AADRL 17/19, Nahmad Bhooshan Studio, Team Oikos

OIKO S

NAHMAD BHOOSHAN STUDIO TUTORS: ALICIA NAHMAD VAZQUEZ SHAJAY BHOOSHAN TEAM MEMBERS: CESAR FRAGACHAN JIANFEI CHU MELIS KUCUKTUNC TAIZHONG CHEN

OIKOS NAHMAD-BHOOSHAN STUDIO 2018-2019 JANUARY, 2019

TEAM MEMBERS CESAR FRAGACHAN MELIS KUCUKTUNC TAIZHONG CHEN JIANFEI CHU

3

4

CONTENTS

CHAPTER 1: INTRODUCTION 9

1.1 AADRL AGENDA 11

1.2 STUDIO AGENDA 1.3 CONTEXT

12 13

2.1 THESIS STATEMENT 2.2 RESEARCH & PRECEDENTS 2.2.1 VERTICAL CITIES

21 25 26 29 32 35 37

CHAPTER 2: THESIS & RESEARCH 19

2.2.2 HOME CUSTOMIZATION

2.2.3 ADAPTABLE COMMUNITIES

2.2.4 CO-LIVING IN LONDON

2.2.5 SELF BUILDING COMMUNITIES

CHAPTER 3: GAME

3.1 GAME PRECEDENTS

6

3.1.1 PALAGONIA 3.1.2 BLOCK’HOOD 3.1.3 THE SIMS

3.2 GAME EXERCISES 3.2.1 GAME THEORY 3.2.2 LEGO GAME

3.2.3 GRID GAME

3.2.4 CREATURE GAME 3.2.5 GAME OF LIFE

3.2.6 SHARE-MATE GAME

3.2.7 COMMUNITY SATISFACTION GAME

3.3 OIKOS GAME 3.3.1 GEOMETRY | PACKING SYSTEM 3.3.2 AGGREGATION ALGORITHM

3.3.3 USER INTERFACE 3.3.4 HOW TO PLAY

3.4 DATA COLLECTION & SIMULATIONS 3.4.1 DATA COLLECTION 3.4.2 PLAYER CLUSTERIZATION 3.4.3 AGENT TYPES 3.4.4 WORK FLOW 3.4.5 AGENT BASED SIMULATIONS

41 45 45 46 47 49 50 54 58 62 66 70 76 84 84 85 86 90 101 102 104 106 108 109

CHAPTER 4: ARCHITECTURAL GEOMETRY 119

4.1 GEOMETRY STUDIES 122

4.2 4.1.1 FORM FINDING 124

4.3 UNIT EXAMPLES 128 4.4 UNIT TYPES 132 4.5 UNIT LIBRARY 136 4.6 UNIT CONFIGURATIONS 138 4.7 FURNITURE CUSTOMISATION 141 4.8 INTERIOR CIRCULATION DESIGN 142 4.9 FACADE ITERATIONS 144 4.10 ASSEMBLY 146 4.11 STRUCTURAL VARIATION 147

CHAPTER 5: DIGITAL FABRICATION

5.1 HOT WIRE CUTTING

161 157

5.1.1 INTRODUCTION 157 5.1.2 PRECEDENTS

158

5.2 PROTOTYPING 5.2.1 END EFFECTOR 5.2.2 PATH PRINCIPLES

5.2.3 PREPARATION OF THE MODEL 5.2.4 WORK FLOW

5.3 ODICO FORMWORK ROBOTICS 5.3.1 3D MODEL

5.3.2 COMPONENTS 5.3.3 SUBDIVISION 5.3.4 CUTTING PROCESS 5.3.5 FINISHES 5.3.6 FINAL IMAGES

5.3.7 DIGITAL WORK FLOW 5.3.8 ON SITE FABRICATION

161 162 164 168 176 185 186 187 188 192 196 200 208 212

BIBLIOGRAPHY & IMAGE REFERENCES

217

7

CHAPTER 1 INTRODUCTION

9

10

INTRODUCTION

1.1 AADRL AGENDA

CONSTRUCTED AGENCY AADRL agenda, Constructing Agency, explores expanded relationships of architecture by considering the future of living, work and culture. The aim of the research to expand the field of possibilities through exploiting behaviour as a conceptual tool in order to synthesize the digital world with the material world.

Advanced computational development is utilised in the pursuit of architectural systems that are adaptive, generative and behavioural. Using the latest in advanced printing, making and computing tools the lab is developing pioneering work that challenges today’s design orthodoxies. Architecture that is mobile, transformable, kinetic and robotic are all part of the AADRL agenda with the aim to expand the discipline and push the limits of design within the larger cultural and technological realm.

11

1.2 STUDIO AGENDA

FUTURE OF LIVING HOUSE.OCCUPANT.SCIENCE.TECH.DATA (HOSTD)

Thomsen et al. 2015 Adriaenssens et al. 2016 3 Anon 2015 4 Reinhardt et al. 2016 5 The guardian 2016; jon earle & irene pereyra n.d.; IKEA 2017 6 Bardakci & Whitelock 2003 7 Chong et al. 2009; Gann 1996 8 Steele 2006 9 Autopoesis of residential community (Schumacher 2002) 1 2

12

The three-year research agenda of the studio, starting from January 2017, is motivated by the following observations regarding contemporary design, fabrication technologies and trends in contemporary living.

1. Digital design and fabrication technologies is maturing with significant progress being made by researchers in the fields of computational architectural design1, computational geometry2, structural design3, robotic manufacture4 etc.

2.

Social, economic and political conditions in large, high-productivity cities such as Tokyo, London, New York etc. have evolved5 such that the market conditions are now suitable6 to engender a demand for mass customised housing.7 The two observations together yield the premise of the research agenda: Developing a real-estate solutions for contemporary living in high-productivity cities are a prime avenue for application of the maturing domain of digital design and fabrication. In other words, the promise made by seminal design research and polemic publications on Mass customisation and housing such as Negotiate my boundary8 and the generation of a vibrant community fabric9, can now indeed be realised.

INTRODUCTION

1.3 CONTEXT Approaching the housing problem has arguably constituted one of architecture’s longest challenges. Many complex dimensions and conflicts are synthesised in the oikos across different scales, from the smallest unit configuration to the macro contextual relationships of the built environment. Adding to the historical challenges of the housing unit London scenario adds several layers of complexity. Along this research we will be focusing mainly in two contrasting conflicts experienced across most people living in London: rent vs own property and single vs shared occupancy.

13

RENTING

BUYING

higher rotation rate affordability

high cost capitalisation

RENTING VS BUYING As housing prices increase yearly in London’s market at a faster pace than average salaries, more and more people are currently turning to the rental market as their housing option. Rental models offer a cheaper option than an owned property and is generally related to a faster rotation rate than the latter as well. On the downside, this model is generally considered a liability over an asset, where there is no personal capitalization and therefore considered a cost over an investment. Most of the time the current rental properties allow very little or no customization possible which in turn fuels the faster rotation of these housing units.

Additionally, these frequently conflicts with healthy community formations since it doesn’t consider neighbouring relationships in time.

On the other hand, owned property constitutes a promising option in terms of investment or capital asset as well as long term stability, customization and economical growth. Yet, as stated above, the housing situation in London is making very difficult if not impossible specially to young professionals to access this type of assets. Additionally, in London, which generally undergoes high migration flows, there is a high demand of rental properties for people aiming to live for relatively short periods of time.

In general, these conditions attract many overseas investors to develop/buy properties in London subsequently renting them. On one hand these investments are well suited not only to them but also to the people who live in them and as an economical contribution to the city. Yet, the alienation of these developers and investor to the society most of the time does not follow a natural growth in healthy community formations and proper home instances.

14

higher privacy higher cost

COLIVING

INTRODUCTION

SINGLE OCCUPANCY

lower privacy lower cost

SINGLE VS SHARED OCCUPANCY London is increasingly being witness of various forms of sharing spaces in housing instances. This situation derives mainly due to increase rent cost across the market spectrum. A great proportion of young professionals and students are renting rooms in larger housing accommodations sharing kitchens and living spaces with flat mates which represent a cheaper option. Generally, this model has several downturns, firstly, it usually does not take into consideration the compatibility between the flatmates and other neighbouring relations, and, it is also dependent on their particular rotation rate, in other words, if one or more of them have to move it usually force the others to do so as well. In a similar model many coliving housing communities are flourishing throughout London. These type of accommodations holds people generally taking into consideration similarities in personal aspects such as relationship status, age and interests. These communities offer a wide range of shared spaces such as kitchens, living rooms, gyms, studios, among others. On the downside, these communities often fix a large number of households per shared space resulting in dissatisfied tenants wanting some privacy or space for themselves. ngle occupancy rents don’t deal with sharing conflicts since privacy is at most respected in their whole living space. As stated above, these type of occupancy is unaffordable by many tenants, but most importantly in many cases it alienates the house holder from a feeling of community and companionship and engaging in acute loneliness feelings affecting the person’s wellbeing.

We could deduce then that different people, each with their own life’s circumstances, have different degrees for willingness to share. This disposition also can relate to personal conditions such as if they are moving with their couple, family and could be determined by their age, i.e. young people tend to socialize and connect with people in their own generations.

15

STANDARDIZATION

affordability mismatch with user preferences

CUSTOMIZATION

high cost one size does not fit all

STANDARDIZATION VS. CUSTOMIZATION Prescripted model where the spatial qualities of a house is predefined. presenting a one-size-fits-all solution that renders obsolete relative to the people’s requirements.

There seems to be a mis-match between homebuyers’ preferences and what the market is providing. Homebuyers’ express a preference for more bedrooms and larger rooms for living and storage. This is perhaps unsurprising, but still represents dissatisfaction with what is being provided.1 By choice of house and areas to live in, and personalization of these in terms of facade, decor, furnishings, etc. the house may psychologically be transformed into a home.2 On the other hand, homebuyers recognise that choice in private housing is limited by affordability, regulation and location.

16

17

18

CHAPTER 2 THESIS & RESEARCH

19

20

THESIS & RESEARCH

2.1 THESIS STATEMENT OIKOS

Among the failures of modern architecture, arguably the most critical has been its inability to address urban complexities. The main reason for this failing has been the perception of an architecture of static: immutable and timeless. Natural organisms have life cycles, so does the built environment. A city can be perceived as an overlay of materialized social dynamics’ frames throughout its history. Moreover, these dynamics change continuously over periods of time as our lives adapt on a daily basis. Our research is interested in adaptive models of living considering changes in social behaviour and specific requirements on a time-based environment.

Social-dynamics shape our communities and they evolve constantly adapting to various factors, i.e. socio-economic, cultural, technological, environmental, et. al. Our living requirements and social dynamics today surely won’t be the same in several years, or even in months or weeks depending in our specific circumstances and our immediate context. We are interested in an architecture that can accommodate changes in these dynamics and a person’s particular circumstances throughout time. Most importantly we are interested in developing an architectural rule-set or by which every person can participate in the design process without affecting the coherence of the overall configuration. In result, we can evaluate how social behaviours emerges from factors such as: public, shared, private, interior and exterior space, lighting and views.

