The Arduino boxes at the base of the prototype. .................................................................. 44 Figure 60 – Electricity transformer, two prepared Arduino boards and the motor. ................................. 44

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1. INTRODUCTION

In recent years a paradigm shift for reaching sustainable solutions

that respond to the ever morphing quality of the natural

environment and the inert materiality of the built environment has

been gaining momentum within the architectural mainstream.

Traditionally, the dominant paradigm for discussing and producing

architecture has been that of a human intuition and ingenuity

(Terzidis, 2003). However, an electronic1 and evolutionary2 paradigm

is also surfacing in which the output postulates an architecture born

of the relationships to dynamic environmental and socio-economic

contexts3, and realized through morphogenetic materialization

(Fraser, 1995).

Making architecture ecologically sustainable will require its

inanimate materiality to become attuned to the variable

biological clocks and activities of occupants inside, and to

similarly variable natural rhythms and mundane activities

outside. (…) Transitions make the city, which both allows

for and fosters bioclimatic diversity. (Yannas, 2011).

If we look at architecture as a trans-disciplinary domain, inherently

encompassing environmental, social and cultural spheres (along

with a myriad of sub-spheres), we can argue that these also have

dynamic qualities and inter-associations that work together as parts

of a mechanism or an interconnecting network, and could thus also

be represented as systems. Which in turn inherently (directly and/or

indirectly) govern and influence design4 choices.

These systems are also often changing, adapting and mutating in

search for homeostasis or equilibrium with and within their own

mechanisms. The built environment therefore could be interpreted

as a continuously metamorphing system, made up from a

compilation of active sub-systems, in contrast to the perception of it

bearing a static (Pask, 1969) or inert materiality.

1 - Electronic Paradigm. Peter Eisenman referred to the idea of an electronic paradigm shift in architecture in 1992. He wrote: During the fifty years since the Second World War, a paradigm shift has taken place that should have profoundly affected architecture: this was the shift from mechanical paradigm to the electronic one. (Eisenman, 1992). 2 - Evolutionary Paradigm - (Mendes & Ahlquist, 2011) . 3 - The European Committee for Standardization (CEN) EN 1521, Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics, Comité European de Normalization (Brussels) 2007; The American Society of Heating, Refrigeration and Air Conditioning Engineers ASHRAE Standard 55-04, Thermal Environmental Conditions for Human Occupancy, 2004. 4 - To some extent, a building is an interface between an outside environment and an inside environment, where people will reside (Caldas, 2001)

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Indeed, for the built environment to better perform in an

environmentally benefiting way, adaptive mechanisms5 need to be

integrated in its design and in order for it to operate in symbiosis

(implying action and reaction) with the natural environment; and

whilst human intuition and ingenuity may be the starting point, the

computational and combinatorial capabilities of computers must

also be integrated (Terzidis, 2003) so to augment a designer’s

capabilities of abstraction and multi-dimensional representation.

The adaptive design approach is demonstrated by a case study

developed via inter-disciplinary collaboration, comprised of a team

of computational experts, fabrication experts, architects and

designers with varied academic and professional experience levels6.

Indeed, the tools and information required for the development of

the adaptive design approach would not have been so readily

accessible without the effort of a much wider, global inter-

disciplinary collaboration; since most of the software, plugins and

add-ons as well as the open sourcing of data, online assistance, web

tutorials, and the real time information sourcing rely on the open-

source philosophy of the individuals who gratuitously develop,

share, teach and discuss their development and findings.

In more detail, the adaptive design approach describes the

framework of simultaneous analysis, evaluation, and generation of

interrelated multidisciplinary systems in order to satisfy early design

form exploration and post synthesis performance. Furthermore, the

goal of the research is to explore if with the use of graphical

algorithm editors and object-oriented programming, designers can

be empowered by a more intuitive approach for designing built

environments that integrate technology following environmental

protocols; ultimately fostering a symbiotic relationship between the

natural and built environments.

5 - Term coined by Victor Olyay in 1953.

6 – The interdisciplinary team was formed by the Institute of Advanced Architecture of Catalonia (IAAC) along with the FabLab BCN team for the SMART itSELF Summer Workshop 2012, which the author took part in. The study and work undertaken at IAAC comprised of many other simultaneous studies and analysis that will not be included in this thesis since they only peripherally relate to the author’s topic. The work that has been included however, serves as the basis and as a preliminary case study for the author’s design approach study, analysis and evaluation.

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1.1. Research Aims and Methods

This thesis seeks to explore and examine if a design approach called

‘adaptive’, applied via a generative system, can result in the

improvement of energy efficient design.

In order to reach this outcome, a research sequence was based on

the need for defining the terms of influence; for outlining the

processes and techniques used; for proposing a new theoretical

approach; and for testing the approach’s validity via a case study

able to provide quantifiable results. The research paper thus follows

a sequence of five chapters:

I. The Introduction chapter provides a brief explanation of the

motive behind the adaptive design approach and describes the

thesis’s main aims and research outline.

II. The Definitions chapter explains the terms used,

exemplifies and establishes the processes and/or techniques that

have been taken into consideration for the thesis’ approach.

III. The Adaptive Design chapter assimilates of the processes

previously described and theoretically includes the adaptive

design paradigm as a generative energy efficient design, and

proposes a design approach phase sequence along with other

considerations.

IV. The Adaptive Design Paradigm chapter is the unification of

the previous chapters into a testable preliminary case study,

which aims to demonstrate the approach’s validity and that it can

be realized; in this case, for the generation of an optimized design

outcome and the creation of an environment based adaptable

prototype for enhanced photovoltaic solar capture performance.

V. The Conclusions chapter bases itself on the studies,

exploration and examination of the previous chapters in which the

author’s final reflections on the adaptive design paradigm, as well

as notes about possible paths and research potential in the

further development of this approach, are described.

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Note on the Chosen Analogy

Janine Beyrus, a biomimicry expert and building consultant from the

Biomimicry Guild defines ecologic design as place based, taking into

consideration a site’s unique ecology and specific land type (Peters,

2012). This implies a holistic approach to ecologically benefitting

architectural design; and although the reach of this study does not

include biomimetic design in a direct sense, consideration was taken

to the evolutionary quality of highly efficient biological systems,

from which in the author’s perspective, could be used for the

benefit of designers in the search for ecologically benefitting design

development8. In this inclusive understanding, digital

morphogenesis in architecture also bears a largely analogous or

metaphoric relationship to the processes of morphogenesis in

nature (Roudavski, 2009); the mechanisms of growth and adaptation

will also be described in analogous or metaphoric terms, such as

seed, genotype, phenotype and embryogene, sharing with them the

reliance of gradual growth and evolutionary development; also,

much like DNA contains genetic instructions used in the

development and functioning of biological organisms, generative

design follows algorithmic instructions in the development of design

forms. These analogies will be further explored throughout this

thesis.

8 - Analogies, particularly biological, bedevil architectural writing. As Sullivan, Wright and Le Corbusier all employed biological analogies, and the concept of the organic is central to the 20th century (Fraser, 1995).

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2. DEFINITIONS

2.1. Generative Design

Generative design is about designing the system that

designs a building. Lars Hesselgren

2.1.1. Definition of Generative Design

Generative Design can be broadly defined as a morphogenetic

design process, in which the initial configuration of a condition is

established by a set of algorithmic rules, resulting in the generation

of a range of design possibilities.

Morphogenesis is a term borrowed from biology, which describes

the origin and development of an organism’s form and structure

(Davis, 2009) by the division and subdivision of a single cell, into new

symmetrical or non-symmetrical cells (Figure 1 and 2). Morphology

is not only a study of material things and the forms of material

things, but it has its dynamical aspect, under which we deal with the

interpretation in terms of force, of the operations of energy

(Thompson, n.d.); energy in which case can be represented by the

rules of which a system is governed by.

In architecture, morphogenesis is understood as a group of methods

that employ digital media not as representational tools for

visualization but as generative tools for the derivation of form and

its transformation (Kolarevic, 2000) often in an aspiration to express

contextual processes in built form (Kolarevic & Malkawi, 2005). Such

group of methods can also be called systems, as described by

(Sheaa, et al., 2005) generative systems are aimed at creating new

design processes that produce spatially novel yet efficient and

buildable designs through exploitation of current computing and

manufacturing capabilities.

Figure 1 and 2 - Radiolaria – image from Allan Turing's research on Morphogenesis and below Ernst Haeckel‘s Kunstformen der Natur.

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2.1.2. Generative Design Approach

The generative design approach allows the architect to choose and

manipulate the dominant parameters of which a design is ruled by.

It has been described by (Krish, 2011) as a designer driven,

parametrically constrained design exploration process, operating on

top of history based parametric Computer Aided Design (CAD)

systems structured to support design as an emergent process.

Whilst presently at stage of development, generative [design]

systems are an essential part of the future development of

performative architectural systems (Oxman, 2009).

2.1.3. Generative Design Systems

In architectural design, (Mitchell, 1978) traced generative systems

back to Leonardo da Vinci, whose idea was later formalized by the

textbooks of the École Polytechnique and the École des Beaux-Art

during the 19th century. Durand in his study Précis des Lecons

d’Architecture (1803) did an interesting generative systems study on

the re-assembly of parts of a structure such as columns, walls and

other architectural features, as illustrated on Figure 3.

With computational design, new possibilities have risen by the

ability to develop designs with a fast performing virtual

environment. This is particularly interesting for current day

architectural design, since a virtual environment allows for multi-

dimensional freedom and it allows, by default, for more effective

data input (as of rules), translation (as with algorithms) and retrieval

(for evaluation and application of new/adapted rules). The rules

applicable to generative systems and which define and control the

many different levels of resolution in form management range from

being completely computerized or to appoint manual step-by-step

override; such rules can be defined as verbal grammars, diagrams,

sets of geometrical transformations and scripts (Krish, 2011).

Figure 3 - One of Durand’s generative pattern studies in Précis des Lecons d’Architecture (Mitchell, 1977).

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According to (Mitchell, 1977) there are three main groups that

describe generative systems: analogue, iconic and symbolic.

i. Analogue: some properties are used to represent other

analogous properties of the designed object. This system can be

exemplified on the interconnected mechanics of Gaudi's wire-frame

suspended structural models, as seen on Figure 4.

ii. Iconic: in turn can create alternative design solutions by

assigning operations and transformations to the described parts,

most often done via computation, an analogic illustration of the

process is exemplified by Figure 5.

iii. Symbolic: or the use symbols such as words, numbers and

mathematical formulas, to represent the possible outputs.

Delouse borrowed from science three types of generative thinking.

He states that genes can tease out complex forms out of materials

because they inherently possess morphogenetic potential.

Population thinking (blending Darwin and Mendel in the 1930’s)

follows the idea that in order for evolution to take place, you need a

large reproductive community; intensive thinking (19th and 20th

century thermo-dynamics); and topological thinking (mathematics);

and finally philosophy allows for the synthesis between these three

types of thinking (Landa, 2009).

Note on Genetic Algorithms

Genetic algorithms are a script-based computational tool which

mimic and steer evolutionary processes by selecting and extracting

certain physical or behavioural traits and generating results based

on those traits through a virtual interface. They can be integrated

into different generative design techniques as described in the next

section.

Figure 4 – Upside down view of one of Gaudi’s suspended structural models which allowed him to understand the stress constrains for the Sagrada Familia.

Figure 5 – Hand drawn evolution drawing by William Latham, 1985 – ‘breeding creatures’ via generative form synthesis.

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2.1.4. Generative Design Techniques

Depending on the chosen generative system group there are

different generative design techniques that can be applied:

Cellular Automaton (Cellular Automata pl.)

These are mathematical idealizations of physical systems in which

space and time are discrete and physical quantities take on a finite

set of discrete values (Wolfram, 1983). These systems can be divided

into three main groups (elementary which is one dimensional, as

represented and illustrated by Figure 6 and Figure 7 respectively;

reversible which allows the system to reverse its iterations; and

totalistic which exists in two or more dimensions and are also

sometimes called life-like automata. Their application ranges from

ornamentation to automated volumetric building generation

(Fasoulaki, 2008).