“Many people hope that the new architecture of the minimal will encourage peaceful cohabitation and make social self-regulation processes possible. The prerequisites for this are in place, because dwellings, buildings and settlements will again be designed by the hands of the people who live in them…” 1 Frei Otto

21

“The people can shape buildings for themselves, and have done it for centuries, by using languages which I call pattern languages. A pattern language gives each person who uses it, the power to create an infinite variety of new and unique buildings, just as his ordinary language gives him the power to create an infinite variety of sentences.” 4 Christopher Alexander

Some of these concepts are inherited from Christopher Alexander’s Pattern Language: a system that structures parts, wholes, and the relation with each other and their immediate context. Most importantly, built within this pattern system lies both the means for sharing patterns and the rule sets for generating new ones2. Hence, he refers to this language as an open-source system that holds the patterns which grants life to towns and buildings3 and that should be expanded and adjusted to specific contexts and situations.

Moreover, the rule-set is systematized as a hierarchical decentralized network of relationships. We are interested in evaluating how can the behaviour of a specific group of people engaging under these systemic networks participate in self-organizing communities. The behaviour can be evaluated in a simulated environment where diverse decision-trees account for an organic emergence of communities. Hence, we can analyse it in a “game-theory” framework in which the decisions of every “player” has local and global consequences within the social-networks and the spatial configuration of the system.

The set of actions played out individually in this simulated environment can be framed within Peter Sloterdijk’s vision of the “Foam City” where he describes the co-relations between individuals, each of them co-isolated in the built environment. Sloterdijk states that the behaviour of an individual (illustrated as a monadic cell) within an urban medium determines the configuration of a social -network. The latter corresponding to a composition of bubble like network, accounting for a foam structure by nature dynamic and time-based. Consequently, considering the city’s networks as colliding ego-spheres in foam-like structure, enhances its adaptability thanks to the emergent capability of associative individualities5.

22

THESIS & RESEARCH

Finally, the objective of this research is to structure systems that inherit these properties, accounting for time and social dynamics as shaping agents of architecture. These systems ideally would allow a rich exchange of relations between individuals having a direct impact on the overall spatial configuration of their communities within a specific contextual environment. Ultimately, these bottom-up organizations will accommodate the complexity and diversity of the city through local specificity in hands of its inhabitants.

23

24

THESIS & RESEARCH

2.2 RESEARCH & PRECEDENTS Our research is interested in time-based architectural models of living, consequently, most of our precedents include the fourth dimension as a structural variable. Time plays a structural role, not only in the conception of spaces but, most importantly, on the dynamics that take place within them. The first concept we have looked up to is Vertical Cities, taking reference from Buckminster Fuller’s 4D Tower as an example of ever evolving time based vertical typology that allows future expansion and Kisho Kurokawa’s Nagakin Capsule Tower.

We have studied how communities and living spaces are formed and evolved over time. In this framework, we have focused on two concepts, Self-Building Communities and Adaptable Communities. Some of the projects we have looked up to are: Moshe Safdie’s Habitat 67’, Alejandro Aravena’s Quinta Monroy. German model Baugruppen with two of its examples.

“Many people hope that the new architecture of the minimal will encourage peaceful cohabitation and make social self-regulation processes possible. The prerequisites for this are in place, because dwellings, buildings and settlements will again be designed by the hands of the people who live in them…” 1 Frei Otto

To be able to observe the housing conflicts that are explained in the first chapter, we have studied the organic and unplanned growth of a self-organizing community in the “Torre de David” (David’s Tower) in Caracas, Venezuela under the concept of Adaptable Communities.

Additionally we have studied new ways of living in the 21st century, a new model that is called flat-sharing en-route to home-ownership: ‘Park-Bernstein 100 Ways to Use 100 sqm’. Continuing with the “co-living”, we have critically observed four examples of co-living communities located in London.

Some of these projects and ideas have laveraged on technological leaps in history, and, most of them, have incorporated in their design variables such as flexibility, adaptability, specificity and diversification. These qualities allow them to adapt to change according to the social dynamics played in a time-based environment. Ultimately, we are interested in incorporating some of these concepts and explore their incidence in a design spaces within a computational framework.

25

2.2.1 VERTICAL CITIES

sit relocate relocate inrelocate site in site extend extend vertically vertically add add more more as required asadd required complete complete -transit air-transit air-transit air-transit relocate in site relocate in construction relocate siteinconstruction siteinconstruction site construction construction construction extend extend vertically extend vertically extend vertically add vertically more asmore add required more as add required more as required as required complete complete complete comple

Image 2.2.1: Time dimension of Dymaxion 4D Tower, adding and substructing units.

In his famous Dymaxion 4D Tower, Buckminster Fuller throughout his work explored two simple yet powerful ideas: incorporating the 4th dimension as a structural core of design and a ‘lightful’ construction that would accommodate the former. The Dymaxion 4D Tower project illustrate these concepts in an adaptable structure that can respond to specific needs according to local rules without losing its overall coherence.

This project’s design and structure is flexible to different conditions and requirement. Units can be added or subtracted according to the social dynamics that take place in a specific moment in its life. Each unit is structurally independent from the rest of the system so they can be added or removed without affecting the overall configuration of the complex. Lastly, the 4D Tower is conceived to be ‘moveable’. Fuller presented a structure that could be transported by a vehicle (i.e. an airship) to different sites according to user demands. (Image 2.1.1) All these promising concepts and ideas have yet to be revised and evaluated according to the actual unit and overall structural design. Since units are layered as a ‘cake’, adding and removing units is very limited: only the unit above can be taken out and an additional one can only be placed on the top. Yet, having a separated structure from the units represent an intelligent approach to accommodate changes.

26

Like Fuller’s Dymaxion 4D Tower, the Nakagin Capsule Tower incorporates time as a structural variable. Although, the latter incorporates an additional component worth mentioning: the capability to combine units or ‘capsules’ to form larger spaces when needed. Each capsule is made of off-site and contains a built-in bed and drop-in bathroom unit. Kurokawa’s capsules offers the freedom by minimizing the domestic choices the inhabitant had to make and maximizing the flexibility of the larger organism to accommodate future versions of itself.1

Image 2.2.2: Nakagin Capsule Tower

The building was originally designed as a hotel to provide affordable accommodations, then evolved into a multi-use complex, alternating between varying combinations of hotel, residential, and office uses for the past 35 years.2 This project, similar to the previous one, separates the structure of the complex from the units making change and adaptation more flexible without altering the overall structural integrity. Nevertheless, we found that the original plan of integrating capsules to form larger spaces hardly ever took place along the building’s life period. Most likely, the intended strategy was unsuccessful because units were not flexible given their construction and structural condition: prefabricated concrete boxes. Altering the sides of the capsules must probably is accompanied by high cost and structural compromise.

27

Image 2.2.3: Nakagin Capsule Tower, addition of prefabricated capsules.

28

2.2.2 HOME CUSTOMIZATION

Moshe Safdie’s Habitat 67’ contrasts sharply with the previously described projects. In one hand, this project does not engage with time in its planning and development. Nevertheless, that does not imply that it has not been transformed over time to accommodate its inhabitants’ new ways of living.

From this project we are interested in the spatial qualities of each unit and the overall complex.

Image 2.2.4: Habitat ‘67

Safdie had one beautiful idea in his mind: “for everyone a garden”. Back in time, he reinterpreted the future of living contrasting with Le Corbusier and Mies Van der Rohe’s housing models which he explicitly found “inhuman”.

Safdie’s model defied the traditional apartment units block by approaching each of them as a ‘house’ in a vertical living complex.

The project was constructed entirely of interlocking prefabricated concrete modules that cluster and create living spaces for different needs. The project emerged from a bottom-up design approach that the singular create the collective.3 Fourteen typologies of houses are created by configuring this modules in different ways. (Image 2.1.3) Since this units are load-bearing they cannot be transformed freely. That is a major problem when addressing future transformations as different homeowners have pointed out. Within the “box” spaces have been reconfigured but they are inherently limited to future expansion or reduction.

29

Image 2.2.4: Habitat ‘67, Individual modules stacked and paired, creating a variety of living unit configurations.

30

Greg Lynn envisioned the Embryological House as an interactive system structures by local rules where the user would be able to participate in the ‘creation’ of his domestic space using this computer-based model. It offers a series of a customized house for numbers of users. (Image 2.2.1) The program attended specific needs and requirements laverage on contemporary fabrication processes. The structure was conceived as a flexible system since the house has no ideal or original form, each unit that is customized is unique and individual.4 The system considered not only specific living conditions for its inhabitants but also environmental and contextual relations.

The main problem with Lynn’s prototype was its inability to address further transformations, in other words, it didn’t account Time as a design variable.

These houses were delivered at a ‘custom-size’ personalized solution but could not be expanded or reduced according to changes in life conditions or the rotation of its inhabitants.

Image 2.2.5: Greg Lynn’s Embryological House, Variety of customized units

Image 2.2.6: Greg Lynn’s Embryological House, Variety of customized units

31

prefabr

2.2.3 ADAPTABLE COMMUNITIES

prefabricated compo prefabricated components

prefabricated components

Image 2.2.7: Alejandro Aravena’s Quinto Monroy Housing project, flexible to possible expansion of the houses in time.

With his 100 people housing project Quinta Monroy, Alejandro Aravena has acknowledged time as a shaping factor in sub-urban informal communities.

Most of his social housing projects have introduced this variable in the design scheme allowing transformation to take place as an organic process in these communities. In Quinta Monroy he envisioned a layout where the inhabitants could ‘grow’ or add units to their houses according on their specific needs in time and economical availability. (Image 2.3.2) They could also participate in ‘customizing’ the appearance and façade of their houses since most people in this communities want to differentiate themselves from their neighbours.

Aravena’s model is far from perfect. These housing complexes lack spatial qualities that dignify the spaces and the living conditions of the people they are trying to accommodate. Still, we highlight that his model allows the inhabitants to participate in the design and development process of their houses which has resulted in a very satisfactory solution for them. Additionally, the transformation is played within specific ‘rules’ set by Aravena and his team which allows the complex to maintain its overall coherence and functionality.

32

Diametrically opposed to Aravena’s Social Housing project, the ‘Tower of David’ represent an organic bottom-up example of a community formation.

Taking aside the concerning issues of criminality, unhealthy conditions and vandalism, the growth of this communities constitutes an interesting topic of study for self-organizing communities taken from a visceral social behaviour.

Image 2.2.8: Torre de David, in Venezuela, process growing informal living spaces.

The initial project was conceived as an office tower that would accommodate a local Bank. Due to a banking crisis during the initial stages of the project, the construction of the tower came to a halt and it remained abandoned during several years. On the other hand, socio-economic problems intensified during the new millennium and, in consequence, different people organized to appropriate empty spaces of the city, such as the ‘Tower of David’, to create their own informal communal living spaces.

The development of these informal social systems started with a few houses and rapidly increased to overpopulate the entire structure. Families were adapting the available space to their specific needs in a precarious living condition. It is worth noticing that a social structure emerged alongside the growth of this community where new inhabitants had to pay a “rent” in order to access “public services” such as water, electricity and security, informal by nature.

This development, while polemic, represent an interesting study model of how social-dynamics can participate in structuring communities. The rules by which these behaviours emerge, account for the overall configuration and determine its success. In this the Tower of David, the rules were determined by basic, visceral human instincts, hence, the community that emerged from these dynamics are a reflection and repetition of these relations.

33

1 x 3b5p (three-bedroom five person) flat of 100 sqm

2 x 1b2p flat of 50 sqm

1 x 3b5p (three-bedroom five person) flat of 100 sqm

2 x 1b2p flat of 50 sqm

1 x 2b4p flat of 75 sqm + 1 x 1p studio (or integral bedsit) of 25 sqm

4 x 1p studios of 25 sqm

Image 2.2.9:”100 Ways to On a different scope of adaptable communities, with “100 Ways to Use 100 use 100 sqm model“ offers sqm” Julia Park and Levitt Bernstein’s model proposes flat-sharing en-route to 1 x 2b4pseperations flat of 75 sqm + 1 x 1p studio integral bedsit) 4 x 1p studiosrules. of 25 sqm different in the home(orownership, based on predefined As we stated in the Chapter 1, of 25 sqm house that can accommoa big proportion of young professionals are spending up to 75% of their earndate variety of flats ings in rent. The properties they can afford (leveraging on mortgages) are too

small and inflexible to future growth to become reasonable long-term homes.

The shell is designed to work as one, two, three or four separate homes and house up to five people. (Figure 2.3.3) It can remain whole, or split into halves or quarters to provide. It allows a flexible usage of the space according to the economic status of the owner.5 For example, the latter can acquire his house leveraging on a mortgage while he is renting part of the property to pay for it.

As he capitalizes with the income from his tenant he can increase his “private” or not rented space.

Additionally, the project can address different needs of its inhabitants while remaining flexible enough to adapt to future transformations. Even though people can share, they still retain their privacy. Finally, The project embraces custom build, co-housing, mutual support, multi-generational living and more flexible forms of tenure and temporary housing6 that can accommodate specificity in needs and lifestyles.

34

2.2.4 CO-LIVING IN LONDON In addition to the architectural references, we have explored some models of living where social interactions (i.e. sharing) play an important role in the way spaces are conceptualized. We are interested in developing a co-living model based on local rules where the social dynamics can participate in the spatial configuration of communities and the interactions that occur within them.

“Housing not only provides essential shelter but also gives form to the social.” 7

Co-living as its definition, is not only people sharing rooms, facilities, and services as in flat-sharing; but also unite around a common interest to collaboratively manage a space, share resources, and coordinate activities and encourage interactions. We see co-living as a possible solution to loneliness in big cities, and a respond to the need to feel part of a community. There are now quite a few examples of co-living especially in London.

‘The Collective’, as the world’s biggest co-living building located in London, accommodates 550 people. It has a particular target group of young professionals, which is the majority of the population at the Collective, with a minority that consists middle-aged people and families. Their motto is “connect, collaborate, socialize.”8 Even though the facilities and services are shared, the rent prices are higher than average rent in London, with particularly smaller rooms. They claim, the focus is more on the common rooms instead of private, to encourage interaction between people. We believe what makes co-living successful, and different from any way of flat sharing or student dormitory is the sense of community. It is obvious that Collective offers more convenient lifestyle for its residents, however, some residents believe the sense of community is missing. According to an interview made with the people currently live there, some claimed that majority of residents aren’t interested in meeting with anyone.

While The Collective says they are “constantly working to understand how we can help improve the growth of community.”9 Based on the same article an interview has been made with the residents in ‘Roam’, a 35-people co-living community in Chelsea, London along with the other big cities in the world such as Tokyo, San Francisco. The target group of Roam is composed of professionals, who chooses to work on different locations in the world. The rent prices are significantly higher than average rent in London, almost double the Collective; with relatively small rooms. However as opposed to some of the residents of Collective, the residents in Roam state that they’re satisfied with the co-living, community and “luxurious” facilities Roam offers.

As it is difficult to pinpoint what exactly gives the community feeling to co-living, observing what people who actually lives in the space think may lead to an answer. Residents at the Roam are all people coming from abroad for a few months or a year, professionals with a relatively similar lifestyle or interests, whereas Collective is open and welcoming for wider age range or occupation of people. The scale of two examples are quite different as well; one ac-

35

The Collective Roam Lyvly

Locations in London

The Collective Image 2.2.10: Private to common space ratio, common spaces represented in color.

Roam

Lyvly

commodates 550, the other 35. These two examples are might be the ones that accommodates lower and higher number of people. Numbers of other co-living examples in London offers different range of scale and target group.

One of the other co-living communities in London is “Lyvly”, which focuses on building curated communities. Their motto is “Live in beautiful homes with amazing people.”4 Different from the others, potential residents go through an application process starting with online questionnaire. Residents should be simply met the criteria of over 25 years old, single and a non-smoker. If the application process is successfully completed, users could customize their living space. Lyvly offers stay for comparatively longer than the others, with a contract for 1 - 3 years.

‘Startuphome’, aims for a specific target group of young entrepreneurs who work in technology. It offers to gather these young professionals in the same place for innovation, sharing ideas and diversity. It is co-working and co-researching as much as it’s co-living. It offers many technological services within the complex to fulfil the needs of its specific target group. It has a location in London and Philedelphia, however, it offers a opportunity to grow the startup in other cities. What makes startuphome unique is that any young entrepreneurs can have a chance to be a part of creating a community in other locations.

36

2.2.5 SELF-BUILDING COMMUNITIES The Baugruppen—German for “building groups”—is one model for constructing housing in this future of architect-led, collectively funded community-based living.10 In Germany, where new models for housing have emerged, ones that take ideas about communal living out of the realm of hippie collectives or alt-squats and into the pragmatic territory of pooled finances and homeownership.11

“Housing not only provides essential shelter but also gives form to the social.” 7

R50 Baugruppen project proposes a collective ownership of a co-living, to ease some of the problems of the housing market. For R50, the architects gathered potential residents from their networks. 19 households built the building together: Funds were pooled for construction and the purchase of the plot. Therefore R50 is not only community and living model but also a financing model is that it was designed with the intensive participation of its residents. The architects facilitated the process, starting with the founding of the building group, leading participatory planning and design meetings.

The residents opted to make the ground floor a shared space—sensible given restrictions on locating apartments in the neighbourhood—that includes a double-height community room and laundry facility. (Image 2.2.3) Instead of individual balconies, each floor has a wrap-around collective balcony, each window thus becomes a door to the in-house street, facilitating new lifestyles and new demands.12 (Image 2.2.3) What makes this idea unique is that it proposes a new living model, not co-living where an architect designs the housing and people rent the predefined spaces: R50 Baugruppen is designed by the people who live in. The place is owned by a community, who worked together with the architects through the design process. It proposes communal ownership rather than individual.

It offers a way for more people to act as developers, cooperatively creating buildings and communities.

Image 2.2.11: Private to common space ratio, common spaces represented in color.

37

Image 2.2.12: R50 Baugruppen community room

Image 2.2.13: R50 Baugruppen collective balcony

38

THESIS & RESEARCH

Baugruppen Kurfürstenstraße is a housing project consists of six towers, that overlap themselves, both vertically and horizontally. There are no clear boundaries between the different units/apartments and the structure of the house can be seen as one large single space continuum. This simple principle leads to endless variations of organisation and spatial combinations. (Image 2.5.3) The modular structure allows for a wide range of uses and varying degrees of isolation and openness.13 Some units are also connected to each other by a shared space and they all have a close relation to the inner courtyard garden, shared roof top terraces and other public spaces within the building.

Neither the cohabitation nor the sharing is enforced by the architecture; though the flexibility allows the inhabitants within the building to create their private and shared spaces according to their own special needs.14

Image 2.2.14: Baugruppen Kurfürstenstraße, flexible configuration of the floor plans.

39

40

CHAPTER 3 GAME

41

42

3 GAME

Our research is interested in the behaviour of social dynamics and how, through their understanding, can architecture incorporate them to create spatially rich and adaptable communities to a particular environment. Our initial approach is to play out these behaviours throughout a “spatial game� framework. The set of local actions unfolded by each participant have a direct consequence in the overall spatial configuration and the particular condition of other players.

Mostly we are interested in developing a gaming environment by which we can evaluate the decision-making tree of different agents according to specific parameters. Each game explored has a set of rules, costs and rewards that condition and delimit each player’s move. Ultimately, the actions taken locally by each participant will determine their living space and ill have a positive or negative impact in the condition of other players.

43

44

SOCIAL DYNAMICS

3.1 GAME PRECEDENTS

3.1.1 PALAGONIA The board game Palagonia constitute an interesting example of collaborative yet aggressive game where the behaviour of the players can be framed within a “Game Theory” strategic interaction of rational decision makers.

Players place their units turn by turn in a central pattern aiming to create closed shapes or “creatures “. When a creature is closed, the last player and the previous one score points based on the size and complexity of the shape.

When all the players’ tiles run out, the one with the most points wins.

In this game, the best strategy to achieve a high score creature is to team up with one of your neighbours. Hence, player interaction and decision making are dependent on other players move which constitute an interesting analogy to co-living circumstances.

Image 3.1.1 Palagonia game tiles and an example pattern.

45

Image 3.1.2 Blockhood game

3.1.2 BLOCK’HOOD Block’Hood is an Indie game developed by Plethora-Project on 2016 which promotes players to engage in the development of ecologically balanced neighbourhoods. Every block placed by the player consumes and produces resources of different kinds. If a block does not receive its required input, it will slowly decay to collapse affecting the balance of the community.

The infrastructure created by the player will attract interested inhabitants (agents in the form of people and animals) that will populate the neighbourhood. It is the responsibility of the player to provide a positive environment for the agents to prosper.

The game is based on ideas of ecology and community health exploring the connection between architecture, urbanism and games, “contributing to a form of digital infrastructure for the ecological and systems thinking that is necessary in contemporary urbanism”

46

3.1.3 THE SIMS

Image 3.1.3 The sims house building

The Sims series are a life-simulation games of day to day activities of one or more virtual person or agents (the “Sims“) in a suburban household near SimCity. The player is responsible for creating, controlling, and caring for the life of a Sim. The introduction to online Sims games reveals that the players in these games are encouraged to make choices and fully engaged in an interactive environment. The main objective of the game is to organize the Sims’ time and help them reach their personal goals. However, the life of Sims is not that easy. They require eating, working, sleeping, socializing and also leisure activities.

The game could be defined as a “sandbox game” where the player is freed from traditional video game structure and direction, and instead chooses what, when, and how they want to approach the available content. The term alludes to a child’s sandbox without rules, with play based on open-ended choice. In the Sims case they employ an open world setting to facilitate the player’s freedom of choice.

47

48

SOCIAL DYNAMICS

3.2 GAME EXERCISES The game exercises explained in the following section is a representational game environment played among people in order to observe player behaviours. In these game we have tested different parameters such as game-theory, path-finding, collaborative strategies and cost which feed back and forth our latest iteration of the game.

Starting with the “game theory”, in which we were observing the player behaviour in a competitive environment. Afterwards with the “lego game” we took the game environment to the 3 dimensional space, exploring the connectivity as a representation of physical architectural decisions. In the following games the concept of “sharing” was introduced where the players have to play collaboratively in order to win.

49

3.2.1 GAME THEORY HOW TO START

The game starts with a four colour chessboard representing the territories of four players. The players start at the central points and choose their certain direction to occupy more space.

blue player’s starting point blue player’s territory

HOW TO PLAY

50

Four players starting from the centre, occupy the spaces by growing in two directions. Players take their steps simultaneously each turn. For each of them, occupying others’ territory is more valuable than their own area.

If both of the steps occupy the same square at the same time, none of those two players scores and the square remains empty.

HOW TO WIN

Game finishes when all the area is conquered. The player who conquered the most valuable area in total wins.