Lindenmayer-systems (L-systems)

L-systems are a mathematical formalism proposed by the biologist

Aristid Lindenmayer in 1968 as a foundation for an axiomatic theory

of biological development (Ochoa, 1998); they are also able to

model the morphology of a variety of organisms ( Rozenberg &

Salomaa, 1980). They consist of four elements: a starting

configuration or initial string, a set of rules, constraints, and

variables; the fact that through a few simple rules complicated

forms can emerge makes L-systems a powerful tool for designers

(Fasoulaki, 2008). L-systems have recently also allowed for several

applications in computer graphics, two principal areas include

generation of fractals and realistic modelling of plants (Ochoa,

1998). Michael Hansmeyer, an architect and programmer used L-

systems, among other, in getting a design to respond to

environmental influences and to adapt to a wider range of

architectural design requirements (Hansmeyer, 2003).

Figure 6 - Conus textile exhibits a cellular automaton pattern on its shell.

Figure 7 - The illustrations above show some automata numbers that give particularly interesting pattern propagated for 15 generations starting with a single black cell in the initial iteration. Rule 30 is of special interest because it is chaotic (Wolfram, 2002)

Figure 8 – Examples of plant like structures generated by L-systems; image via Joost Rekveld.

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Voronoi Diagrams

These are named after the Russian mathematician Georgy

Fedoseevich Voronoi, who in 1907 defined and studied the n-

dimensional case. A voronoi diagram is made up of cells which,

through a pattern called Dirichlet tessellations, decomposes metric

space into regions or convex polygons. These polygons in turn are

determined by distances (Figure 9) to a specified family of subsets in

space. Subsets can also be called sites, generators, or ‘seeds’ to

which a voronoi cell will associate or correspond to. They can be

used for urban planning analysis and design to define for example,

the outer limits of districts in relation with infrastructural limits.

Fractals

In 1975, Benoit Mandelbrot coined the term fractal to define

mathematical rules that govern natural forms (Figure 10). Fractals

are broadly geometrical shapes that can be subdivided into parts

and their geometric characteristic is self-similarity i.e. each of the

parts are similar, reduced copies of the whole (Fasoulaki, 2008). The

connection between fractals and leaves, for instance, is currently

being studied by Dr. Brian Enquist (2011), an Associate Professor of

Ecology and Evolutionary Biology at the University of Arizona, to

determine how much carbon is contained in the leaves of trees.

Shape Grammar

The first design-oriented generative system, as defined by George

Stiny and James Gips in 1971. Shape Grammars is a rule-based

technique which generates designs by performing visual

computations with shapes in two steps: recognition of a particular

shape and its possible replacement (Fasoulaki, 2008). Architect

Michael Hansmeyer has used this technique in an attempt to

generate the design of a new column order (Figure 11).

Figure 9 – Voronoi diagram by Ivan Delgado. Each polygon contains exactly one generating point and every point in a given polygon is closer to its generating point than to any other (Fasoulaki, 2008).

Figure 10 – The Golden Ratio is a rudimentary fractal. In 1854, Adolf Zeiging, a mathematician and philosopher, noted that “the Golden Ratio is a universal law in which is contained the ground-principle of all formative striving for beauty and completeness in the realms of both nature and art, and which permeates, as a paramount spiritual ideal, all structures, forms and proportions, whether cosmic or individual, organic or inorganic, acoustic or optical; which finds its fullest realization, however, in the human form”.

Figure 11 – Form finding development using shape grammar via mesh based system by Michael Hansmeyer, 2010.

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2.1.5. Generative Design Examples

At the Building Scale

Frei Otto’s experiments with soap films and bubbles have shown

that self-generating and self-optimising forms in tents, cable net

structures of all types, various membranes and air or water-filled

pneumatics have been proven in engineering and are gaining

increasing application (Lee, 2009).

At the Urban Scale

Ivan Delgado’s preliminary urban design study using voronoi rule

based pressures to restructure a site defined by neighbourhood

quarters, bordering infrastructure and built-form section, as

illustrated on the first image from left to right in Figure 13. The

second image illustrates the initial built form curves formed and

residential district section delineation. The third image illustrates

the outer-most district limits in co-ordinance with southern

infrastructural border. And lastly, the fourth image illustrates the

outer limits of the mixed-use and manufacturing districts in relation

with northern and southern infrastructural limits – as established by

the designer. Voronoi system rules in this case assisted in defining

sections according to pressure dependant on a pre-determined

hierarchy. This allows for quicker analysis visualization, as well as

the addition and interaction of various rules (i.e. social, built or

environmental) by which an urban system is simultaneously

influenced.

Figure 12 - Frei Otto, Stuttgart Train Station. From top to bottom respectively: soap film experiments for producing minimal surfaces, prototype and final structure. Figure 13 – Preliminary urban planning analysis sequence using voronoi diagram technique; study by Ivan Delgado.

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2.2. Energy Efficient Design

2.2.1. Definition of Energy Efficiency

The word energy was defined by Aristotle as energeia, equating to

activity and efficacy: the power through which the possible is

transformed into the real. In the 19th century the term attained its

physical definition1 as ‘the work stored in the system or the capacity

of the system to do work’ (Hegger, et al., 2008). The International

Organization for Standardization in turn defines efficiency as the

‘relationship between the results obtained with the means used’ 2. It

is a behaviour that leads to achieving a goal while at the same time

keeping effort to a minimum.

Energy Efficiency is therefore the ability to use less energy more

effectively whilst providing the same output level (Lehmann, 2011),

it has also been defined by Frank Kreith, in the Handbook of Energy

Efficiency and Renewable Energy as the ‘ratio of energy required to

perform a specific service to the amount of primary energy used for

the process’ (Kreith & Goswami, 2007).

2.2.2. Energy Efficiency and Sustainable Development

Energy efficient buildings are an integral part of the overarching aim

to achieve sustainable development (Lehmann, 2011). Sustainable

development, as defined by the United Nations World Commission

on Environment and Development (WCED), is the ‘development

which meets the needs of the present without compromising the

ability of future generations to meet their own needs’3. Since the

1980’s the term sustainability has been used more widely in the

sense of human sustainability on the planet and has consequently

merged with the concept of sustainable development in view of

object, location and process qualities4. Sustainability affects the

totality of the active planning and running of a building, social,

economic and ecological concerns (Hegger, et al., 2008).

1- Energy occurs in various forms and can be divided, for example, into mechanical, thermal or chemical energy in accordance to its physical properties (Hegger, et al., 2008). 2 - ISO 9000:2005: Quality management systems – Fundamentals and Vocabulary.

3 - The Brundtland Report published on the 20th of March, 1987. 4 – Sustainable development is defined not only in terms of the qualities of the object being built (object quality), but also by its position (location quality) and its development process (process quality). Efficiency in the use of energy and resources has become a key quality indication for a building. The instruments of materials and energy-efficient building are at the same time architectural methods: lightness and mass, shelter and transparency, economical use of space and spatial effect. Manfred Hegger, 2008.

12

In this light, we can interpret that energy-efficient buildings need to

be designed in such a way that they totally or holistically (Lyle, 1994)

contribute towards the larger vision of building energy-efficient and

environmentally sustainable cities (Lehmann, 2011). Indeed, a

report from the Organisation for Economic Co-operation and

Development ( OECD, 2003) defines sustainable buildings as

buildings that are designed on the basis of holistic approaches, each

of which can be viewed as inter-related parts of a multi-scalar

system (Figures 14, 15, 16 and 17).

Holistic or Multi-Scalar Energy Efficient Design

For the design of energy efficient building in a holistic or multi-scalar

level, general criteria must be based on the adoption of suitable

parameters for building orientation, shape, structure, envelope,

passive heating and cooling mechanisms, shading, and glazing (R.

Pacheco, 2012); thus striving to reduce the overall impact of the

built environment on human health and on the natural environment

by efficiently using energy as well as other resources as well as

reducing waste products. Steps that could be taken to properly

investigate the efficiency of a site at the regional level are: research

into all pertinent aspects that influence a site such as the societal,

the built and natural environments; a written and illustrated analysis

and diagnosis by influencers (i.e. the pros, cons and levels of

mitigation due to overlap); a prognosis determined by pre-

determined parameters of influence; and a proposal of a five or ten

year plan with the new prognostic outlook. This assists in

determining the areas which display fluid or stagnant efficiency

levels. Following these parameters, localized design interventions

can be applied to improve or benefit from these areas through

strategic and energy efficient building design; which in turn primarily

relies on establishing environmental comfort whilst simultaneously

adapting to the regional climate characteristics (Figures Figure 18

and 19). The success of these adaptations can ultimately determine

a design’s energy efficiency level.

Figures 14, 15, 16 and 17 – From top to bottom respectively: showing a multi-scalar analysis and detailing at the regional level (Reiman Buechner and Crandall, 1983).

Figure 18 and 19 – Multi-scalar, climatic analysis and detailing at the building level (Watson & Labs, 1983); an enlarged version of these images can be found in Appendix 1.

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2.2.3. Energy Efficient Design Orientation Systems

Six systems that could assist in orienting a holistic or multi scalar

approach to sustainable development via energy efficient design

considering the interrelation between the societal, the built and the

natural environments:

i. Information system: Social and Cultural

ii. Natural Resources system: Raw Materials

iii. Developed Resources system: Energy

iv. Processed Resources system: Waste

v. Urban system: Infrastructure, Mobility & Planning

vi. Natural system: Biodiversity and Climate

A city is made up of an urban metabolism5 and a rich ecosystem, and

in this light a heterogeneous complex system. Like any complex

system, it changes and evolves over time, continuously adapting to

social, built and environmental changes. Adaptation in turn helps

create resilience, which is the key to ensure continuity of services in

the city at any time of crisis (City Protocol Org, 2012).

5 - First used as an exploration and comparison modelling tool by Abel Wolman in The metabolism of Cities, Urban Metabolism offers benefits to studies of the sustainability of cities by providing a unified or holistic viewpoint about the health of a city: energy efficiency, material cycling, waste management and effectiveness of infrastructure, thereby encompassing all of the activities of a city in a single integrated model (Kennedy, 2004). Figure 20 – Anatomy of the City Protocol, displaying the interconnectedness of natural and built systems at various scales. The city should be adaptive, learning, evolving, self-repairing, and self-reproducing. (City Protocol Org, 2012). Note that the economic aspect of these systems is integrated and in most cases also promotes interconnectedness. An enlarged version of this image can be found in the Appendix 2.

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2.2.4. Energy Efficient Design Example

An example of holistic or multi-scalar energy efficient design is

Renzo Piano’s California Academy of Sciences built in 2008, and

which achieved the Leadership in Energy and Environmental Design

(LEED)6 Platinum Certification, the highest of LEED ratings, scoring

above eighty points out of a hundred based on criteria of site

selection, water efficiency, energy and atmosphere, materials and

resources, indoor environmental quality, location and linkages,

awareness and education, innovation in design and regional priority.

The approach by the architects allows for an overall increased

efficiency from design through building synthesis via multi scalar

integration which includes among other: information systems via on

site ecological education and physical interaction with the building;

natural resources system: via sourcing of raw and recycling materials

for construction; developed resources system: generating energy on

site and utilizing passive design strategies throughout the building;

processed resources system: complex waste and water systems

implemented to work in conjunction with i.e. the aquarium; urban

system: infrastructure, mobility and planning initiatives to

encourage public transport use; natural system: biodiversity and

climate via integration and ecological considerations7.

6 - LEED certification provides independent, third-party verification that a building, home or community was designed and built using strategies aimed at achieving high performance in key areas of human and environmental health: sustainable site development, water savings, energy efficiency, materials selection and indoor environmental quality. 7 - A more detailed account of the LEED rating criteria and a quantitative explanation on the measures that lead up to the platinum certification, as described by the Fondazione Renzo Piano, can be found in Appendix 3.