51

52

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 1

Red Player: Yellow Player: Green Player: Blue Player:

1 2 1 2

Red Player: Yellow Player: Green Player: Blue Player:

2 3 2 3

Red Player: Yellow Player: Green Player: Blue Player:

3 4 3 4

Red Player: Yellow Player: Green Player: Blue Player:

4 4 4 4

Red Player: Yellow Player: Green Player: Blue Player:

5 5 5 5

Red Player: Yellow Player: Green Player: Blue Player:

6 6 6 6

Red Player: Yellow Player: Green Player: Blue Player:

7 7 7 7

Red Player: Yellow Player: Green Player: Blue Player:

8 8 8 8

Red Player: Yellow Player: Green Player: Blue Player:

9 9 9 9

Red Player: Yellow Player: Green Player: Blue Player:

10 10 10 10

Red Player: Yellow Player: Green Player: Blue Player:

11 11 11 11

Red Player: Yellow Player: Green Player: Blue Player:

13 13 13 13

Red Player: Yellow Player: Green Player: Blue Player:

14 14 14 14

Red Player: Yellow Player: Green Player: Blue Player:

15 15 15 15

Red Player: Yellow Player: Green Player: Blue Player:

16 16 16 16

Red Player: Yellow Player: Green Player: Blue Player:

Red Player: Yellow Player: Green Player: Blue Player:

20 17 17 17

Red Player: Yellow Player: Green Player: Blue Player:

21 18 18 18

Red Player: Yellow Player: Green Player: Blue Player:

Red Player: Yellow Player: Green Player: Blue Player:

23 19 19 22

Red Player: Yellow Player: Green Player: Blue Player:

24 20 20 23

Red Player: Yellow Player: Green Player: Blue Player:

Red Player: Yellow Player: Green Player: Blue Player:

26 22 22 25

Red Player: Yellow Player: Green Player: Blue Player:

27 23 23 26

Red Player: Yellow Player: Green Player: Blue Player:

53

3.2.2 LEGO GAME

54

HOW TO START

The gmae starts with a simple setup. Each player is represented by a color.

The goal is to connect all your initial tiles.

HOW TO PLAY

Players locate their tiles one by one to connect their existing tiles. Players build their new chips on, beneath and by the side of the previews ones. They can connect either horizontally or vertically.

Opponents might block each other’s way. Players may need to go to the upper levels.

HOW TO WIN

The first player who completes the loop wins.

55

56

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

0 0 1 0

Red Player: Yellow Player: Green Player: Blue Player:

1 0 1 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 1

Red Player: Yellow Player: Green Player: Blue Player:

2 1 1 1

Red Player: Yellow Player: Green Player: Blue Player:

2 2 1 1

Red Player: Yellow Player: Green Player: Blue Player:

2 2 2 1

Red Player: Yellow Player: Green Player: Blue Player:

2 2 2 2

Red Player: Yellow Player: Green Player: Blue Player:

3 2 2 2

Red Player: Yellow Player: Green Player: Blue Player:

3 3 2 2

Red Player: Yellow Player: Green Player: Blue Player:

3 3 3 2

Red Player: Yellow Player: Green Player: Blue Player:

3 3 3 3

Red Player: Yellow Player: Green Player: Blue Player:

4 3 3 3

Red Player: Yellow Player: Green Player: Blue Player:

4 4 3 3

Red Player: Yellow Player: Green Player: Blue Player:

4 4 4 3

Red Player: Yellow Player: Green Player: Blue Player:

4 4 4 4

Red Player: Yellow Player: Green Player: Blue Player:

5 4 4 4

Red Player: Yellow Player: Green Player: Blue Player:

5 5 4 4

Red Player: Yellow Player: Green Player: Blue Player:

5 5 5 4

Red Player: Yellow Player: Green Player: Blue Player:

5 5 5 5

Red Player: Yellow Player: Green Player: Blue Player:

6 5 5 5

Red Player: Yellow Player: Green Player: Blue Player:

6 6 5 5

Red Player: Yellow Player: Green Player: Blue Player:

6 6 6 5

Red Player: Yellow Player: Green Player: Blue Player:

6 6 6 6

Red Player: Yellow Player: Green Player: Blue Player:

7 6 6 6

Red Player: Yellow Player: Green Player: Blue Player:

7 7 6 6

Red Player: Yellow Player: Green Player: Blue Player:

7 7 7 6

Red Player: Yellow Player: Green Player: Blue Player:

7 7 7 7

Red Player: Yellow Player: Green Player: Blue Player:

8 7 7 7

Red Player: Yellow Player: Green Player: Blue Player:

8 8 7 7

Red Player: Yellow Player: Green Player: Blue Player:

8 8 8 7

Red Player: Yellow Player: Green Player: Blue Player:

8 8 8 8

Red Player: Yellow Player: Green Player: Blue Player:

9 8 8 8

Red Player: Yellow Player: Green Player: Blue Player:

9 9 8 8

Red Player: Yellow Player: Green Player: Blue Player:

9 9 9 8

Red Player: Yellow Player: Green Player: Blue Player:

9 First!

9 9

Red Player: Yellow Player: Green Player: Blue Player:

10 First!

9 9

Red Player: Yellow Player: Green Player: Blue Player:

10 First!

9 9

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

9 9

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

10 9

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

10 10

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

11 10

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

11 11

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

12 11

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

12 12

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

Third!

12

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

Third!

13

Red Player: Yellow Player: Green Player: Blue Player:

Second!

First!

Third!

13

57

3.2.3 GRID GAME HOW TO START

The game starts with an empty grid. Each player is represented by a color.

Player 1 Player 2 Player 3 Player 4

HOW TO PLAY

58

Players locate the lines on the grid from the boundaries each turn, starting from the corner unit in the grid. If a square is closed by the same color, it becomes their private space.

The private space only forms by closing the four boundaries. Additionally, a square can also be shared by more than one players with different proportions.

Each square space values four points. If players share the square, they also share the points.

4

HOW TO WIN

1

3

2 2

2

1 1

The player who occupies the biggest area wins.

Player 1: 14 Player 2: 15 Player 3: 15 Player 4: 17

59

60

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

1 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

1 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 0 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 0 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1.5 1.5 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1.5 1.5 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1.5 1.5 0

Red Player: Yellow Player: Green Player: Blue Player:

2 1.5 1.5 0

Red Player: Yellow Player: Green Player: Blue Player:

2 1.5 1.5 0

Red Player: Yellow Player: Green Player: Blue Player:

2 1.5 1.5 0

Red Player: Yellow Player: Green Player: Blue Player:

2 1.5 2.5 0

Red Player: Yellow Player: Green Player: Blue Player:

2 1.5 2.5 0

Red Player: Yellow Player: Green Player: Blue Player:

2 1.5 2.5 1

Red Player: Yellow Player: Green Player: Blue Player:

2 1.5 2.5 1

Red Player: Yellow Player: Green Player: Blue Player:

2 1.5 2.5 1

Red Player: Yellow Player: Green Player: Blue Player:

2.75 2.75 2.5 1

Red Player: Yellow Player: Green Player: Blue Player:

2.75 2.75 2.5 1

Red Player: Yellow Player: Green Player: Blue Player:

2.75 2.75 2.5 1

Red Player: Yellow Player: Green Player: Blue Player:

2.75 2.75 3 1.5

Red Player: Yellow Player: Green Player: Blue Player:

2.75 2.75 3 1.5

Red Player: Yellow Player: Green Player: Blue Player:

2.75 2.75 3 1.75

Red Player: Yellow Player: Green Player: Blue Player:

2.75 2.75 3 1.75

Red Player: Yellow Player: Green Player: Blue Player:

2.75 3 3 2.5

Red Player: Yellow Player: Green Player: Blue Player:

2.75 3 3 2.5

Red Player: Yellow Player: Green Player: Blue Player:

2.75 3 4.5 2.5

Red Player: Yellow Player: Green Player: Blue Player:

2.75 3 4.5 2.5

Red Player: Yellow Player: Green Player: Blue Player:

2.75 3 4.5 4.

61

3.2.4 CREATURE GAME HOW TO START

The game starts with an hexagonal grid board with only a few predefined “public� tiles. Each player is represented by a color. Each player starts the game with same amount of variety of tiles. The coloured parts represent the private area and the black parts are the shared space. The black tile is the preset public space.

HOW TO PLAY

Turn by turn, players must locate one of their tiles in preferred rotation, by following three simple rules: Two different colour parts or players can connect only through their shared space, the same colour parts can also connect trough their private space, and shared spaces can connect to the public space.

shared + shared

private + private

62

shared + public

Players create “creatures” by connecting their shard spaces. The objective of the game is to create as much closed “black creatures” as possible, so players have to play collaboratively, but sometime aggressively at the same time.

creatures

HOW TO WIN

Once there is no space to put tiles, the game ends. The scores are calculated by those shared or black space connecting to the closed creatures. The player who has the highest score would be the winner.

63

64

Red Player: Yellow Player: Green Player: Blue Player:

0 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

1 0 0 0

Red Player: Yellow Player: Green Player: Blue Player:

1 1 1 0

Red Player: Yellow Player: Green Player: Blue Player:

3 2 1 3

Red Player: Yellow Player: Green Player: Blue Player:

4 3 2 3

Red Player: Yellow Player: Green Player: Blue Player:

7 5 2 5

Red Player: Yellow Player: Green Player: Blue Player:

7 8 5 5

Red Player: Yellow Player: Green Player: Blue Player:

7 8 5 7

Red Player: Yellow Player: Green Player: Blue Player:

8 9 6 7

Red Player: Yellow Player: Green Player: Blue Player:

9 9 6 9

Red Player: Yellow Player: Green Player: Blue Player:

9 12 8 9

Red Player: Yellow Player: Green Player: Blue Player:

9 12 8 10

Red Player: Yellow Player: Green Player: Blue Player:

9 15 10 7

Red Player: Yellow Player: Green Player: Blue Player:

10 15 10 9

Red Player: Yellow Player: Green Player: Blue Player:

10 17 13 9

Red Player: Yellow Player: Green Player: Blue Player:

13 17 14 10

Red Player: Yellow Player: Green Player: Blue Player:

15 19 14 13

Red Player: Yellow Player: Green Player: Blue Player:

15 20 17 13

Red Player: Yellow Player: Green Player: Blue Player:

17 20 18 14

Red Player: Yellow Player: Green Player: Blue Player:

17 21 19 14

Red Player: Yellow Player: Green Player: Blue Player:

22 21 19 15

Red Player: Yellow Player: Green Player: Blue Player:

22 22 20 15

Red Player: Yellow Player: Green Player: Blue Player:

24 22 20 16

Red Player: Yellow Player: Green Player: Blue Player:

24 23 20 16

Red Player: Yellow Player: Green Player: Blue Player:

26 23 20 17

Red Player: Yellow Player: Green Player: Blue Player:

26 24 21 17

Red Player: Yellow Player: Green Player: Blue Player:

26 24 21 20

Red Player: Yellow Player: Green Player: Blue Player:

26 27 23 23

Red Player: Yellow Player: Green Player: Blue Player:

29 27 25 23

Red Player: Yellow Player: Green Player: Blue Player:

29 28 25 24

Red Player: Yellow Player: Green Player: Blue Player:

30 28 25 24

Red Player: Yellow Player: Green Player: Blue Player:

30 31 26 27

Red Player: Yellow Player: Green Player: Blue Player:

31 31 27 28

Red Player: Yellow Player: Green Player: Blue Player:

31 36 27 34

Red Player: Yellow Player: Green Player: Blue Player:

35 36 29 34

Red Player: Yellow Player: Green Player: Blue Player:

35 38 29 35

Red Player: Yellow Player: Green Player: Blue Player:

40 38 32 35

Red Player: Yellow Player: Green Player: Blue Player:

40 40 32 38

Red Player: Yellow Player: Green Player: Blue Player:

41 41 34 38

Red Player: Yellow Player: Green Player: Blue Player:

41 45 WIN! 37 38

65

3.2.5 GAME OF LIFE HOW TO START

HOW TO PLAY

The game starts with an hexagonal grid board with only predefined “public� tiles. Each player is represented by a color.

For Private Units: 1. Loneliness: If a private unit has no same colour or public neighbour, it dies. 2. Overcrowded: If a private unit has four private neighbours, it converts into a shared unit.

loneliness rule

overcrowded rule

66

For Shared Units: 1. Loneliness: If a shared unit has less than two neighbours, it dies.

2. Overcrowded: If a shared unit has same four private unit neighbours, it turns into a private space.

loneliness rule

overcrowded rule

HOW TO WIN

The player who occupies the biggest area wins.

67

68

Red Player: Yellow Player: Blue Player: Green Player:

0 0 0 0

Red Player: Yellow Player: Blue Player: Green Player:

1 0 0 0

Red Player: Yellow Player: Blue Player: Green Player:

1 1 0 0

Red Player: Yellow Player: Blue Player: Green Player:

2 1 1 1

Red Player: Yellow Player: Blue Player: Green Player:

3 2 2 2

Red Player: Yellow Player: Blue Player: Green Player:

4 3 3 3

Red Player: Yellow Player: Blue Player: Green Player:

4 4 4 4

Red Player: Yellow Player: Blue Player: Green Player:

6 5 5 4

Red Player: Yellow Player: Blue Player: Green Player:

6 4 5 5

Red Player: Yellow Player: Blue Player: Green Player:

7 5 5 5

Red Player: Yellow Player: Blue Player: Green Player:

7 5 6 5

Red Player: Yellow Player: Blue Player: Green Player:

7 5 6 7

Red Player: Yellow Player: Blue Player: Green Player:

8 6 6 7

Red Player: Yellow Player: Blue Player: Green Player:

8 6 7 6

Red Player: Yellow Player: Blue Player: Green Player:

9 6 7 7

Red Player: Yellow Player: Blue Player: Green Player:

9 7 8 7

Red Player: Yellow Player: Blue Player: Green Player:

10 7 8 7

Red Player: Yellow Player: Blue Player: Green Player:

10 8 9 7

Red Player: Yellow Player: Blue Player: Green Player:

11 8 9 9

Red Player: Yellow Player: Blue Player: Green Player:

11 9 9 8

Red Player: Yellow Player: Blue Player: Green Player:

10 9 10 8

Red Player: Yellow Player: Blue Player: Green Player:

11 9 10 9

Red Player: Yellow Player: Blue Player: Green Player:

11 10 10 9

Red Player: Yellow Player: Blue Player: Green Player:

11 10 11 9

Red Player: Yellow Player: Blue Player: Green Player:

11 10 11 10

Red Player: Yellow Player: Blue Player: Green Player:

11 11 11 10

Red Player: Yellow Player: Blue Player: Green Player:

12 11 12 10

Red Player: Yellow Player: Blue Player: Green Player:

12 11 12 11

Red Player: Yellow Player: Blue Player: Green Player:

13 12 12 11

Red Player: Yellow Player: Blue Player: Green Player:

13 12 13 11

Red Player: Yellow Player: Blue Player: Green Player:

13 10 13 12

Red Player: Yellow Player: Blue Player: Green Player:

14 10 13 11

Red Player: Yellow Player: Blue Player: Green Player:

14 11 14 12

Red Player: Yellow Player: Blue Player: Green Player:

15 11 14 12

Red Player: Yellow Player: Blue Player: Green Player:

15 12 14 12

Red Player: Yellow Player: Blue Player: Green Player:

15 12 15 12

Red Player: Yellow Player: Blue Player: Green Player:

15 12 15 13

Red Player: Yellow Player: Blue Player: Green Player:

17 12 15 13

Red Player: Yellow Player: Blue Player: Green Player:

17 13 15 13

Red Player: Yellow Player: Blue Player: Green Player:

17 12 16 14

69

3.2.6 SHARE-MATE GAME OBJECTIVE

The objective of the game is to accumulate as much “points” as possible, so players will have to play collaboratively and aggressively depending on their particular situation. We are interested in evaluating players’ willingness to share introducing an economic factor of cost and reward.

The board is predefined as a starting scene. The subdivision is related to a packing system of truncated octahedrons (see chapter 4). Hexagonal areas are potential public spaces that can be activated during the game with exception of the centre one which is activated at the beginning of the game acting like the seed or the future development of moves.

HOW TO START

As with the creature game, three types of tiles representing how much people is willing to share also assigning different cost structures to each of them. The grid incorporates an initial public space which can be related to the vertical circulation.

shared space private space

one-shared-space unit private space

two-shared-space unit

game board

70

three-shared-space unit

HOW TO PLAY

Instead of having a fixed tile, some rules has been assigned to represent where the shared space can be incorporated since they are also related with the circulations of the space horizontally and vertically.

A cost is needed each time when a unit is placed. Players get points once their shared units are completely closed. cost

reward

£ 4000

£ 5000

£ 3000

£ 5000

£ 2000

£ 5000

As stated before, each tile has a different cost structure.

A player who is willing to share less (1 tile) will cost more than a player that is willing to share more (directly related to the amount of private space that it can access).

71

HOW TO PLAY

P1: £ 5000 P2: £ 5000 P3: £ 5000 P4: £ 5000

P1: £ 3000 P2: £ 5000 P3: £ 5000 P4: £ 5000 1

P1: £ 3000 P2: £ 2000 P3: £ 5000 P4: £ 5000

2

P1: £ 3000 P2: £ 2000 P3: £ 1000 P4: £ 5000 3

P1: £ 8000 P2: £ 2000 P3: £ 1000 P4: £ 2000

4

P1: £ 9000 P2: £ 5000 P3: £ 5000 P4: £ 7000 5

6

The game requires that players start related to a public or a shared space.

Player must connect through their shared spaces as well. The peripheral hexagonal tiles are potential shared or public spaces that are trigger or activated only when at least three players connect a shared space to it. Players only get reward points when their shared wishing potential has been fulfilled.

shared + public

72

Potential shared space converts into the public space get activated if at least three neighbours connect to it.

shared + shared

HOW TO WIN

Players earn points every time their shared units are completely closed.

The player who accumulates as much “points� as possible wins. Players earn points every time their shared units are completely shared.

73

74

Red Player: Yellow Player: Blue Player: Green Player:

£ 5000 £ 5000 £ 5000 £ 5000

Red Player: Yellow Player: Blue Player: Green Player:

£ 3000 £ 5000 £ 5000 £ 5000

Red Player: Yellow Player: Blue Player: Green Player:

£ 3000 £ 3000 £ 2000 £ 5000

Red Player: Yellow Player: Blue Player: Green Player:

£0 £ 3000 £ 7000 £ 3000

Red Player: Yellow Player: Blue Player: Green Player:

£ 5000 £ 5000 £ 5000 £ 8000

Red Player: Yellow Player: Blue Player: Green Player:

£ 5000 £ 5000 £ 5000 £ 9000

Red Player: Yellow Player: Blue Player: Green Player:

£ 3000 £ 5000 £ 5000 £ 9000

Red Player: Yellow Player: Blue Player: Green Player:

£ 3000 £ 3000 £ 5000 £ 9000

Red Player: Yellow Player: Blue Player: Green Player:

£ 8000 £ 3000 £ 2000 £ 9000

Red Player: Yellow Player: Blue Player: Green Player:

£ 8000 £ 3000 £ 2000 £ 6000

Red Player: Yellow Player: Blue Player: Green Player:

£ 4000 £ 3000 £ 2000 £ 6000

Red Player: Yellow Player: Blue Player: Green Player:

£ 14000 £ 3000 £ 2000 £ 6000

Red Player: Yellow Player: Blue Player: Green Player:

£ 14000 £0 £ 2000 £ 6000

Red Player: Yellow Player: Blue Player: Green Player:

£ 14000 £0 £ 7000 £ 6000

Red Player: Yellow Player: Blue Player: Green Player:

£ 14000 £ 5000 £ 5000 £ 6000

Red Player: Yellow Player: Blue Player: Green Player:

£ 14000 £ 5000 £ 10000 £ 7000

Red Player: Yellow Player: Blue Player: Green Player:

£ 11000 £ 10000 £ 10000 £ 7000

Red Player: Yellow Player: Blue Player: Green Player:

£ 11000 £ 8000 £ 10000 £ 12000

Red Player: Yellow Player: Blue Player: Green Player:

£ 11000 £ 8000 £ 7000 £ 12000

Red Player: Yellow Player: Blue Player: Green Player:

£ 11000 £ 8000 £ 7000 £ 9000

Red Player: Yellow Player: Blue Player: Green Player:

£ 8000 £ 8000 £ 7000 £ 9000

Red Player: Yellow Player: Blue Player: Green Player:

£ 13000 £ 5000 £ 7000 £ 9000

Red Player: Yellow Player: Blue Player: Green Player:

£ 13000 £ 5000 £ 4000 £ 9000

Red Player: Yellow Player: Blue Player: Green Player:

£ 13000 £ 10000 £ 9000 £ 14000

Red Player: Yellow Player: Blue Player: Green Player:

£ 13000 £ 15000 £ 9000 £ 15000

Red Player: Yellow Player: Blue Player: Green Player:

£ 10000 £ 15000 £ 9000 £ 15000

Red Player: Yellow Player: Blue Player: Green Player:

£ 10000 £ 12000 £ 9000 £ 15000

Red Player: Yellow Player: Blue Player: Green Player:

£ 10000 £ 17000 £ 10000 £ 15000

Red Player: Yellow Player: Blue Player: Green Player:

£ 10000 £ 17000 £ 10000 £ 12000

Red Player: Yellow Player: Blue Player: Green Player:

£ 7000 £ 17000 £ 10000 £ 12000

Red Player: Yellow Player: Blue Player: Green Player:

£ 12000 £ 17000 £ 15000 £ 17000

Red Player: Yellow Player: Blue Player: Green Player:

£ 12000 £ 14000 £ 15000 £ 17000

Red Player: Yellow Player: Blue Player: Green Player:

£ 12000 £ 14000 £ 16000 £ 17000

Red Player: Yellow Player: Blue Player: Green Player:

£ 12000 £ 14000 £ 16000 £ 18000

Red Player: Yellow Player: Blue Player: Green Player:

£ 8000 £ 14000 £ 16000 £ 18000

Red Player: Yellow Player: Blue Player: Green Player:

£ 18000 £ 14000 £ 21000 £ 18000

Red Player: Yellow Player: Blue Player: Green Player:

£ 18000 £ 10000 £ 21000 £ 18000

Red Player: Yellow Player: Blue Player: Green Player:

£ 18000 £ 10000 £ 22000 £ 18000

Red Player: Yellow Player: Blue Player: Green Player:

£ 18000 £ 10000 £ 22000 £ 19000

Red Player: Yellow Player: Blue Player: Green Player:

£ 18000 £ 10000 £ 22000 £ 19000

75

3.2.7 COMMUNITY SATISFACTION GAME OBJECTIVE

The game’s final objective is to maximize the Player’s Satisfaction in relation to the respective “Available Points” (initial budget).