Figure 21 and 22 – Elevation showing aesthetic integration of green roof with surrounding landscape (top) and longitudinal cross section showing planetarium dome, exhibition hall, piazza and rainforest dome (bottom); images by Fondazione Renzo Piano. The cross section above roughly illustrates some of the passive systems implemented in the building design. LEGEND: 1.Restored adjacency park (natural shadow), 2.Green roof (insulation and passive cooling), 3.Roof Geometry favours “venturi effect”, 4.Glass canopy with photovoltaic cells, 5.Concrete walls (passive cooling), 6.Operable vents and skylights, 7.Sunshades, 8.Radiant floor, 9.Natural lights for plants.

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2.3. Generative Energy Efficient Design

2.3.1. Definition of Generative Energy Efficient Design

Generative design, operating on non-linear platforms of

neighbourhood-based computing, is working on opening new

regional topologies of tension and synthesis (Andrasek, 2012).

According to Christopher Alexander, a generating system is not a

view of a single thing, but a kit of parts, with rules about the ways

these parts may be combined8. If we wish to create a built

environment that functions holistically with the natural

environment, or as a ‘whole’, then we shall have to invent

generating systems whose parts and rules will create the necessary

holistic system properties to serve this desired function (Alexander,

1968). If architecture is to embark into the foreign world of

algorithmic form its design methods should incorporate

computational processes that allow flexibility for architects to merge

environmental design solutions with current and emerging

technology and aesthetically complex design. What could be called

data materialization is opening up the potential for architecture to

finally resonate with the complexity of ecology (Andrasek, 2012).

A criterion for evaluation is necessary for the system to be proved

effective. Adding evaluation to those combinatorial mechanisms

(Mitchell, et al., 1990) allows for the application of quantifiable,

numerical methods to these systems, and in some way to the

emergence of the field of optimization (Caldas, 2001). One must

note that for the application of an evaluation method for a holistic

or multi-scalar system, the evaluation methods cannot be solely

based on optimization factors. That is because unquantifiable

influencers exist, that are for example aesthetic or societal in nature,

and which a simulation program cannot properly quantify without

the designer’s personal input. Instead, the final design intent should

strive to reach the best strategically adapted solution, where the

architect defines the intent(s) to evolve to and chooses the final

adaptation according to his own experience and sensibility.

8 - Almost every system as a whole is generated by a generating system (Alexander, 1968).

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2.3.2. Generative Energy Efficient Design Example

An example of generative energy efficient design is the Spain based

Media - Tecnologías de la Información y la Comunicación building

(Media TIC) in Barcelona, designed by Cloud 9 Architects under

Architect Enric Ruiz Geli; completed in 2009. The Media TIC’s

structure was designed via generative techniques, as one example,

for improved load distribution and support (Figure 23), maximizing

the efficient use of materials and consequently achieving significant

energy savings in terms of embedded or grey energy; according to

the Energy Manual: Sustainable Architecture, heavyweight forms of

construction require about 20% more grey energy than lightweight

structures (Hegger, et al., 2008). A graphic scheme of Media TIC’s

energy efficiency measures can be found in Appendix 4.

The building consists of a main metallic structure, composed of four

rigid, braced frames, from which the building’s eight floor plates are

hung via cables. The frame type consists of metal beams made of

forged-metal girders; each frame has a support beam that transfers

their load to the rigid support centres (Geli, 2007) and by following a

generative design resolution, this structural system efficiently

distributes the loads using only the necessary amount of material.

The construction method also allowed for a quick assembly of the

light weight structure (Geli, 2007). The resulting design does not

follow the usual orthogonal grid design; note how, as a result of the

generative technique, the final design resembles a Voronoi diagram

(Figure 25). Segments from the patchwork geometry of EFTE9 double

faced or cushioned panels have also been created following

generative patterns. Each of the facades exposes a different grid,

glazing and openings pattern dependent on the interactions

between the load bearing structure as well as the interior and

exterior climate. The envelope allows for an openness and flexibility

of the façade and interior (Figure 24) via the real time interaction of

more than 300 thermo/light sensors that automatically regulate

temperature and light levels by inflating or deflating its cushions.

Figure 23 – Media TIC; photos author’s own.

Figure 24 – Detail of envelope layout (Geli, 2007).

Figure 25 - Sancho D´Avila Façade (Geli, 2007). 9 - Ethylene tetrafluoroethylene, fluorine based translucent plastic, used by some architects as a building’s skin envelope.

17

3. ADAPTIVE DESIGN: A Generative Energy Efficient Design Approach

Charles Darwin in his 1859 book Origin of Species stated that “in the

struggle for survival, the fittest win out at the expense of their rivals

because they succeed in adapting themselves best to their

environment” and that “it is not necessarily the strongest of the

species that survives, nor the most intelligent, but the species that is

most responsive to change” (Darwin, 1964). Gilles Deleuze

complements Darwin by stating that matter has its own

morphogenetic qualities1.

Biology based essentialism and creationism theories state that

matter is essentially inert, that is, without any morphogenetic

capabilities and which cannot give rise to new forms on their own; in

this light, form is created through an ideal and is imposed as an inert

materialism. Indeed, the built environment seems to be

predominantly viewed as presenting an inherent un-responsive or

inert materialism; especially when compared to nature’s own

version of ‘built’ environment in the form of, for example, spider

webs (Figure 26) or a beaver’s dam (Figure 27) which can both be

viewed as systems of variable complexity able to react and adapt to

climatic and environmental circumstances. Also, as John Fraser

explains, a produced architecture is already a participant of the

natural system, exhibiting metabolism and acting like the mechanics

to which it was formed: in exchange with environment, responsive

to feedback and evolutionary in its own right (Menges & Ahlquist,

2011). During the early 1970’s John Henry Holland described

adaptation as a process whereby a structure is progressively

modified to give better performance in its environment (Holland,

1975). This can be applied to the design as well as built systems

themselves. The defining particularity however, is to produce an

architecture that intentionally benefits the natural and built

environment through such participation.

Figure 26 - A spider web silk strings adapts to the changing weather by stretching or compressing in order to maintain its structure and function.

Figure 27 – A beaver dam goes through continuous structural morphosis to adapt to the changing levels of water whilst avoiding internal flooding and maintaining a constant average of internal environmental comfort for its inhabitants. 1 - Deleuze stated that “there is only one substance, and it can modify itself in many ways. Those ways are not copies or replicas or models of some original; they are foldings, unfoldings, and refoldings of substance. Those foldings and unfoldings may become different from what they are. Darwin has taught us that they likely will. We don’t even know of what a body is capable” (May, 2005) .

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3.1. Definition of Adaptive Design

The term ‘adaptive’ has a dual utilization in this study: the first use

refers to a morphogenetic design evolution which adapts according

to environmental design parameters in search for improved

resilience in design outcome through a multitude of iterations; the

second use refers to the real-time physical adaptation of the design

to the surrounding environment based on the previously established

parameters in search of an improved symbiosis between the built

and natural environment.

Ultimately, for this study, ’adaptive’ describes a design approach

that seeks to unite multi-scalar factors via a generative system in

order to reach a symbiotic energy efficient design solution.

Note on Performative Design

The term performative architecture (performance in design) can be

interpreted and translated into a myriad of approaches; however it

basically defines the architectural object, not by how it appears, but

rather by its capability of affecting, transforming and doing; in other

words, by how it performs (Albayrak, 2011). Performative design has

also been recently proposed as the action that mediates the two

forces of artifice and environment; and the performance of design

(considered through that which is built, materialized and produced)

as it engages with its surroundings (Araya, 2011). Other designers

naturally attribute their own interpretations to the same approach.

The descriptions that encompass the performative approach also

appear to be very similar in meaning to the one the author calls

‘adaptive’ specially in striving to reach a certain type of balance or

equilibrium between the natural and the built environments.

However, for this study, the term adaptive has been chosen due to

its metaphorical and analogous association to the natural processes

that better exemplify the desired design process, development and

outcome.

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3.2. Adaptive Form and Performance

A whole range of ideas and concepts have been imposed on physical

forms in an attempt to find the answer of the true function of form

(Moussavi, 2009). During the nineteenth century, the concept

behind the dictum “form follows function” was first associated to

Horatio Greenough, which in 1852 related it to the organic principles

of architecture (McCarter, 1999). Later in the same period, the

American Architect Louis Sullivan devised the phrase2, relating it

mainly to its cultural and social role (Moussavi, 2009).

Through time however, this perception changed to a modernist and

industrialized way of thinking3. The core concept of the afore

mentioned dictum was stripped from its multi-scalar and complex

potential to a simplified one, resulting most often in an

(aesthetically and culturally de-sensitized) mass produced

architecture which does not try to adapt to its surrounding

environment but instead imposes itself on it whilst simultaneously

striving to achieve some form of independent efficiency. However,

as exemplified in the previous chapters, the [built] environment is

the product of diverse processes that are linked in complex ways

(Moussavi, 2009); in other words, these systems are

interdependent. It is logical to assume then, that different systems

which share or compose a heterogeneous environment could

achieve better efficiency through a symbiotic or interdependent

relationship (maintaining a fluid heterogeneity). Following this logic,

the better that architecture (if viewed as form and system) adapts to

its surroundings (made for example, of the six afore-mentioned

energy efficiency orientation systems) the better the results (via

synergy) will be in terms of multi-scalar (energy) efficiency. An

approach to reach this adaptive paradigm will be described,

analysed and evaluated in the following sections.

2 - It is the pervading law of all things organic and inorganic, of all things physical and metaphysical, of all things human and all things super-human, of all true manifestations of the head, of the heart, of the soul, that the life is recognizable in its expression, that form ever follows function. This is the law. (Sullivan, 1896). 3 – A view of Modern Architecture developed from the convergence of the nineteenth century dictum “form follows function” and Adolf Loos’ 1908 proclamation that ”ornament is crime”. Later, in the twentieth century Walter Gropius, one of the progenitors of the modernist architecture, stated that: “the unification of architectural components would have the salutary effect of imparting that homogeneous character to our towns which is the distinguishing mark of a superior urban culture. (…) The concentration of essential qualities in standard types presupposes methods of unprecedented industrial potentiality, which… can only be justified by mass-production.” (Gropius, 1965).

20

3.2.1. Adaptive Form: Morphogenetic Evolution

Morphogenesis and evolution provide both an all-encompassing and

intricate notion of the formation and functioning of natural systems

(Menges & Ahlquist, 2011). Trummer also argues that the real

potential of computational techniques is to overcome any idea of

typological thinking and to come up with a thesis of a design

practice based on morphogenetic processes (Trummer, 2011).

Goethe, in 1796, introduced the notion of morphology, outlining a

critical distinction between form (gestalt) and formation (bildung),

and which seeks to "illuminate the processes that governed form

rather than form itself" (Menges & Ahlquist, 2011) and so laying the

foundation for linking geometric behaviour with a functional logic.

D’Arcy Thompson illustrated how to mathematically demonstrate

this concept by geometrically representing homologous formations

through parametric systems. Both Goethe and D’Arcy contributed to

the understanding of transformational laws which influence the

expression of form (Menges & Ahlquist, 2011); however, the

understanding of biological formation did not come into full

perspective until the discovery of genetics. These concepts, when

united, directly apply to the notion of morphogenetic evolution.