Each player’s satisfaction values are unique, based on their willingness to have private or shared spaces; as well as views, lights and terraces.

UNIT COST

1500 points

1000 points

Bigger unit costs more than the smaller one.

1500 + 750 points

76

UNIT PLACEMENT

public space

initial unit

Initial units should be connected to the public space.

Players can grow their living area both horizontally or vertically.

SHARED SPACES

Players can decide whether to expand their Living Area spending less resources (Available Points) by sharing. Each unit can potentially share with other two units.

77

VERTICAL PLACEMENT

UNIT COST

If a player decides to place his next unit above his own property, then a vertical spatial relation will take place between and create double height space. Players might have different satisfaction values for double-height spaces.

Every unit is aware of how much “light” or open space it has immediately surrounding it. Depending on how much neighbors it has a unit might range from feeling “lonely” to overcrowded and asphyxiated and a player’s satisfaction will be affected in consequence.

penalized

Light on 1 side: 10 pt Light on 2 sides: 20 pt (optimum) Light on 3 sides: 10 pt Light on 4 sides: 10 pt No light: -100 pt (penalized)

78

CREATING PUBLIC SPACE

If there are three units around a hexagonal space, it becomes a public space.

This spaces account for general circulation around the complex and/or different public uses of interest to the inhabitants (gym, kitchens, lounges, gardens, etc.).

If there are enough neighbours around, the public place gets “activated.�

OVERCROWDED PUBLIC SPACE

A public space can accommodate up to five (5) living units surrounding it.

Since these spaces are by nature public, it must be accessed at least by one side from the exterior.

Public space cannot be completely surrounded by the private units.

79

SCENIC VIEWS

80

Every scene in the simulated environment shows a particular set of elements that correspond to a “scenic view” which increases the player’s satisfaction according to their specific value.

PRIVATE TERRACES

Each unit is conscious of its surroundings, it can perceive if a private terrace or garden is available to it. Each player can adjust his personal degree of value toward this feature.

81

82

83

3.3 OIKOS GAME 3.3.1 GEOMETRY | PACKING SYSTEM

Site

Potential Grid

Potential Packing

84

1

1

1

2

2

3

1 2

3

34

4

3

1 3

1

4

1

2

2

2

3

3

4

2 OWNED RENT

1 2

1

1 2

3

MAXIMUM 3 4 CHILD

1 2

3

3.3.2 AGGREGATION ALGORITHM

GROWTH DIRECTION

1

MAXIMUM 2 NEIGHBOURS

GROWTH 3 4 DIRECTION

3

MAXIMUM 2 CHILD

MAXIMUM NEIGHBOURS OWNED RENT

1

3

1

1 2

1 2

3

4

3

2

3

4

2

OWNED RENT

circulation

circulation

private

private

circulation

circulation

private

private

circulation

circulation private

circulation

circulation private

privatecirculation

private

circulation

private

circulation

private

1 circulation

private

circulation

1

private circulation

circulation private

4

privateprivate

1

private

1

2 circulation circulation3 3

circulation

private

circulation circulation

priv

circulation

2

private

3 1

3 4 privateprivate

1

2 3

2

2 3 circulation circulation

4

2

OWNED RENT OWNED RENT

1

1 2

3

3

GROWTH 2 DIRECTION

4

1

MAXIMUM CHILD

1 2

MAXIMUM NEIGHBOURS

GROWTH 3 4 DIRECTION

3

MAXIMUM 2 CHILD

MAXIMUM NEIGHBOURS

OWNED RENT

1

1 2

3

1 2

4

rivate

1

3 2

3

3

4

2 OWNED RENT

circulation

circulation

private

private

circulation

private

circulation

private

circulation

circulation

private

private

circulation

circulation circulation

private private

private

circulation

private

circulation

circulation

OWNED RENT

circulation

private

private

private

circulation

circulation

circulation

private

private

circulation

circulation

private

private

private

circulation

85

pri

3.3.3 USER INTERFACE The game starts with a welcome screen where the players can add their details.

These details will be later used in the game interface, to represent different players. The information given on the welcome screen will be shared by the other players in the game.

Welcome screen

The players will be assigned an avatar according to their gender, age range and household choices, for other players to simply identify one another.

SINGLE MALE

SINGLE FEMALE

AGE: 18-35

AGE: 35-60

AGE: 60+

Avatars

86

COUPLE

FAMILY (WITH KID/S)

GAME INSTRUCTIONS

In the user interface of the VR, information about the players are located on the left hand corner, such as player name

Player information

When the controller is pointed to a unit, player can see the information about that room on the corner of the UI.

Room information

87

Players can see example units on the left controller. This suggests variety of unit configurations for each function of the room.

Sample room references Sample living room hologram

When the player chooses the function with the left controller, he can place that function of the room with the right controller. Therefore the sample hologram works as a reference when placing a room.

Placing a function to the room

88

Placing a living room

GAME INSTRUCTIONS

Players can set their satisfaction value to indicate that how much they are happy with that current situations of their homes, quality of their spaces and sharing conditions. This data will be saved in each turn to understand the decisions of the player.

Adjusting the satisfaction value Satisfaction: 79

Satisfaction: 33

The satisfaction of the player will appear next to its avatar. This value will also affect the community health.

Satisfaction bar

Satisfaction bar appears next to the avatar of the player

89

3.3.4 HOW TO PLAY STEP 1:

INSTANTIATING A NEW SEED & PLACING UNIT First step in the game is to instantiate private unit grid which is connected to the public circulation unit.

TIP: The cost for attaching different faces of the public unit may differ; i.e the face with the view is more valuable than others.

Attaching a face of the public unit

Instantiating a private unit grid

90

Instantiating a private unit grid

Every virtual unit is evaluated by their structural position and assigned a cost value accordingly. The cantilevered units would cost more as they need extra structure below. The cost of each unit is updated and could change based on the neighboring conditions.

GAME INSTRUCTIONS

UNIT COST

40 points

10 points

TIP: The cost for putting units to different parts of the grid may differ, according to the view, lighting and level (height) properties.

High cost unit

Medium cost unit

Low cost unit

91

STEP 3:

PLACE A ROOM AND ITS FUNCTION Players can buy more than one units and combine them as they want.

TIP: Players can combine the units for bigger rooms.

Combination of three units

Addition of units.

92

CUSTOMIZE THE ROOM

After placing the room, players can customize their room. They can take off walls/windows. Change the arrangement of the furniture.

GAME INSTRUCTIONS

STEP 4:

TIP: Players can take off the interior walls to create bigger spaces, exterior walls to create windows.

Customization of walls and windows

Taking of walls/furniture blocks

Customization of a room

93

STEP 5:

SHARING SPACES Players can share their spaces with other players. They simply show the community that they are willing to share by changing the color of their room.

Click the unit: Opening up for sharing Shared space

94

GAME INSTRUCTIONS

The community can recognize the sharing space from its color. If they like the player and the space, they can request sharing.

Request sharing Sharing request

The sharer will be informed by the request. More than one player can send sharing request at the same time. Sharer needs to click yes or no.

TIP: Players should make sure that you are offering something in return. If you have another room to share, sharers most likely to accept your request.

Accepting/Declining the sharing request Accepting sharing request

95

STEP 6:

RENT Players can rent their unused units or invest to buy a unit then put it to rent in the game.

TIP: Players can earn points by renting their units.

Renting the unit

Room for rent

96

CUSTOMIZING INTERIORS

Players can customize the interior of their units by simply carving out the blocks. These virtual furniture blocks will then translate into an architectural design.

GAME INSTRUCTIONS

STEP 7:

Customizing furnitures

97

80 PLAYER GAME PLAY

98

99

100

DATA & SIMULAITIONS

3.4 DATA COLLECTION & SIMULATIONS An important dimension in our research is the collection of data gathered from the players in the various game iterations being played out. Each of our players can be interpreted as multidimensional individuals whose actions determine the overall configuration and health of the ecosystem in which they are immersed. These actions can be directly correlated to the “Game Theory” interaction and furthermore mapped into a multidimensional space. It is quite challenging then to manually find correlations between these datasets, moreover, impossible to visualize it as hundreds of dimensions would be required.

We are leveraging on dimensionality reduction techniques in the form of machine learning algorithms to compute this task and find proper correlations between the data. Specifically, we have been exploring t-Distributed Stochastic Neighbor Embedding or TSNE algorithms, a probabilistic technique well suited for visualizing high dimensional datasets. “t-Distributed stochastic neighbor embedding (t-SNE) minimizes the divergence between two distributions: a distribution that measures pairwise similarities of the input objects and a distribution that measures pairwise similarities Wof the corresponding low-dimensional points in the embedding”. In other words, the algorithm runs through the original data and tries to represent the output in a low-dimension space (2 or 3), by matching both distributions.

101

To further engage in this process, we had to organize the data by player taking into considerations not only demographic and personal qualities such as age, relationship status, interests, but most importantly, we are interested in the actions that have a direct incidence (directly or indirectly) in the overall community.

3.4.1 DATA COLLECTION

PROFILES

First dimension of the data, demographic and personal qualities are collected by the welcome screen of the game.

- Age - Gender - Interests -Occupancy

102

GAME ACTIONS

This dimension of data is collected from the actions of players during the game, regarding the decisions of physical properties of their homes.

- Number of rooms - Their functions - Sizes of rooms - Positions of rooms - Furnitures of rooms - Green spaces

SOCIAL DECISIONS

This level of data is collected from the actions of players during the game, regarding the further decisions on social aspects.

- Share/not to share - Who to share with - Renting

DATA & SIMULAITIONS

Specifically, we are collecting data regarding actions such as property type (rented or privately owned) by space (i.e. living room, kitchen, bedroom and bathroom) and occupancy level (single occupancy or collectively shared) also by space.

SATISFACTION

Another important layer of the data is that if the players are satisfied with their actions.

- Satisfaction

103

3.4.2 PLAYER CLUSTERIZATION

Low-dimensional data visualization

104

We started testing this data work flow with an 80-player game iteration. The output is mapped into a three-dimensional space showing different correlations between players in the form of clusters.

DATA & SIMULAITIONS

The algorithm is clustering similar players to in this case 4 types.

Low-Dimensional Data Visualization Rent Own Single Occupancy Co-living Single Couple Family

Type A Type B Type C Type D 105

3.4.3 AGENT TYPES

106

According to the clusterization, we will refer to the types as student, freelancer, family and investor. Such as student having low budget but high tendency to share, family requiring more number of units. Type D, what we call investor is a profile who buys multiple units and rent to other players.