The discourse on digital morphogenesis in architecture has since

linked it to a number of concepts including emergence, self-

organization and form-finding (Roudavski, 2009). According to

Kostas Terzidis (2003) morphism employs algorithmic processes for

the interconnection between seemingly disparate entities and the

evolution form one design to another. Paraphrasing Peter Trummer,

if architectural objects are thought of as assemblies we can start to

understand them as physical systems, whereby the addition of parts

defines a space of possible change; also described by Manuel de

Landa as degrees of freedom4. As a consequence, the architectural

object is no longer to be understood as a geometrical construct but

as a physical entity. Thus the architectural object would be

understood by means of its morphogenetic process and defined as a

ADAPTIVE [USE #01] A MORPHOGENETIC DESIGN EVOLUTION WHICH ADAPTS

ACCORDING TO ENVIRONMENTAL DESIGN PARAMETERS, IN SEARCH FOR

IMPROVED RESILIENCE IN DESIGN OUTCOME THROUGH A MULTITUDE

OF ITERATIONS.

4 - By defining the paths of which a system is ruled by, the paths of freedom of that system also become apparent. Once a process’s degrees of freedom are discovered, the model can be given a spatial form by assigning each of them to a dimension of a topological space. (Landa, 2011)

21

multiplicity rather than type (Trummer, 2011). Furthermore, in the

context of creativity in design, evolution serves as an exploratory

engine in producing variety within genotypic parameters, and

natural selection acts as a search for effective functioning of

phenotypic results (Bentley & Corne, 2002).

Architects can, through this process, go beyond geometry to directly

design the structure of matter itself (Andrasek, 2012).

Complementing Andrasek, since computational kernel processes are

built on porous boundaries between systems, an energy efficient

based flow of production and operability could also be engaged

within the fibres of generative processes, allowing the design and

the built form to evolve within certain fitness5. This makes

architecture more resilient against energy inefficient pressures and

pre-set industrial rigidities.

3.2.2. Adaptive Performance: Symbiotic Homeostasis

As we have seen so far, improved performance can equate to

energy efficiency through holistic integration and interaction of

multi-scalar systems. According to (Bertanffy, 2011) equifinality and

feedback are two critical conditions which are required for multi-

themed dynamic systems to operate. By their nature both

conditions seek balance, or homeostasis, and in the case of this

thesis, whilst retaining their heterogeneous or inherent qualities in

order to reach an correspondingly agreeable result.

Symbiotic homeostasis in building performance equates not to the

optimal performance of individual parameters, but the resulting

efficiency through their interaction. Since the natural environment is

never completely still or inert, and we cannot attempt to control its

mutability, a different approach could be necessary; perhaps if the

inert materiality of the built environment became dynamic and

could adapt to the ever morphing quality of the natural one, and

through a hierarchy defined via equifinality and feedback, greater

energy efficiency between these two environments could be

reached.

5 - The notion of fitness is taken from evolutionary biology where fitness landscape is used to visualize relationships between generative agents (such as genotype or phenotype) and their capacity to satisfy certain goals (such as reproductive success). In architecture, fitness usually refers to success related to performative aspects of a system, or the design intent posed by the architect herself (Andrasek, 2012).

ADAPTIVE [USE #02] THE REAL-TIME PHYSICAL

ADAPTATION OF THE DESIGN TO THE SURROUNDING ENVIRONMENT,

BASED ON THE PREVIOUSLY ESTABLISHED PARAMETERS, IN

SEARCH OF AN IMPROVED SYMBIOSIS BETWEEN THE BUILT AND NATURAL

ENVIRONMENT.

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3.3. Adaptive Design Approach

3.3.1. Prerequisites for Utilizing the Adaptive Design Approach

Some general pre-requisites should be considered in order to

properly realize and achieve the desired outcome associated to an

adaptive design approach; briefly described they are:

Specialized Multi-Disciplinary Collaboration

Multi-disciplinary and trans-geographic collaborations can promote

sharing of knowledge, conceptual brainstorming, multiple goals,

creative negotiations, and performative feedbacks; allowing for a

variation of multi-disciplinary, and maybe conflicting, performances

to be examined and faced in greater detail at the early design phase

and not when the design solution is solidified. Furthermore,

systematic design methods strive to reduce the amount of errors,

trade-offs and implementation time, while obtaining more

innovative and advanced designs (Fasoulaki, 2008).

Early Integration and Identification of the Design Phases

The rise of concurrent architectural phase development requires

early team formation and constant communication throughout the

project life cycle. By communicating and developing projects though

real time and virtual integrated software systems in which the

interface between user and machine is continuous, users can modify

the design problem, by adding, removing or changing data,

throughout the design phase (Fasoulaki, 2008). By guiding evolution

as it happens, the users are able to explore new ideas as they

emerge through the mechanisms of evolution (Mendes & Ahlquist,

2011). Just as important is the identification of the design phases,

which establishes the sequences and deadlines, and predicts the

expectations and desired outcomes for each of the project

development phases, allowing for general controlled improvement.

Operability and Completeness of Metadata Systems

The need to replicate the real world context as much as possible

relies on the compatibility and completeness of the input data;

23

inclusively the evaluation and synthesis of interrelated sub-systems

should be done in a holistic and synergetic way. By thinking about

the performances beyond their affiliated systems, designers might

invent new building systems that satisfy many needs simultaneously

through an unexpected form (Fasoulaki, 2008).

Unified Interaction of Design Tools and Spontaneity

The unification of design tools with simulation and evaluation tools

and the exploration of generative capabilities of digital design tools

are required for the development of a unified environment in which

they will be used both for analysis and synthesis phase merging

generative, optimization and simulation algorithms (Fasoulaki,

2008). The process should allow flexibility for the designer so it is

successfully used within a myriad of situations. Inclusively, in order

to achieve a high degree of realism, the simulation is designed to

include elements of uncertainty and the consequent high level of

tension through programmed spontaneity. Guidance is provided by

automatic software routines that judge evolving solutions without

the need for human input (Mendes & Ahlquist, 2011).

User Accessibility and Legitimacy of Results

A process’s further workability and user accessibility usually

depends on a previously achieved level of transparency, readability

and legitimacy of results. In order to value the multi-disciplinarily

and trans-geographic qualities that allowed for the project to be

created and developed, the final result must allow for the re-

integration of the same in order to allow for further development

through the evolution of derivations based on the original process.

This is possible, for example, through the utilization of open sourced

algorithmic based software which can inherently proportion

integrated development between all stages. Because of the open-

source quality, processes will be continuously tested and improved

on via multi-disciplinary trans-geographic users, potentially

improving its resilience and output.

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3.3.2. Adaptive Design Phases

According to Mendes and Ahlquist, for the adaptive process to

occur, three components are required (Menges & Ahlquist, 2011);

they have been integrated for the purposes of the adaptive

approach as the environment of the system undergoing adaptation:

such as the starting form, the materiality and/or the structure of

the building and its influences; the adaptive plan, whereby a system

is modified to effect improvements: such as structural changes or

addictions as well as environmental, and/or societal rules by which

the system must function by; and a measure of performance, i.e.,

the fitness of the structures based on its balance with the

environment. Inclusively a practical generative design method, as

recently outlined by Sivam Krish, has been defined as a

comprehensive computer aided design method aimed to work at all

stages of the design development process, spanning from

conceptual to detailing of final design (Krish, 2011); the generative

design process is composed of configuration variations,

performance metrics and decision making responses (Marsh, 2008).

Furthermore, in the context of an adaptive environment,

architectural design can take place in several interdependent stages,

they are: the specification of the goal or purpose, the choice of basic

environmental materials, the selection of the invariants,

specification of what the environment will learn about as well as

how it will adapt, and the choice of a system for adaptation and

development (Pask, 1969).

Merging these concepts and methods and considering the processes

inferred by the chosen analogies for the adaptive design approach,

the following five phase sequence is proposed:

i. SEED - Specification of the goal or purpose of the project in

question and research into the required legislative,

environmental, historic and other information that customarily

precedes an architectural project. The phase called ‘seed’ serves

to establish the basic and unchangeable parameters that will be

25

used to generate the future project and inherently contain full

development potential.

ii. GENOTYPE - Choice of hierarchy between basic design

parameters specifying the limits of the design space to be

explored, for example the initial values and exploration

parameters based on previous phase criteria. The ‘genotype’

phase consists of delineating the limits and values to which the

design should follow by, via designer imposed hierarchy.

iii. PHENOTYPE - Selection of the observable characteristics

and invariants that may include build history, built-in relationships

and built-in equations. The ‘phenotype’ phase specifies initial

results on what the environment (or architectural design) will

learn about and how it will adapt. It also includes the data table

that stores the driving design parameters, their initial values and

limits.

iv. EMBRYOGENE – Exploration of iterations based on the

previously established design parameters and limitations. The

‘embryogene’ phase allows iterations to be explored via a

parametric computer aided design engine, with a transparent and

editable build history preferably with a tri-dimensional geometric

kernel, with capabilities to manage geometric relationships,

engineering equations and connect to external design tables.

v. SYNTHESIS – Definition of system for adaptation or change

and development via performance or software filters able to

evaluate the performance of generated designs based on pre-set

or comparative performance criteria. The performance may be

evaluated directly from the design table, by inbuilt evaluation

interface tools or by the use of external analytical software.

Figure 28 – Ernst Haeckel's drawings of the evolution of vertebrate embryos (Haeckel, 1874).

26

3.3.3. Potential Benefits of the Adaptive Design Approach

There are many potential benefits for using an adaptive design

approach via digital design systems. In search for adaptive form and

performance, a generative design approach is useful because a

geometric model can be formulated to transform and generate

according to specific evaluation criteria6 and which can, based on

these criteria, produce further geometric models (Oxman, 2009).

With evolutionary development however, these results can include

desired as well as non-desired outcomes. The adaptive design

approach therefore seeks to generate an evolutionary sequence of

iterations taking into consideration specific ‘genetic’ goals in search

for an improved design outcome. Therefore the integration of

biological morphogenesis can strategically inform and thus benefit

architectural and urban design applications. An example as to how

biological processes can benefit architectural design7 has been

described by Roudavski as:

Architectural design increasingly seeks to incorporate

concepts and techniques, such as growth or adaptation,

that have parallels in nature; architecture and biology share

a common language because both attempt to model

growth and adaptation (or morphogenesis) in silico

(Roudavski, 2009).

This is not to say that the adaptive design approach results in

seamlessly efficient results, since evolution also depends on the

interpretation of what is or isn’t considered a fault to evolve from,

which depends on environmental, societal and other factors along

with the designer’s personal interpretation. It does however

significantly enhance the chances for achieving that goal, as will be

confirmed through a preliminary case study in chapter four.

6 - These may be single criteria evaluations (i.e. structural performance, solar loading, and acoustic performance) or, multi-criteria evaluations including multiple performance and optimization factors (Oxman, 2009).

7 - In a reverse occurrence, architecture and engineering can inform the studies in biology because components of organisms develop and specialize under the influence of contextual conditions such as static and dynamic loads or the availability of sun light; in biology as in architecture, computational modelling is becoming an increasingly important tool for studying such influences; architecture and engineering have developed computational tools for evaluating and simulating complex physical performances (such as distribution of loads, thermal performance or radiance values); and such tools are as yet unusual or unavailable in biology. (Roudavski, 2009). It is often important to understand the reverse occurrence in order to better understand their processes and integral raison d'être.

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3.4. The Role of the Architect

It is important to note here, the central role of the designer

in continuously modifying the generative scheme based on

the resultant outcomes; by which the solutions space is

navigated in search of viable design solutions (Krish, 2011).

The role of the professional in generative design is of a designer of

algorithmic models for form generation and/or modifications and/or

moderator of knowledge and principles into rules of which a

generative system will follow. When digital morphogenesis is

applied to a design, the architect must: define the problem, choose

the algorithm, and verify the output is valid (Davis, 2009).

Paraphrasing Mark Burry, while computation itself implies

operation, it is really the selection, alignment and coordination of

the operators which allows for knowledge to be inherited into the

process and specificity relevant to material and context to be

realized. This is the capacity of the architect (2011). Inclusively, we

must considering that not every generating system creates results

with desired or valuable properties. Indeed, buildings also perform

subtle economic, societal and cultural roles which can only be

understood adequately by reasoning about them in the light of

extensive economic, societal and cultural knowledge (Mendes &

Ahlquist, 2011).

Architectural design should therefore not be singularly about finding

the 'optimal' solution based on a set of parameters or criteria

(Caldas, 2001), because they might not provide the desired solution

for a specific environment; thus it is important to let the architect

interfere with his preferences, knowledge and aesthetic sensibility in

the adaptation process.

In addition to an increased level of proficiency and

understanding of building performance and environmental

principles, it is new skills such as writing scripts and

computer programming, not typically taught to architects,

which are proving to be a major contributor to the building

28

design process. It is often those designers who have

adapted and developed these skills to better integrate

performance analysis at the earliest stages that are

increasingly designing the buildings best able meet our

current environmental challenges (Marsh, 2008).

Authored practice in generative design therefore retains crucial

importance, since it extends the transference of ‘creativity’ from the

explicit impression into form, to the investment of thought,

organization and strategy in the computational processes by which it

is produced (Fraser, 1995). Gordon Pask also notes that the symbolic

and the informational needs of man cannot be satisfied purely by

following a set of instructions (1969); the built and natural

environment systems are much more complex than we can yet

encompass in a algorithmic-based formula, in the sense that both

inherently possess unquantifiable and unpredictable data and

influencers, which need be interpreted into the design by an

architect (also inherently possessing unquantifiable and

unpredictable qualities themselves). Basically, the idiosyncrasies of

the natural and built environment need to be considered, defined

and integrated (and re-integrated as many times necessary8) by the

architect to the augmented computer aided design interface9.

Another important aspect that requires mentioning is that the final

architectural design is most often a conglomeration of inputs

conjointly developed by a number of specialized professionals. This

is crucial for achieving a resilient design intent, development and

outcome due to the heterogeneous and all-encompassing nature of

the feedback provided.

8 – In order to improve resilience within a desired design evolution, as explained in the previous sections of this chapter. 9 - The computer works as a way of augmenting the architect's capabilities and creativity, such as the machine did before it, entailing a first 'loss of innocence’ (Alexander, 1964), from what many architects of the time retracted. The introduction of computation in the design process corresponds to a second 'loss of innocence,' according to Alexander too, this time an intellectual rather than mechanical one, that many architects may not be willing to accept either. Second, that the idea that an architectural design must be totally intentional, in the sense that all decisions have been made by the architect in response to a program and a site, may be passive of reflection. Programs change [a building is designed to be occupied in some way and it is later adapted for some other use]; sites change, and a building's response to a site may become just a trace after time has passed by; so one may question if the design shape does indeed need to be fully responsive and intentional in relation to its time/place contingencies. Alvaro Siza, who has always taken the 'site' as a main departing point for a design development, has recently put forward the idea of 'a shape looking for a site.' (Caldas, 2001)

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4. ADAPTIVE DESIGN PARADIGM: Case Study

The primary aim of this preliminary case study is the familiarization

with the design phases of the Adaptive Design approach and to

examine how a generative computational model could be defined to

take into account a number of interrelated performances in order to

achieve better energy efficiency. Additionally, how the conflict or

synergy of a generative and energy efficient juxtaposition could be

visualized through form by choosing a simulation approach that fits

with the research question, assumptions and theoretical logic.

The preliminary case study will enable to explore and examine if the

design approach called ‘adaptive’, applied via a generative system,

can result in the improvement of energy efficient design; first

through the use of digital morphogenetic evolution at the design

phase, and second by virtually connecting the resulting form or

structure’s operating system to real time data readings in order to

automate reactions to their own and other systems of influence.

Ultimately, through this case study, an attempt to achieve a level of

symbiotic homeostasis between the built and natural environments

through a generative energy efficient design approach will be

tested.

Two factors extracted from the IAAC case study hold primary

importance for this research and therefore have been selected for

further analysis by the author. They refer to the adaptive generative

evolution of design iterations and to the physical adaptation of the

final form to environmental influences which can conjointly

determine the holistic energy efficiency of a built-form.

In more detail, the term ‘adaptive’ has a dual utilization in this

study; based on the two factors respectively: the first use refers to a

generative design evolution which adapts according to

environmental design parameters. This type of design development

can operate at the conceptual stages when the design is still under

formulation, as well as follow a specific evolution defined by sets of

rules orchestrated by the designer1; such as environmental

1 - Christopher Alexander, in his book Architectural Design, identified and classified generative schemes as DNA-like building blocks of architectural design, where the application of basic instructions can generate infinite variations; inclusively ‘the generative scheme always generates structure that starts with the existing context, and creates things which relate directly and specifically to that context’ (Alexander, 1999).

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parameters for energy efficiency. The ability to explore a controlled

evolution of design variations at the early stages of design can

produce far more beneficial results than optimizing it within narrow

means at the final stages of design (Krish, 2011).

The second use of the term ‘adaptive design’ refers to the real-time

physical adaptation of the design to the surrounding environment

based on a previously established set of parameters2. As a

continuum to the evolutionary generative design explanation,

Christopher Alexander noted that “the resulting form’s ability to

rejuvenate and readjust to the changing environments and design

needs makes generative schemes timeless patterns”.

Ultimately the desired result for this preliminary case study is to

create, explore and develop the possibilities of adaptation of an

environmentally responsive structure, containing improved energy

efficiency characteristics, resulting in a quantifiable improvement

from an otherwise static system.

4.1.1. Case Study Approach

The case study follows the adaptive design approach as described

and proposed in the previous chapter and aims to demonstrate the

approach’s validity and that it can be realized for the generation of

an optimized design outcome and the creation of an environment

based adaptable prototype for enhanced photovoltaic solar capture

performance. Each phase is separated into sub-chapter sections and

the relevant information respective to the phase is described.

The approach will be performed through the exploration of

generative design, optimization and simulation methods and

techniques via a specialized multi-disciplinary team of collaborators

arriving from different stages of professional development, most if

not all related to an architectural, design or computational

background3. This team was formed and directed by the Institute of

Advanced Architecture of Catalonia (IAAC) along with the FabLab

BCN team for the SMART itSELF Summer School 2012 workshop,

2 - If it could be demonstrated that any complex organ existed, which could not possibly have been formed by numerous, successive, slight modifications, my theory would absolutely break down. But I can find no such case (Darwin, 1964).

3 - The multi-disciplinary team consisted of a multi-disciplinary team of academics and professionals with varied backgrounds and levels of expertise.

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which the author took part in. The study and work undertaken at

IAAC comprised of many other simultaneous studies and analysis

that will not be included in this thesis since they only peripherally

relate to the author’s topic. The work that has been included

however, serves as the basis and as a preliminary case study for the

author’s design approach study, analysis and evaluation.

Indeed, the group of chosen collaborators provided valid know-how

and technical knowledge for the IAAC along with the FabLab BCN

workshop purposes, and despite achieving a successful outcome;

the group does not encompass the full requirements of multi-

disciplinary input which the adaptive design approach requires,

which for example structural engineers and other specialized fields

can provide in case the intent was an integral architectural project.

The early integration and identification of the design phases is

another factor of importance which has been taken into account,

and has been assimilated into the process of this specific study by

the sub-division of the group of collaborators into smaller topic-

focused sub-groups, allowing for inter-communication, the merging

of sub-groups and their re-integration as the design phases evolved;

thus allowing for an organic development, which largely benefitted

the experimental and exploratory nature of the study.

The software, plugins and add-ons chosen for the study inherently

permit inter-program operability and the completeness of metadata

systems. Since they inherently perform via inter-action, inter-

program operability subsequently becomes a fundamental

requirement for the successful implementation of the design tools.

As a consequence the results and processes are mathematically

transparent, mutable and originally created with the intent to be

open-sourced, providing legitimacy in the form of pure data which in

turn is left to the scrutiny of the user; and as long as the user has

some understanding about the mathematical logic behind the

processes, they can use and adapt the system to follow their own

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desired purposes, allowing for the evolutions to occur within a

myriad of fields and backgrounds, not just the architect’s.

Note on the General Approach

Prior to this study the author had only marginal familiarity with the

terms, processes and techniques that ended up encompassing the

adaptive design paradigm. The interest on this topic originated from

the author’s pursuit to filter down the original topic of interest

which comprised of sustainable design through biomimicry;

following the belief that the mathematics inherently embedded in

biological systems could provide the answer for increased energy

efficiency in the built-environment.

Acknowledging this and in order to properly conduct this research,

along with the literary based research, the author took specialized

software courses which allowed for a more tangible glimpse into the

operability that the adaptive design approach seemed to require.

Due to these courses it was found that the potential of the software,

plugins and add-ons fortuitously exceeded the author’s original

expectations, as will be briefly explained in the conclusion chapter

along with other considerations noted for potential further work.

However, because of the time allotment which restricted the

software practise and exploration time, another measure seemed

necessary for the author to achieve the desired level of

understanding and multi-level perspective that a paradigm based

approach requires. This new measure was attained in the form of

the IAAC workshop, which dealt with a closely related theme.

Having then explored, developed and tested the concept proposed

in this thesis within a more abrangent case study and team, the

processes respective to the adaptive design paradigm and approach

could now be more meticulously explored, examined and concluded

through the author’s own criteria, methods, newly acquired

experience and perspective via the preliminary case study example.

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4.2. Case Study Background

As for any architectural endeavour, a starting brief is required in

order to properly orientate and assess the general environmental

influencers on the future design.

4.2.1. Case Study Location and Solar Data Brief

The case study site is located at the top south-east corner of an

Eixample city block (Figure 29) in the El Poblenou neighbourhood at

the Sant Martí district in the city of Barcelona, Spain. The Barcelona

Eixample was drafted by the Spanish urban planner Ildefons Cerdà i

Sunyer, and can be considered the largest solar-planned

neighbourhood in existence; inclusively its history exemplifies the

tension between solar access and developmental needs (De Decker,

2012). El Poblenou stands in an extensive post-industrial district

bordering the Mediterranean sea to the south, Sant Adrià del Besòs

to the east, Parc de la Ciutadella in Ciutat Vella to the west, and

Horta-Guinardó and Sant Andreu to the north (Figure 30); comprised

by an extensive cluster of ex-factories and mostly working class

residential areas. It is technically part of the Eixample (Figure 31)

although the historic centre of the neighbourhood predates the grid.

It is important to note that the site for the final prototype location

was not strategically chosen apart for the ease of accessibility that it

provides for the final testing phase. The non-strategic nature of the

chosen location ultimately benefits the study since the final form

should adapt to any given environment. The orientation based on

urban design and seasonal and solar data have nonetheless been

considered to a greater extent since they can directly influence the

design and its potential energy generating outcome.

However, because of the inherent solar-planned nature of the

Barcelona urban plan, the case study has been inadvertently

benefitted. Measures that lead to improved solar efficiency in the

urban plan will be briefly described since they directly relate to the

holistic nature that the adaptive approach seeks to accomplish.

Figure 29 – Eixample city block, Barcelona; image source: Density Atlas (2011).

Figure 30 - Image displaying the historic centre of El Poblenou and the neighbourhood as part of the Eixample urban plan; image source: Urbanter (2011).

Figure 31 – The Eixample plan presently has an area of 7.46 km2, consists of streets 20 metres wide, intersected by a few boulevards 50 metres wide, and very large city blocks measuring 113 x 113 metres (De Decker, 2012); image source: Density Atlas (2011).

34

As succinctly described by Kris De Decker on an article about the

Solar Envelope: How to Heat and Cool Cities without Fossil Fuels:

Ildefons Cerdà intended to maximize solar access (and

ventilation) to every apartment in four ways. Firstly, he

limited building height to 16 metres (Figure 32) for streets

20 metres wide. Furthermore, he mandated that city blocks

could only be built up on two instead of four sides, either

parallel to each other or in the form of an L (Figure 33). This

enabled the creation of large interior spaces and

introduced sunlight and fresh air at both sides of each

building (Figure 34). Thirdly, all city blocks have truncated

corners, further improving solar access. Lastly, he decided

not to lay the street grid on the cardinal points, but

diagonal to it, this gave all apartments access to sunlight

during the day, while offering all streets shadow

throughout the day (De Decker, 2012).