DATA & SIMULAITIONS

3.4.4 WORK FLOW

107

80

85

27

74

72

51

46

3.4.5 AGENT BASED SIMULATIONS

AGENT TYPES

80

%25 INVESTOR %75 STUDENT

108

80

Average Satisfaction

80 72

80

80 40

85 46

72

38

35

Shared Units

80 40 38

Rented Units

80 85 46 35

Structure

AVERAGE SATISFACTION

72 27 10 33 SHARED UNITS

8040

80 85 46

72 27 10

51 74 25

RENTED UNITS

8085

27 72

5174

42 46

STRUCTURE COST

72

51

46

39

109

Agent Types

Average Satisfaction

Shared Units

Rented Units

AGENT TYPES

80

72

38

35

80

40

46

10

80

85

27

74

80

72

51

46

EQUAL MIX OF 4 TYPES

110

`

` Agent Types

Average Satisfaction

AVERAGE SATISFACTION

80 Agent Types

Average Satisfaction

72 Shared Units

SHARED UNITS

80

nt Types

Average Satisfaction

80 72 Shared Units

40 38 Rented Units

RENTED UNITS

80

age Satisfaction

80

80 40

85 46

72

38

35

Shared Units

Rented Units

Structure

STRUCTURE COST

72

80 40 38

85 80 46 35

27 72 10 33

8040

80 8546

72 27 10

51 74 25

80

111

85

80

85

27

74

72

51

46

AGENT TYPES

80

%25 INVESTOR %75 STUDENT

112

80

Average Satisfaction

80 72

80

80 40

85 46

72

38

35

Shared Units

80 40 38

Rented Units

80 85 46 35

Structure

AVERAGE SATISFACTION

72 27 10 33 SHARED UNITS

80 40

80 85 46

72 27 10

51 74 25

RENTED UNITS

8085

72 27

5174

46 42

STRUCTURE COST

72

51

46

39

113

80

72

38

40

46

80

85

27

80

72

51

AGENT TYPES

80

%50 INVESTOR %50 FAMILY

114

80 Agent Types

Average Satisfaction

72 Shared Units

AVERAGE SATISFACTION

80 80

Agent Types

Average Satisfaction

72 Shared Units

40 38 Rented Units

SHARED UNITS

80

erage Satisfaction

80

80 40

85 46

72

38

35

Shared Units

Rented Units

Structure

RENTED UNITS

80 72

80 40 38

80 85 46 35

72 27 10 33

STRUCTURE COST

80 40

80 85 46

72 27 10

51 74 25

8085

72 27

5174

46 42

115

116

117

118

CHAPTER 4 ARCHITECTURAL DESIGN

119

120

4 ARCHITECTURAL DESIGN

The design approach to the housing units is informed not only by the game decisions of each player but also by the fabrication technology. We are leveraging the latter in robotic hot wire cutting techniches and further exploring the realm of ruled surfaces. We have been exploring from efficient packing eomteries to libraries of joints systems, facades and furniture configurations that allow specificity and customization of the units giving hundreds of variations with a finite amount of components at the hand of each “player�.

121

4.1 GEOMETRY STUDIES

Perspective packing number: 22 level count: 9 maximum unit count:: 198

Units connect others through six directions. Each hexagon surface is a possible interface of two units except the top and the bottom one, which are potential floors for public space. An aggregation of the units has varies levels as well as an adaptive shape.

Plan packing number: 22 level count: 9 maximum unit count: 198

122

packing number: 1 level count: 4 maximum unit count: 9

packing number: 2 level count: 5 maximum unit count: 18

packing number: 3 level count: 6 maximum unit count: 27

packing number: 4 level count: 6 maximum unit count: 36

packing number: 5 level count: 6 maximum unit count: 45

packing number: 6 level count: 7 maximum unit count: 54

packing number: 7 level count: 7 maximum unit count: 63

packing number: 8 level count: 8 maximum unit count: 72

123

4.2 FORM FINDING: SOAP FILM EXPERIMENT We sectioned the base geometry (truncated octahedron) with three equivalent planes and developed our frame. We observed and analyzed the behaviour of soap tensile surfaces along the structural setting while air was introduced in different points of the system. The result of the experiment helped us develop our subdivision strategy within the packing system.

Soap film experiment, to analyse the subdivision of the possible floor plane.

124

We also explored ways in which units can share spaces to accomodate the social dynamics explored in the “game� environment. Changes in the configuration of these spaces constitute a challenge to be addressed afterwards in the construction and fabrication system.

ARCHITECTURAL GEOMETRY

4.2 FORM FINDING: SURFACE RELAXATION

By taking reference from the form finding process we come up with a library of rooms, following the shape of the packable geometry. The library of rooms are combined with double height spaces only shows 8 of the possibilities.

However the architecture allows various combinations.

125

126

127

4.3 UNIT EXAMPLES LIVING UNIT EXAMPLES GAME REPRESENTATION FURNITURES

128

WALLS/WINDOWS

KITCHEN & DINING UNIT EXAMPLES GAME REPRESENTATION FURNITURES

WALLS/WINDOWS

129

BEDROOM EXAMPLES GAME REPRESENTATION FURNITURES

130

WALLS/WINDOWS

BATHROOM UNIT EXAMPLES GAME REPRESENTATION FURNITURES

WALLS/WINDOWS

131

4.4 UNIT TYPES

132

133

134

135

4.5 UNIT LIBRARY GAME REPRESENTATION

Kıtchen Unıt

Bedroom Unıt

136

ARCHITECTURAL DESIGN

Bathroom Unıt

Offıce Unıt

137

4.6 UNIT CONFIGURATIONS

138

2 units

4 units

6 units

8 units

10 units

12 units

139

140

4.7 FURNITURE CUSTOMISATION

141

4.8 INTERIOR CIRCULATION DESIGN

Interior circulation located at the center of the geometry

Entrance

142

ARCHITECTURAL GEOMETRY

Interior circulation atrium

143

4.9 FACADE ITERATIONS

144

145

4.10 ASSEMBLY

Bent Wood Facade Component

Furniture Blocks

Wooden Flooring

Structural Joints

146

Mechanical, Electrical & Plumbing

4.11 STRUCTURAL VARIATION

Gradient structural variation Customized for the position and the weight it carries

147

148

149

150

151

152

CHAPTER 5 DIGITAL FABRICATION

153

154

5 DIGITAL FABRICATION

An important dimension of our research account for new fabrication technologies that could reduce the gap between the virtual or digital design and the physical manufacturing. Whith such tools we could stand against economies of scale and address the housing problem as specific and customizable as possible.

Mainly we are developing a language of ruled surfaces given by robotic hot wire cutting which informs the formal design of the housing units. The components are constrained to robotic and material limitations yet constitute a promising opprotunity for the AEC sector.

155

156

DIGITAL FABRICATION

5.1 HOT WIRE CUTTING 5.1.1 INTRODUCTION

Robotic hot wire cutting has been a research topic throughout many years.

Recently the company Odico has lead the commercial application and development of this technology outside of the academic research and has showed case its qualities in the construction industry.

Though many materials can be cut following zero-gaussian curvature (or ruled-surfaces) we have narrowed our research in Expanded Polystyrene (EPS) blocks. The positive shape acquired through the robotic path correspond to the formwork in which concrete will be later casted or shotcreted.

Robotic HWC techniques uses generally a straight heated nichrome wire of high resistance. This informs and determine the formal design into ruled surface or zero-gaussian curvature geometry, as the ruled surface is achieved by smooth sequence of straight line section across the geometry. Ruled surfaces designs in architecture have already been exploited in creating complex architectural geometries. An iconic example is the masterful work of Antoni Gaudi n his ongoing masterpiece: la Sagrada Familia.

However, the wire can be also shaped to research beyond the ruled surfaces and to explore more geometrical possibilities. Ongoing research in non-straight cutting using multiple robots is currently being developed which could open the spectrum of formal possibilities by this technique.

157

5.1.2 PRECEDENTS

Image 1.2.1: Kirk Kapital Headquarters Vejle, Denmark Odico & Olafur Eliasson

Image 1.2.2: Mathematics: Winton Gallery, Design Museum, RHWC concrete benches Odico & ZHCODE 158

DIGITAL FABRICATION

Robotic Hot-wire cutting (RHWC) utilizes a robotically controlled, electrically heated wire to cut through industrial foams, replicating the geometry by a given CAD-model. The process enables us to produce complex geometry formwork for concrete casting and foam based elements for industrial applications. We can do this at a fraction of the time and cost associated with the implementation of pre-existing technologies. Foam cut-off and used formwork can be recycled for new insulation products or formwork material, enabling a highly sustainable production cycle.

With the completion of this technology, on the back of 8 years of academic and industrial research, Odico has pioneered a global breakthrough for architectural robotics – large-scale construction application for RHWC. Danish-Icelandic artist Olafur Eliasson has completed his first building shaped by wire cutting geometry – a fortress-like office in the Vejle Fjord in Denmark, called Fjordenhus. Fjordenhus is the headquarters of Kirk Kapital, which is the holding and investment company for three brothers who are direct descendent of the founder of Lego. But it also features a publicly accessible ground floor.

It is the first building entirely designed by Studio Olafur Eliasson, which has previously collaborated on architectural projects including the Harpa concert hall in Reykjavík and the Serpentine Pavilion 2007 in London, and built smaller structures including the Cirkelbroen bridge in Copenhagen. The building’s geometric form is made of four intersecting circles. Each of these cylinders has voids carved out of them, which are circular at one end and elliptical at the other. Partially glazed, arch-shaped openings are also cut from these volumes. Built around a concrete structure, the building’s inner and outer walls are built from 970,000 bricks. The artist chose 15 different hues of unglazed brick, along with blue, green and silver glazed bricks. Each of the external facades has a different combination of bricks depending on the light that it will receive, with the glazed blue bricks used more frequently near the base and blue bricks more often at the top of the building.

159

160

DIGITAL FABRICATION

5.2 PROTOTYPING WORKSHOP We have been developing our architectural language through the use of this technique. Mainly the housing units are composed by the configuration of customized prefabricated joints assembled and casted in-site.

A customized hot wire end effector was designed and assembled for the task reaching error tolerances of less than a milimeter in a one to one scale.

Additionally a customized workflow was developed accross different software platforms so the unit configurations set by the social simulation of the game can be processed in real time by the robot paths.