In addition, Barcelona’s average sunshine duration is 2524 hours per

annum, equating to an average of 72 percent; with the highest

incidence occurring between March and September and the lowest

from October to January (AEMET, 2012).

Barcelona also benefits from a large number of daylight hours if

compared to the rest of Europe. Daylight hours in the northern half

of Europe averages at 1200 to 1800 hours per annum, whereas the

southern half, where Barcelona is located, benefits from an average

of 1800 to 2500 hours per annum and above (AEMET, 2012);

Barcelona in particular averages with 6 to 7.5 daylight hours per day

per annum equating to an average of 2500 plus daylight hours per

annum, as can be verified by Figure 35 (Eurostat, 2009).

Figure 32 – Representation of the Eixample building cross section. Gradually, the laws regarding building height were relaxed, from the original 16 metres to almost 30 metres. However, solar access was retained on all floors of the buildings by placing the top floors further back (De Decker, 2012).

Figure 33 – The Eixample L shaped city blocks layout (De Decker, 2012).

Figure 34 – The Eixample block and resulting solar path (De Decker, 2012).

Figure 35 – Average sunshine hours per day in selected European cities (Eurostat, 2009); a larger version of this image is found in Appendix 5.

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4.2.2. Software Interface, Computing Platform and Materials

The relevant case study software interface qualities, computing

platform and principal materials used in the digital development of

this project and in the construction of the 1:1 scale prototype will be

briefly described in this section.

Software Interface for Morphogenetic Evolution

Software I: Rhinoceros (Rhino) by Mc Neel is a NURBS modeling

software. NURBS is an abbreviation for Non-Uniform Rational Basis

Spline which is a special type of B-spline4 that is described by

complex equations ( Ross, 2010). The software allows for controlled

aesthetically complex designs to be created in very high resolution.

Software II: Autodesk Ecotect Analysis is a concept-to-detail

sustainable building design tool that allows for simulation and

building energy analysis; which include online energy analysis

capabilities in integrating with tools that enable the user to visualize

and simulate a building's performance within the context of its

environment (Autodesk, 2012).

Plugin: Grasshopper created by Scott Davidson is a graphical

algorithm editor and generative modeling tool that is meticulously

integrated to Rhino (Davidson, 2012) and allows for the integration

of selected software, such as Ecotect, to happen through the Rhino

interface whilst allowing the designer to control the integration and

interaction of the software tools as well as potentially expand their

capabilities through the addition of Add-ons.

Add-on I: Geco is a set of components which establish a live link

between Rhino through Grasshopper and Ecotect, exporting,

evaluating and importing data between the programs (UTO, 2012).

Add-on II: Galapagos is an evolutionary solver which provides a

generic platform for the application of evolutionary algorithms to be

used on a wide variety of problems by non-programmers (Rutten,

2010). This add-on is particularly important for this study and its

processes will be described in more detail.

4 - B-Spline is a basis spline; a very smooth curve controlled by three or more control vertices; the more weight a control vertice has, the more the curve is attracted to it, and the sharper the curve bends ( Ross, 2010).

36

Galapagos developer David Rutten produced the plugin so it would

follow five steps in order to achieve an optimized evolutionary

solution, here’s a brief explanation of the embedded processes:

Fitness Function

In evolutionary computation, the fitness function determines the

best outcome to evolve to according to the designer’s parameters.

This allows for great flexibility due to the lack of inhibitors. However,

the fitness landscape can still result in efficient or non-efficient

results.

Selection Mechanism

The artificial selection mechanism, inspired by biological natural

selection, affects the direction of the gene-pool over time by

regulating the genes involved in the evolutionary process. Three

mechanisms are used in Galapagos (Figure 36): with isotropic

selection all genes are allowed to mate5, it dampens the speed with

which a population optimizes and evolves, thus acting as a safe-

guard against a premature colonization of recessive gene traits; with

exclusive selection only the dominant genes are allowed to mate

allowing for multiple offspring; and finally with biased selection the

chances of mating increases as the fitness increases, this last

mechanism has been chosen for the purposes of this study.

Coupling Algorithm

The coupling algorithm determines the process of selection of genes

to mate; and although evolutionary algorithms allow for a wide

possibility of coupling methods, Galapagos currently only allows for

this selection by a process called genomic distance. A single genome

is defined by a number of genes; in order to properly augment the

potential benefits by the evolution of a gene population, the

selected genomes should not present too many similar or dissimilar

traits base on the genome to mate with. The best fit6 distance for

genome differentiation was defined by Rutten and implemented

into Galapagos; simplified graphical representation of it can be seen

in Figure 37.

Figure 36 – Respectively from top to bottom: a graphical illustration of an isotropic, exclusive and biased selection mechanism (Rutten, 2010). 5 - An analogy to wind-pollination or coral spawning styles of reproduction can serve as an example of this type of selection mechanism.

Figure 37 – Graphical representation of a genome map illustrating in green the optimal genome ‘fitness valley’ that will reproduce with the genome circumscribed in red (Rutten, 2010). 6 - In 1993, Mark Burry along with his architectural colleagues from the Universidad Politécnica de Cataluña worked with a set of minima and maxima values making a program iteratively run through potential solutions such that all of the points in our set were tested for conformation to each hypothetical solution, gradually reducing the maxima and minima until finally there would be only one result – the ‘best fit’ (Burry, 2011).

37

Coalescence Algorithm

This is a simplified digital variant of the much more complex

biological process of gene recombination for offspring genotype

formation. Galapagos allows for different process mechanisms to be

implemented (Figure 38): the crossover coalescence mechanism

allows for a completely symmetrical gene switch to occur, without

following any specific gene hierarchy; the blend coalescence

mechanism considers both parent genomes and averages the values

resulting in the offspring genome; and finally, the relative fitness

coalescence mechanism chooses the gene that has the highest

fitness value from either parent genome to generate an offspring

genome based solely on dominant gene traits. This last mechanism

is the one used for this study.

Mutation Factory

This is a crucial aspect for improving resilience within an

evolutionary process in order to reach optimized genotype results.

The aforementioned mechanisms of selection, coupling and

coalescence have been designed to improve the quality of solutions

on a generation by generation basis; however, they also inherently

have a tendency to reduce the biodiversity of a population. By

strategical and controlled addition of alternative genomes from

outside the original fitness gene pool, an increased adaptation is

demanded from the evolutionary process in order to reach the more

relevant or dominant genes, eventually increasing the resilience of

the resulting genotype offspring. Several types of mutation are

available in the Galapagos core, though the nature of the

implementation in Grasshopper at the moment restricts the possible

mutation to only point mutations (Rutten, 2010). A graphical

representation of point mutations can be seen in Figure 39.

Figure 38 – Respectively from top to bottom: crossover coalescence, blend coalescence and relative fitness coalescence mechanisms (Rutten, 2010).

Figure 39 – Respectively from top to bottom: a genome graph representing point mutation, where only a single gene value is changed and inversion mutation which can be useful when subsequent genes have a very specific relationship, however this can be a detrimental operation in most cases since it also drastically modifies the fitness values (Rutten, 2010).

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Software and Platform for Symbiotic Homeostasis

Add-on III: Firefly Firmata is a set of components dedicated to

bridging Grasshopper with an Arduino micro-controller, the internet,

and a variety of remote sensors; by allowing near real-time data

flow between the digital and physical worlds by generating and

reading data synergetically from internet feeds. It also includes a

Cosm reader (Davidson, 2010) which is a secure, scalable platform

that connects devices and products with applications to provide real

time control and data storage (Cosm Ltd, 2012).

Computing Platform: Arduino Uno microcontroller is an open-source

electronics prototyping platform intended for the creation of

interactive objects or environments. It can sense the environment

by receiving input from a variety of sensors and can affect its

surroundings by controlling lights, motors, and other actuators6

(Arduino, 2012).

Case Study Materials

Wood panels, wire cables and heavy duty elastic fabric were used

for the fabrication of the prototype provided by IAAC. For a holistic

analysis of energy efficiency the sources of these materials would

have to be taken into account, however for the purposes of this

preliminary study this data is not particularly relevant.

Previous to this study a number of solar cells were electrically

connected to each other and mounted into photovoltaic panels7 by

IAAC (Figure 40), which were then attached between the wooden

ribs of the 1:1 scale prototype (IAAC, 2012). The energy output in

Watts of the solar panels is not relevant for the preliminary case

study; however this data requires quantification for the proper

development of further stages of the prototype testing. For this

preliminary case study an average of 15 percent efficiency will be

considered in order to quantify the resulting improvement of energy

efficiency by percentage8.

Figure 40 – Front and back of one of the Thin Film Photovoltaic Panels used in the prototype; images: author’s own. 6 - The microcontroller on the Arduino board is programmed using the Arduino programming language (based on Wiring) and the Arduino development environment (based on Processing). Arduino projects can be stand-alone or they can communicate with software running on a computer (Arduino, 2012). 7 - In 2010, IAAC faculty together with Solar Power Co. engineers developed homemade flexible solar panels using Teflon and photovoltaic cells. Thin film photovoltaic solar panels are typically thinner and more flexible, which benefits this study by allowing for better mechanical malleability, although it is not an essential requirement for the purposes of the adaptive design approach. 8 - Thin film solar technology is essentially less efficient than conventional solar panels due to how they are created, reaching between 11 to 22 percent efficiency (SunPower Corporation, 2012). However, comparing the thin-film solar panels by SunPower with their competitors (i.e. First Solar, NanoSolar, and Solyndra), which have average efficiency rates slightly above 10 percent (Ricketts, 2010); a considerable increase in efficiency potential is noted.

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4.3. Case Study Profile

4.3.1. Seed Phase

This phase serves to establish the basic and unchangeable

parameters that will be used to generate the future project and

which inherently contain full development potential.

The parameters that were taken into consideration at the early

design phase for the simulation of an adaptive structure following a

morphogenetic evolution were developed by three distinct team

sub-groups as described in the adaptive design approach section of

this thesis (Figure 41 and Figure 42). Relevant to this case study are

the sustainability related characteristics of this project, which have

been divided into primary and secondary considerations. Primary

considerations for the sustainability aspects are directed towards

energy efficiency, such as the location (so to define the best

orientation) and solar data (the daylight and sunshine hours, which

help guide the initial photovoltaic panel positions); secondary

considerations include how the orientation and relevant solar data

can influence the project’s structure and membrane.

Primary considerations:

The orientation of the photovoltaic facade should face in between

south east and south west in order to increase solar exposure

(Figure 43 and Figure 44). For maximum efficiency the panels should

be placed the closest to a perpendicular angle to the sun as possible,

implying roughly a 30 to 35 degree fixed angle inclination from the

horizontal plane and 90 degrees in relation to the sun.

Secondary considerations:

Only one side of the model will hold the photovoltaic panels, this

helps promote stability and maximizes the area exposed to the sun.

The photovoltaic panels will be attached to the wooden ribs, having

no direct influence on the membrane, due to its lighter and less

stable composition.

Figure 41 – Team of participants; source: workshop participant.

Figure 42 - Group 4 presentation; source: workshop participant.

Figure 43 – Sketches of a participant analysing the structural concept chosen; source: workshop participant.

Figure 44 – Workshop participant Jordi Vinyals demonstrating the potential flexibility of the chosen structure; source: workshop participant.

40

4.3.2. Genotype Phase

The ‘genotype’ phase consists of delineating the limits and values to

which the design should follow by, via user-imposed hierarchy. For

the design to properly achieve symbiotic performance at the later

phases, the parameters to guide the adaptation of the design to the

solar path must be considered. The initial values and exploration

parameters, based on the previous phase criteria and in accordance

to the established hierarchy from the previous phase, define the

limits of the design space to be explored. For this case study they

have been specified as:

The orientation of the facade which holds the photovoltaic panels

faces south west in order to increase solar exposure, whilst also

taking into consideration the site where the prototype will be placed

on and the adjacent shadowing edifications. The four facades which

will hold the photovoltaic panels are designed in Grasshopper

through Rhino and each seek to reach an optimized position in

relation to the sun through parameters set via Geco and Galapagos.

The facades have been programed to twist according to the sun’s

daily path from sunrise to sunset and bend according to sun’s path

thorough two distinct seasons (Figure 45 and Figure 46), for the

duration of a year. Each facade has guidelines so that each of the

nine sensors positioned at the centre of each facade simultaneously

strives to reach the closest to a perpendicular angle to the sun as

possible. Furthermore a daily optimal set of three general positions

(morning, noon and evening) is calculated for each facade,

considering that they are parametrically linked to one another9. The

two solar paths chosen correspond to the months with the highest

sunshine incidence (March and September) and the lowest (October

to January) for Barcelona, as mentioned in a previous sub-chapter.

The operability and completeness of these metadata systems are

tested and verified at this phase via consecutive trial runs, and

adjustments are made until a satisfactory improvement is achieved.

Figure 45 – Plan view of potential twisting movement direction relative to solar incidence in the X and Y axis; source: author.

Figure 46 – Respectively from top to bottom: front elevation view and side elevation view showing potential bending movement direction relative to solar incidence in the Z axis; source: author. 9 - Because of the physical limitations of wood, the twisting motion potentially realized by the facades versus the elasticity of the wood used had to be considered for the simulation; the solution was to link all adjacent facades parametrically and thus minimize the twisting motion.

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4.3.3. Phenotype Phase

The ‘phenotype’ phase selects the observable characteristics and

invariants that may include build history, built-in relationships and

built-in equations. This phase specifies initial results on what the

design will learn about and how it will adapt.

In order to achieve efficient and relevant results, trial runs were

performed in an attempt to streamline the design and results based

on the previous parameters. The first attempts in testing the

design’s solar collection potential comprised of the full facade

(Figure 47). However it was soon realised that a better and more

selective position for the solar sensors could be achieved by locating

them solely at the top of each facade.

4.3.4. Embryogene Phase

The ‘embryogene’ phase allows iterations to be explored via Rhino,

Ecotect, Grasshopper, Geco and Galapagos simultaneously and

within a real time graphically transparent and editable interface

with capabilities to manage geometric relationships, equations and

connect to external design tables if necessary (please see Appendix

6 for software interface screenshots).

In this phase the morphogenetic evolution takes place following the

first adaptive design approach definition. It is in this phase that

consecutive iterations are generated striving to reach the best

optimization possible within the limiting parameters, as established

by the designer in the previous phase. In more detail: 30 generations

were executed via Geco and Galapagos through Grasshopper in

Rhino, for each genotype the number of generations is user defined,

it was found however that 30 generations reached sufficient

optimization for this study (please see Appendix 7 for an example of

the computed results for the first six genomes in generation 1 and

generation 30). Each genotype corresponds to one out of the nine

individual panels (or sensors) for each individual facade (Figure 48

and 50). In total 36 genomes and 1080 generations were computed.

Figure 47 – Graphical representation of the full structure analysis and results for the high (top) and low (bottom) seasons.

Figure 48 - Graphical representation of the analysis for where the solar sensors will be positioned for the high (top) and low (bottom) seasons.

Figure 49 – Graphical representation of the morning (top), midday (middle) and evening (bottom) analysis for the high (left vertical column) and low (right vertical column) seasons.

42

4.3.5. Synthesis Phase

The synthesis phase, the defining system for adaptation or change

and development via performance or software filters is finally able

to be evaluated through the performance of the generated designs

based on a pre-set or comparative performance criterion. The

performance may be evaluated directly from the design table, by

inbuilt evaluation interface tools or by the use of external analytical

software.

Because of the preliminary nature of this study, the data is not

complex enough to need external analytical software in order for it

to be evaluated. The data was collected from the Galapagos internal

species record detail log (an example can be seen in Appendix 7),

and can be evaluated by percentage comparison.

The evaluated results can now be applied to the second adaptive

design approach definition of symbiotic homeostasis for energy

efficient design in the 1:5 finished scale model (Figure 50). For that

to be achieved, one further step is required for the design to

physically and symbiotically adapt to chosen environmental

parameters, such as a location’s solar path data. This step consists of

the implementation of a microcontroller board (Figure 51) which will

direct five remote sensors on the 1:5 scale model (created with the

previous phase dimension parameters), in order to allow for near

real-time data flow between data files and the structural ribs of the

model, allowing it to interact with the data synergetically through

data feeds.

The Arduino Uno microcontroller computational platform is thus

integrated into the 1:5 scale model, along with five RC servo

motors10, each connected to a strategically positioned wire which

can control the rib’s adaptive movements via the Firefly Firmware

and Grasshopper interface (Figure 52 and Figure 53). A sample of

the Arduino control code for this stage can be seen in Appendix 8.

Figure 50 – The 1:5 scale final model and the connections from the model ribs, to the motors and the Arduino controller.

Figure 51 – Respectively from top to bottom: the final 1:5 model, the incorporation of motors to the wooden ‘ribs’ of the model and the integrated Arduino microcontroller board to the motors and electricity source.

Figure 52 – Fritzing illustration of the Arduino Uno board platform, the breadboard, the energy source and an RC servo motor (Arduino, 2012). 10 - Servo motors are output devices which give precise angles of rotation when a right pulsing time is given.

43

Within Firefly, the control of the direction and speed of the

improved servo motor is realized through a positive and negative

block input11 value; adjusting these values allows for the control of

the rotation direction. In the case of this study, the offset value of

zero did not equate to the servo-motor stopping, so an offset value

was calibrated instead. Also, the RC servo motor originally only

allowed for an un-continuous 180 degree rotation; since a 360

degree continuous rotation was required in order to give the wire

proper leeway in reeling in the respective model rib, the internal

potentiometer within the RC servo motor was removed. The timing

and velocity of the rotation can then be controlled by sending a

pulse-width modulation (PWM) value, using microsecond pulses,

based on maximum and minimum conditions, allowing for velocity

controlled forward, still or backward motion.

Furthermore, the connection between the Arduino microcontroller

and a photocell or light dependant resistor (LDR) was made (Figure

54 and Figure 55) in order for the structure to adapt according to

the environmental data being created and broadcasted by the

sensors (following pre-set criteria of maximum and minimum

twisting and bending).

11 - The block input inherits the data type of the upstream block, and internally converts it to data readable to the Arduino.

Figure 53– Schematic illustrating how to set up the positions of a RC servo motor with the Arduino board and a potentiometer (Arduino, 2012).

Figure 54 – Schematic illustrating how to set up the positions of a RC servo motor with the Arduino board and a photocell receptor (Arduino, 2012).

Figure 55 – Fritzing illustration of the Arduino Uno board platform, the breadboard, the energy source and an RC servo motor (Arduino, 2012).

44

4.4. Prototype Testing

By definition simulation research involves controlled replications of

a real world context for the purposes of studying the dynamic

interactions that can occur within that setting, providing real world

information in ways that yield measureable and useful data (Groat &

Wang, 2002). However we remain unable to predict how a building

will ultimately perform based on design-phase building performance

simulations.

Therefore, a 1:1 sized wooden prototype (Figure 56) with thin film

photovoltaic panels (Figures 57) was developed and assembled

based on and up-scaling the 1:5 model inclusively with the Arduino

microcontroller, and a respective scale-based motor (Figure 58 and

Figure 59) , in order to test the outcomes of the IAAC workshop with

real-world materials, structural, wind, gravitational and other loads

and real-time weather based adaptation.

The finished prototype is currently at the test phase at the IAAC

building in Barcelona, where it is being accessed for durability and

performance. Based on the results acquired from these two

parameters, a measure of the holistic level of energy efficiency of

the prototype is able to achieve can be calculated by considering

and calculating the difference between the total input and output of

energy generated and used.

Figure 56 – The 1:1 scale final HelioCell prototype. Photographs of the model and prototype fabrication can be found in Appendix 9.

Figures 57 – Flexible photovoltaic panels were connected to the prototype structure.

Figure 58 – The Arduino boxes at the base of the prototype.

Figure 59 – Electricity transformer, two prepared Arduino boards and the motor.

45

4.5. Observed Results

The results obtained through the preliminary case study as applied

via the Adaptive Design Approach successfully replicate the

theoretical propositions with the simulation results.

Describing the simulation results empirically, an overall increase in

the photovoltaic solar capture capabilities of an average of 20% was

found. This can be verified by the Galapagos Species Record, a

sample of which can be seen in Appendix 7, by comparing the

results obtained from the first generation of genotypes and the last,

showing the improvement in percentages of the increase in the

energy capture capacity that the photovoltaic panels can achieve if

the final structure adapts according to the mechanical evolutions; as

tested and specified for the 1:5 scale model. Furthermore, the

results also described locations which provided less than 50% of the

photovoltaic panels’ full capacity, for these locations it can be

concluded that photovoltaic panels should be omitted. This last

percentage is an example of criteria which can be chosen by the

designer. Ultimately the 20% increase in solar capture result in a

significant improvement of the photovoltaic panels’ output capacity.

The implementation of the Adaptive Design Approach through the

preliminary case study successfully resulted in the culmination of

the principles of morphogenetic evolution and symbiotic

homeostasis for energy efficiency as proposed by the adaptive

design approach; since the final 1:5 scale model, designed through a

generative and optimized evolutionary approach, demonstrated the

capability to mechanically adapt its structure, based on the optimal

solar capture orientation as pre-determined by software

calculations, thus achieving a real-time homeostatic adaptation to

the designer criteria and the outside environment. Furthermore, the

design approach showed significant straightforwardness in the

generation of aesthetically complex designs, their exploration and

testing through the use of the graphical algorithm editors and

object-oriented programming used in this study.

46

5. CONCLUSIONS

This thesis proposed to explore and examine if a design approach

called ‘adaptive’, applied via a generative system, could result in the

improvement of energy efficient design. The term ‘adaptive’ had

dual utilization in this study. The first use refers to a generative

design evolution which adapts according to environmental design

parameters, defined by the author as morphogenetic evolution; and

the second use refers to the real-time physical adaptation of the

design to the actual surrounding environment based on the

previously set parameters, defined by the author as symbiotic

homeostasis.

The application of the adaptive design paradigm into a design

approach was accomplished by defining and explaining the terms of

influence relevant to generative and energy efficient design

methods, properly establishing the base for assimilating the theory,

principles and motives behind the adaptive paradigm, so that it

could be applied as an approach and validated through a case study

able to provide quantifiable results.

This resulted in the proposal of a five phase design sequence

approach, inclusively containing prerequisites and further

considerations that this approach requires. The approach was then

validated by the author by developing, testing, verifying and

explaining the results achieved through a preliminary case study

example; ultimately achieving the desired outcome of increased

energy efficiency through a generative design approach. Inclusively

it was found that the design paradigm for reaching sustainable

architectural solutions is able to respond to the ever morphing

quality of the natural environment and the inert materiality of the

built environment; through holistic integration of these two factors

via an adaptive design approach based on user defined criteria.

The relevant processes and techniques used for this approach,

through the use of specific software and respective plugins and add-

ons such as graphical algorithm editors and object-oriented

47

programming, were researched, critically evaluated and described in

the thesis as well as tested via the case study, demonstrated a great

amount of flexibility for architects to intuitively merge

environmental design solutions with current and emerging

technology and aesthetically complex design.