161

5.2.1 END EFFECTOR

Autodesk BUILD Space ABB IRB 6700 245 300

End effector design

162

Top view

Front view

Side view

24

24

24 42 27

83

2

33

83

27

83

83

16

3

8

89

8

89

51

83

83

9

1 14

82

82

82

End effector components

163

5.2.2 PATH PRINCIPLES

End effector coordinates

164

Path plane sequence

Cutting path

165

166

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

167

494

181

60

181

689

788

689

788

382

5.2.3 PREPERATION OF THE MODEL

876

30

30

181

60

181

49

682

49

329

464

382

01_G

329

494

682

788

181

60

382

181

53

876

494

464

181

60

168

Dimensions

464

689 30

788

689

788

30 876

181

49

682

49

329

382

3

53

382

169

170

1

2

3

4

5

6

7

8

9

10

11

12

171

172

173

174

175

5.2.4 WORK FLOW GENERAL WORK FLOW

DATA COLLECTION

Players Unity

Game

Machine Learning

Visual Studio

Data Grasshopper

Translation

DIGITAL WORKFLOW

Rhino

Classification Grasshopper

Path Construction Machina Robotstudio

PHYSICAL WORKFLOW

Data Streaming

176

Simulation

Robot

Fabrication

Robot Calibration Material Setup

DATA COLLECTION

Players

Game

Machine Learning

Data

177

DIGITAL WORK FLOW

Translation

Classification

point list

plane construction

Path Construction

178

path list

path construction

PHYSICAL WORK FLOW PERS tooldata WireCutter := [TRUE, [[0,0,1245],[1, 0, 0, 0]], [12,[0, 0, 622.5],[1,0,0,0],0,0,0]]; CONST speeddata vel20 := [20,20,5000,1000]; CONST speeddata vel100 := [100,20,5000,1000]; CONST zonedata zone2 := [FALSE,2,3,3,0.2,3,0.2]; PROC main() ConfJ \Off; ConfL \Off; ! Tool “WireCutter” attached ! [Attach tool “WireCutter”] ! [Set precision radius to 2 mm] ! [Set TCP speed to 100 mm/s] MoveL [[640.089, -2308.828, -79.91], [0.000339, -0.011964, 0.999928, 4E-06], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [640.089, -2308.828, -79.91] mm and rotate to [X:[-1, -0.024, -0.001], Y:[-0.024, 1, 0], Z:[0.001, 0, -1]]] MoveL [[640.089, -2090.828, -79.91], [0.000339, -0.011964, 0.999928, 4E-06], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [640.089, -2090.828, -79.91] mm and rotate to [X:[-1, -0.024, -0.001], Y:[-0.024, 1, 0], Z:[0.001, 0, -1]]] MoveL [[639.112, -2074.746, -79.77], [0.0004, -0.018919, 0.999821, 8E-06], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [639.112, -2074.746, -79.77] mm and rotate to [X:[-0.999, -0.038, -0.001], Y:[-0.038, 0.999, 0], Z:[0.001, 0, -1]]] MoveL [[638.106, -2058.685, -79.63], [0.00046, -0.025808, 0.999667, 1.2E-05], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [638.106, -2058.685, -79.63] mm and rotate to [X:[-0.999, -0.052, -0.001], Y:[-0.052, 0.999, 0], Z:[0.001, 0, -1]]] MoveL [[637.072, -2042.647, -79.49], [0.000519, -0.032627, 0.999467, 1.7E-05], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [637.072, -2042.647, -79.49] mm and rotate to [X:[-0.998, -0.065, -0.001], Y:[-0.065, 0.998, 0], Z:[0.001, 0, -1]]] MoveL [[637.072, -2042.606, -82.832], [0.000511, -0.032674, 0.999466, 1.7E-05], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [637.072, -2042.606, -82.832] mm and rotate to [X:[-0.998, -0.065, -0.001], Y:[-0.065, 0.998, 0], Z:[0.001, 0, -1]]] MoveL [[637.073, -2042.565, -86.174], [0.000503, -0.032722, 0.999464, 1.6E-05], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [637.073, -2042.565, -86.174] mm and rotate to [X:[-0.998, -0.065, -0.001], Y:[-0.065, 0.998, 0], Z:[0.001, 0, -1]]] MoveL [[637.073, -2042.524, -89.517], [0.000496, -0.032769, 0.999463, 1.6E-05], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [637.073, -2042.524, -89.517] mm and rotate to [X:[-0.998, -0.066, -0.001], Y:[-0.066, 0.998, 0], Z:[0.001, 0, -1]]] MoveL [[637.532, -2058.607, -89.714], [0.000529, -0.025935, 0.999663, 1.4E-05], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [637.532, -2058.607, -89.714] mm and rotate to [X:[-0.999, -0.052, -0.001], Y:[-0.052, 0.999, 0], Z:[0.001, 0, -1]]] MoveL [[637.962, -2074.722, -89.912], [0.000562, -0.018999, 0.999819, 1.1E-05], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [637.962, -2074.722, -89.912] mm and rotate to [X:[-0.999, -0.038, -0.001], Y:[-0.038, 0.999, 0], Z:[0.001, 0, -1]]] MoveL [[638.364, -2090.869, -90.11], [0.000596, -0.011964, 0.999928, 7E-06], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [638.364, -2090.869, -90.11] mm and rotate to [X:[-1, -0.024, -0.001], Y:[-0.024, 1, 0], Z:[0.001, 0, -1]]] MoveL [[638.364, -2308.869, -90.11], [0.000596, -0.011964, 0.999928, 7E-06], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [638.364, -2308.869, -90.11] mm and rotate to [X:[-1, -0.024, -0.001], Y:[-0.024, 1, 0], Z:[0.001, 0, -1]]] MoveL [[615.791, -1853.459, -29.027], [-0.034028, -0.12145, 0.992005, -0.004166], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [615.791, -1853.459, -29.027] mm and rotate to [X:[-0.968, -0.241, 0.069], Y:[-0.241, 0.97, 0], Z:[-0.066, -0.017, -0.998]]] MoveL [[697.796, -1866.028, 207.47], [-0.021745, -0.090797, 0.99563, -0.001983], [0,0,0,0], [0,9E9,9E9,9E9,9E9,9E9]], vel100, zone2, WireCutter\WObj:=WObj0; ! [Transform: move to [697.796, -1866.028, 207.47] mm and rotate to [X:[-0.983, -0.181, 0.044], Y:[-0.181, 0.984, 0], Z:[-0.043, -0.008, -0.999]]] ENDPROC

Data Streaming & Simulation

Fabrication

179

180

181

3 ARCHITECTURAL ASSOCIATION DIGITAL PROTOTYPING LABORATORY

Scale of the model is optimized according to the reach of the robot and size of the EPS blocks.The model is composed of 22 components.

182

183

184

DIGITAL FABRICATION

4 ODICO FORMWORK ROBOTICS We have collaborated with Odico Formwork Robotics Company in Odense, Denmark to develop advanced robotic hot wire cut and robotic abrasive wire cutting prefabricated components for the housing units. During November 2018 we have spent 3 weeks at the factory and built real scale prototype of an iteration of a living unit with 50 components.

185

4.1 3D MODEL

186

4.2 COMPONENTS

6 main components of the prototype are consists of structural elements, wall envelops and a furniture block.

187

4.3 SUBDIVISIONS

The components are subdivided according to optimum use of foam blocks and the degree of its curvature. The component on the left is composed of 38 pieces.

188

189

190

191

4.4 CUTTING PROCESS

Robotic Abrasive Wire Cutting

192

193

Robotic Hot Wire Cutting

194

195

4.5 FINISHES

Step 1: Acrylic One As a first step of the finishing one coat of acrylic one is applied to the foam surfaces. The ratio of the mixture is 1 unit of acrylic one powder to 1.3 unit of resin.

196

Step 2: Paste When the acrylic one coat is dry, one thin layer of paste was applied to the surfaces.

197

Step 3: Sanding After waiting the paste to dry for a day, the surfaces are sanded to have a smooth finishing.

Step 4: Final Layer of Acrylic One When smooth surfaces are achieved, one more layer of acrylic one mixture is applied the last time.

198

Step 5: Painting Finally, all surfaces are painted with 3 layers of water-based white paint.

199

4.6 FINAL IMAGES

200

The sample furniture block

The entrance

201

202

203

204

205

Texture achieved by hot wire cutting

206

207

DIGITAL WORK FLOW

Players

Unity

Game

Machine Learning

Agentbased Simulation

Grasshopper

Visual Studio

Data DATA PROCESS

208

RobotStudio Translation Simulation

Rhino

Classification

Grasshopper

Robots

Path Construction

Fabrication

Machina

.CSV

Data Streaming DATA COLLECTION

209

Material Set-up

Factory On The Fly

Schedule

Industrial Supports OFF-SITE PREPARATION

210

Robotic Hot Wire Cutting

Frame Work Concrete

Concrete Casting

Structural Components

Pasting

Finishing

Customisation

Construction

Furniture

211

ON SITE FABRICATION

Robotic cutting

Framework

Casting concrete

212

213

214

215

216

BIBLIOGRAPHY & IMAGE REFERENCES

217

218

REFERENCES

CHAPTER 1: INTRODUCTION 1 2

Greater London Authority, “Housing space standards.” A Report by HATC Ltd for the Greater London Authority (2006), 8.

Judith Sixsmith, “The meaning of home: An exploratory study of environmental experience.” Journal of environmental psychology 6, no. 4 (1986), 282.

CHAPTER 2: THESIS & RESEARCH 1 2 3 4 5

Frei Otto and Bodo Rasch, Finding Form (1995),15.

Molly Wright Steenson, Architectural Intelligence (2017), 49.

Christopher Alexander, The Timeless Way of Building (1979), 212.

Christopher Alexander, The Timeless Way of Building (1979), xi.

Catalina Ionitas, Foam City (2015), 8.

CHAPTER 3: SOCIAL DYNAMICS SIMULATIONS 1 2 3 4 5

Frei Otto and Bodo Rasch, Finding Form (1995),15.

Molly Wright Steenson, Architectural Intelligence (2017), 49.

Christopher Alexander, The Timeless Way of Building (1979), 212.

Christopher Alexander, The Timeless Way of Building (1979), xi.

Catalina Ionitas, Foam City (2015), 8.

219

IMAGE REFERENCES

CHAPTER 1: INTRODUCTION Image 1.3.1: Greater London Authority, “Housing space standards.” A Report by HATC Ltd for the Greater London Authority (2006), 8.

CHAPTER 2: THESIS & RESEARCH Image 2.2.4: Habitat ‘67. Spyropoulos, Theodore, Adaptive Ecologies: Correlated Systems of Living. Architectural Association, 2013, 77.

Image 2.2.12: R50 Baugruppen community room, ttp://www.metropolismag.com/architecture/residential-architecture/dont-call-it-a-commune-inside-berlin-radical-cohousing-project/, Accessed April 14, 2018.

Image 2.2.13: R50 Baugruppen collective balcony, ttp://www.metropolismag.com/architecture/residential-architecture/dont-call-it-a-commune-inside-berlin-radical-cohousing-project/, Accessed April 14, 2018.

CHAPTER 3: SOCIAL DYNAMICS SIMULATIONS Image 3.1.1: Palagonia game tiles and example pattern, https://boardgamegeek.com/ boardgame/69578/palagonia Image 3.1.2: Block’hood game, https://www.plethora-project.com/blockhood/ Image 3.1.3: Sims game, https://www.game.co.uk

220

BIBLIOGRAPHY Alexander, Christopher, Sara Ishikawa and Murray Silverstein. A pattern Language: Towns, Buildings, Construction. New York: Oxford University Press, 1977.

Alexander, Christopher. The Timeless way of Building. New York: Oxford University Press, 1979.

Bergdoll, Barry, and Peter Christensen. Home delivery: fabricating the modern dwelling.

The Museum of Modern Art, 2008 Catalina Ionitas, Foam City (2015) https://pa.upc.edu/...catalina/.../CI_Foam%20city Greater London Authority, “Housing space standards.” A Report by HATC Ltd for the Greater London Authority, 2006.

Griffin, Jo. The Lonely Society. The Mental Health Foundation. 2010.

June 14, Kurfurstenstrase Building Group, Accessed March 8, 2018. http://june-14. com/2018/building-group-kurfurstenstrase/ Maak, Niklas. “Post-familial communes in Germany.” Harvard Design Magazine: architecture, landscape architecture, urban design and planning 41 (2015) Metropolis Magazine, “Don’t Call It A Commune: Inside Berlin’s Radical Cohousing Project”. Accessed April 14, 2018. http://www.metropolismag.com/architecture/residential-architecture/dont-call-it-a-commune-inside-berlin-radical-cohousing-project/ New London Architecture. New Ideas for Housing. NLA Insight Study, 2015 Otto, Rasch. Finding Form. Edition Axel Menges 1995 Phillips, Andrea and Fulya Erdemci. Actors, Agents and Attendants. 2010.

Sixsmith, Judith. “The meaning of home: An exploratory study of environmental experience.” Journal of environmental psychology 6, no. 4. 1986.

Spyropoulos, Theodore, Adaptive Ecologies: Correlated Systems of Living. Architectural Association, 2013 Wright Steenson, Molly. Architectural Intelligence. Cambridge, Massachusetts: MIT, 2017

221