An added and inherent benefit of using the chosen group of

computer aided design interfaces is the open-source philosophy that

the developers of the software, plugins and add-ons follow by. This

allows for the almost real time integration with global participants

to help in potential problem solving aspects of the project. The

open-source aspect also demonstrated potential in reaching one

important prerequisite for this approach: the early integration of a

multi-disciplinary team of collaborators, which is necessary in order

to properly access and establish the global defining parameters

required for the resulting evolutionary output to prove beneficial in

a holistic sense. Other implications of equally important nature that

resulted from the theory research, as further described in the thesis,

include: the early integration and identification of the design phases,

the operability and completeness of metadata systems, the unified

interaction of design tools and the spontaneity, user accessibility

and legitimacy of results. Furthermore, the architect’s own

authorship also proves to be an essential requirement in the

implementation of the adaptive design approach, since their

definition of preferences, knowledge and aesthetic sensibility

ultimately define the rules by which the evolutionary process will

follow in order to reach the desired design outcome.

The preliminary case study results, which stemmed from the

application of the adaptive design five phase sequence approach,

the corresponding development of an ‘evolved’ or ‘adapted’ design

to the creation of a real-time environment-based adaptable

prototype based on these parameters, ultimately reached a total

average of twenty percent improvement in its photovoltaic solar-

capture performance; where some of the parameters tested that

48

had improvement capability reached ninety-nine percent of their

potential, others reached such low levels that the design

optimization would then result in their omission.

The processes and results obtained from the preliminary case study

also allowed for a glimpse into the further potential of this approach

for a more complete sustainability based analysis. These consist of

the possibility of performing whole-building energy analysis by

calculating the total energy use and carbon emissions of the building

model on an annual, monthly, daily, and hourly basis, using a global

database of weather information; thermal performance analysis by

calculating heating and cooling loads for models and analyse effects

of occupancy, internal gains, infiltration, and equipment; water

usage by being able to estimate water use inside and outside the

building, including cost evaluation; solar radiation by visualizing

incident solar radiation on windows and surfaces over any period in

time; daylighting, which include the analysis of daylight factors and

illuminance levels; and finally, shadows and reflections by displaying

the sun’s position and path relative to the model at any date, time,

and location. The aforementioned analysis comprise of the ones

based on the Ecotect software, thus even greater further potential

could be incorporated into this approach if other software or

engines were to be integrated; an example is an existing real-time

physics based engine for interactive simulation, optimization and

form-finding of structural force analysis1. These are only two

possibilities within a myriad of further design creation and analysis

tools presently available, inclusively, permitting for these outputs to

be analysed in conjunction with or against other outputs such as

societal or for optimized manufacturing capabilities, in one shared

interface environment that is continuously being optimized, whilst

simultaneously providing enhanced creative potential and software

control to the designer.

1 - Through a Grasshopper integrated software engine called Kangaroo.

49

In conclusion, this thesis served to introduce, through theory

research and examples, and examine, through a case study

developed via inter-disciplinary collaboration, if a design approach

called ‘adaptive’, applied via a generative system, could result in the

improvement of energy efficient design. The approach was found to

be successful and although this research was validated through a

preliminary case study and therefore could benefit from further

analysis and testing, it allowed to confirm that at least in the early

design phases, architects can indeed be empowered by these

intuitive tools in order to merge environmental design solutions,

integrated by bio-climatic building protocols, with current and

emerging technology and aesthetically complex design; thus taking

one step closer to fostering a symbiotic relationship between the

natural and built environments. Furthermore, theoretical notes

about possible paths and research potential in the further

development of the Adaptive Design paradigm and approach are

described in the next section of this chapter.

50

5.1. Further work

This is the age of networked intelligence (Tapscott, 2012).

Imagine a machine which could respond to local situations in the

physical environment: a family that moves, a residence that is

expanded, and/or income that decreases (Negroponte, 1969). If this

machine was interpreted as a built form (a building) made of a

number of cells (which could be sectors or rooms), and it reacted in

a way that it adapted its internal settings to accommodate changes

occurred in one or two high energy sectors (rooms requiring energy)

as opposed to low energy ones (rooms temporarily not being used).

At the User Scale

Environmental comfort could be defined by users, where they each

input their preferences on their phone or similar device and the

microcontroller computes the best possible solutions, for example,

the average of all user’s input and/or by user location within the

building. This same logic could be implemented for public spaces

where the input flow from the transient people could be monitored

and serve for the benefit of public administration and infrastructure

management. User preferences and control (which could be

interpreted as components of an environment) is thus inherently

embedded into the built environment.

At the Building Scale

One type of input can be complemented with other types of input.

Consider these: the confluence of a user-defined preferences data, a

building’s real time energy use data, and the building’s real-time

weather file data (based on location and orientation) and the

regional or national goal rules for GHG emission reduction - all

working together to balance the building’s internal environmental

comfort and optimal energy use.

51

At the Urban Scale

If a majority of buildings of a block, per say, were connected to the

same inputs, theoretically they could also have interconnections

between themselves and make use of each other’s inputs in order to

help each other reach the same goal. The same way that if one of

the buildings in this group was struggling to keep up with the

requirements (ex. a historic building or one that has tight retrofit

restrictions or one that was abundantly generating more energy

than it needs) the other interconnected buildings could assist

synergetically in reaching holistic equilibrium for that group.

At the Global Scale

Where energy generation, from the large to the small scale systems,

was interconnected to energy requirements: a better overall energy

distribution could be achieved; cities could grow strategically based

on a number of synergetically linked parameters, including (or

principally) the ones based on locally available energy or natural

resource sources.

At the Interplanetary Scale

The solar system scale has already been partially considered with

the orientation and weather data inputs. We could now go on a loop

back into the singular user on Earth or out into the interplanetary

scale. As Carl Sagan would say “energy is all around; it is what we’re

made of: star-stuff”, or point-cloud based star-dust.

52

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APPENDIX

01. MULTI-SCALAR ENERGY EFFICIENT DESIGN (Reiman Buechner and Crandall, 1983)

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01. MULTI-SCALAR ENERGY EFFICIENT DESIGN continued

(Reiman Buechner and Crandall, 1983).

(Watson & Labs, 1983)

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02. CITY PROTOCOL INFOCHART (City Protocol Org, 2012)

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03. LEED CRITERIA and the CALIFORNIA ACADEMY OF SCIENCES - LEED and Fondazione Renzo Piano

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04. MEDIA ITC, BARCELONA – Cloud 9 Architects

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05. AVERAGE SUNSHINE HOURS PER ANNUM FOR SELECTED EUROPEAN CITIES (Eurostat, 2009)

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06. SCREENSHOT OF SOFTWARE INTERFACE

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07. GALAPAGOS SPECIES RECORD DETAIL

------------------------ Created on: Thursday, 19 July 2012 (17:23:14) Generation 1 { Bio-Diversity: 0.980 Genome [0], Fitness=2731939.32, Genes [81% · 84% · 22% · 60% · 99% · 99% · 100% · 38% · 71%] { Record: Multiple fitness values were supplied; fitness is defined as the average. } Genome [1], Fitness=2327790.77, Genes [80% · 39% · 90% · 83% · 89% · 65% · 88% · 60% · 86%] { Record: Multiple fitness values were supplied; fitness is defined as the average. } Genome [2], Fitness=2182370.92, Genes [37% · 69% · 25% · 89% · 96% · 77% · 63% · 35% · 90%] { Record: Multiple fitness values were supplied; fitness is defined as the average. } Genome [3], Fitness=2171586.80, Genes [92% · 96% · 86% · 28% · 86% · 23% · 79% · 48% · 12%] { Record: Multiple fitness values were supplied; fitness is defined as the average. } Genome [4], Fitness=2128909.91, Genes [43% · 89% · 59% · 13% · 82% · 84% · 83% · 74% · 62%] { Record: Multiple fitness values were supplied; fitness is defined as the average. } Genome [5], Fitness=2097796.06, Genes [39% · 3% · 46% · 56% · 87% · 76% · 51% · 82% · 1%] { Record: Multiple fitness values were supplied; fitness is defined as the average. } Genome [6], Fitness=2036530.44, Genes [85% · 79% · 78% · 86% · 65% · 62% · 48% · 70% · 47%] { Record: Multiple fitness values were supplied; fitness is defined as the average. (…) Generation 30 { Bio-Diversity: 0.023 Genome [0], Fitness=2939875.88, Genes [100% · 97% · 21% · 59% · 99% · 99% · 99% · 39% · 71%] { Record: Point Mutation at index 5: 0.993 -> 0.9986 } Genome [1], Fitness=2934279.42, Genes [99% · 98% · 21% · 59% · 99% · 99% · 99% · 39% · 71%] Genome [2], Fitness=2933979.44, Genes [99% · 98% · 21% · 59% · 99% · 99% · 99% · 39% · 71%] Genome [3], Fitness=2932768.55, Genes [99% · 98% · 21% · 59% · 99% · 99% · 99% · 38% · 71%] Genome [4], Fitness=2931195.85, Genes [99% · 97% · 21% · 59% · 99% · 99% · 99% · 39% · 71%] Genome [5], Fitness=2931183.72, Genes [99% · 97% · 21% · 59% · 99% · 99% · 99% · 39% · 71%] Genome [6], Fitness=2930829.32, Genes [99% · 98% · 21% · 59% · 99% · 99% · 99% · 39% · 71%] { Record: Point Mutation at index 5: 0.993 -> 0.9968 (…)

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08. ARDUINO SAMPLE CONTROL CODE (Arduino, 2012)

------------------------ // Controlling a servo position using a potentiometer (variable resistor) // by Michal Rinott <http://people.interaction-ivrea.it/m.rinott> #include <Servo.h> Servo myservo; // create servo object to control a servo int potpin = 0; // analog pin used to connect the potentiometer int val; // variable to read the value from the analog pin void setup() { myservo.attach(9); // attaches the servo on pin 9 to the servo object } void loop() { val = analogRead(potpin); // reads the value of the potentiometer (value between 0 and 1023) val = map(val, 0, 1023, 0, 179); // scale it to use it with the servo (value between 0 and 180) myservo.write(val); // sets the servo position according to the scaled value delay(15); // waits for the servo to get there }

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09. PHOTOGRAPHS OF MODEL AND PROTOTYPE FABRICATION (Photos by Adrià Goula for DOMUS)

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More information on the HelioCell project at: IAAC SMART itSELF Global Summer School website: http://www.iaac.net/globalschool/2012/ IAAC Blog: http://www.iaacblog.com/blog/2012/iaac-global-summer-school-2012-smart-itself/ DOMUS: http://www.domusweb.it/it/architecture/iaac-heliocell/

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NOTE ON COPYRIGHT AND PERMISSIONS

The use of the HelioCell project which was conceived and developed

at the Institute of Advanced Architecture of Catalonia during the

Global Summer School 2012 SMART itSELF programme as a basis for

the preliminary case study and further studies conducted in this

thesis has been permitted by the IAAC Coordinators Nota Tsekoura

and Areti Markopoulou and by the Oxford Brookes University -

Sustainable Building: Performance and Design Programme

Coordinator Paola Sassi.

Following is the full list of participants which took part in the IAAC

workshop: Aleksandra Chechjotkina, Aline Vergauwen, Arrash

Fakouri, Ayesha Farooq, George Ladurner, Guido Hermans, Jordi

Vinals Terrez, Marc Subirana Ribera, Marina Diez Cascon, Nahal

Fathi, Paula Baptista, Pedram Seddighzadeh Yazdi, Rodion Eremeev,

Veronika Natividade and Zinnur Osman Aytek.

This thesis is licensed under a Creative Commons Attribution-

NonCommercial- ShareAlike 3.0 Unported License. The licensor

permits others to copy, distribute, display, and perform only

unaltered copies of the work and distribute derivative works only

under a licence identical to the one that governs the licensor's work.

In return, licensees must give the original author credit. Licencees

may not use the work for commercial purposes without the

licensor’s permission.

More information on this licence at:

http://creativecommons.org/licenses/by-nc-sa/3.0/legalcode/

ADAPTIVE DESIGN A Generative Energy Efficient Design Approach | MSc Thesis PBaptista

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