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Dwell.t Own Nothing, Access Everything: Time-based dwelling.

Robotically woven, lightweight timber structures for infill sites in high density cities.

Leo Bieling | Basant Elshimy | Ariadna A. Lopez


Architectural Association School of Architecture Design Research Lab 2017 Design Research Agenda: Constructing Agency Tutors: Shajay Bhooshan | Alicia Nahmad Team: Leo Bieling Basant Elshimy Ariadna Lopez www.dwell-t.com mail@dwell-t.com


Table of Contents


01_Own Nothing. Access Everything 1.1 Hybrid Typology: Hotel+Home 1.2 Housing for Transient Communities 1.3 Design Methodology Feedback Loop

Dwell.t Own Nothing, Access Everything: Time-based dwelling. Robotically woven, lightweight timber structures for infill sites in high density cities.

02_Objectives 2.1 Building Transient Communities 2.2 Data Driven Spatial - Customisation 2.3 User Path Simulation 03_Threads of Investigations 3.1 Primitive Game: Intersections and Interactions 3.1.1 Seminal Projects: Dimensional Metrics of Interactions 3.1.2 Co-living Neufert 3.1.3 Intrinsic Rules 3.1.4 Extrinsic Rules 3.1.5 Evaluative Metrics 3.1.6 Time-use Occupancy Simulation 3.2 Architectural Geometry: 3D Graphic Statics 3.2.1 Seminal Projects: Form-finding Diagram 3.2.2 Primitive to Architectural Geometry Transformation 3.2.3 Outcome Evaluation 3.3 Digital Fabrication 3.3.1 Seminal Projects: Wood Bending and Architectural Models 3.3.2 Digital Timber and 3D Robotic Weaving Process 3.3.3 Structural Tests 04_Digital Timber and 3D Robotic Weaving Prototyping Workshop 4.1 22-Node Proposal 4.2 Timber to Nylon Fabrication Process 05_References 6.1 Bibliography 6.2 Image Credits


Own Nothing. Access Everything.


1.1 Hybrid Typology: Hotel+Home

Dwell.t is a new model of living stemming from the social phenomenon of the subscription model. Its purpose is to build a community fostered and served by technologies of spatial customisation in a dynamic, diverse urban setting like London. Catering to the dynamic lifestyle of both visitors and residents, the basis of the thesis is “Own Nothing. Access Everything” (Figure 1.1.1). 1.1.1 Hotel to Home The current challenge is constructing a new model of living which prioritises social and spatial principles. Relevant examples of co-housing developments include: • The Collective in London. • The Amalgamated Housing in New York (Figure 1.1.2)

Own Nothing

Access Everything

The Dwell.t fabrication methodology undertakes techniques of wood bending similar and robotic weaving similar to: • The plywood chairs of Charles and Ray Eames (1.1.3). • The research pavilions developed by ICD / ITKE (1.1.4).

Figure 1.1.1: The basis of the thesis, “Own Nothing. Access Everything” provides a lens to investigate how communities may be fostered and served

The research aspires to yield a hybrid typology between a hotel and a residence (Figure 1.1.5). The proposal targets infill sites dispersed through East - Central London as a strategy to cope with unaffordable land prices.

by technologies of spatial customisation in a dynamic and diverse urban setting like London. Cooperative living: Membership-based corporation or cooperative which owns real state. Each member is legally regarded as a shareholder with the right to occupy a housing unit. Alternative cooperative arrangements include communes and student Figure 1.1.1

10

_1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel

accommodations.

1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel_

11


1.1.2 Co-living Community The primary motivations are: • To build a unique community, situated amongst contemporary models of subscription living such as Airbnb (Figure 1.1.7). • To construct an architectural manifestation for the transient community of visitors and residents in London, to facilitate social and cultural exchange between distinct user profiles.

• Temporary access • Shared spaces • City visitors • On-demand • Cyclical usage

Although it offers a quicker, more comfortable solution to many travellers than a conventional hotel, challenges with the Airbnb model include: • People find it difficult to have ever-changing neighbours as it removes any potential for interaction or community building. • Not spatially customised to the user’s needs. The advantages of community building in an urban context include:

• Knowledge and skill exchange between different age and social groups.

• Short term visitors can experience the authenticity of the city and •

culture through their interactions with their neighbours. Long term visitors can become exposed to a wider range of cultures.

Dwell.t

• On-demand • Distributed

functions of living

• Spatial

customization

Figure 1.1.2: Photograph of the Amalgamated Housing Cooperative in the Bronx, New York. Built in 1927 for industrial workers and their families, the spatial planning and location are tailored to the

• Privacy • Personalised • Permanent

Figure 1.1.2

residents

prospective residents. Figure 1.1.3: Charles and Ray Eames Plywood chair prototype sets a powerful precedent for lightweight bent timber fabrication (1945). Figure 1.1.4: ICD/ ITKE Research Pavilion, woven out of carbon fibre filaments. Figure 1.1.5: The aim of Dwell.t is to create a subscription based architecture

Figure 1.1.3

12

_1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel

Figure 1.1.4

that is a hybrid between Figure 1.1.5

residential and hotels.

1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel_

13


1.1.3 User Experience A mobile application is an essential part of creating a customisable, smooth user experience. Through the application, users can: • Select the aggregation most suited to their needs. • Sign up for Dwell.t. • Check-in • Check-out • Make payments • Potentially give information about their movement through the aggregation. This is data used to update the spaces to better suite the users needs and facilitate interactions. Check-in to Check-out User Experience Step 1: Download the Dwell.t mobile application. Step 2: Create a profile and answer some questions: Name Age Personal ID number Occupation Payment details Step 3: Receive unique membership bar code Step 4: Locate nearest premise Reserve private unit (held for 30 minutes) Step 5: Check-in by swiping unique bar code Access unit and all amenities and services (user behaviour data is collected during this time)

Figure 1.1.6

Step 6: Check-out by swiping given bar code Credit card is charged based on number of minutes and type of unit selected.

Figure 1.1.6: A simple graphic user interface similar to what might be used by Dwell.t.

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_1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel

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1.1.3 User Behaviour Patterns The second motivation of the thesis is to use technology of data driven design-based spatial customisation to better facilitate interactions between users. Dwell.t proposes data analysis as a tool to make informed inferences on user behaviour patterns, which then drive spatial organization and qualities. The research makes use of an electrical survey conducted by the UK government in 2012, which tracks 260 households in order to obtain detailed information of household usage (UK Gov, 2012). The data is analysed and categorised in order to identify User Behaviour Pattern (UBP). (Figure 1.1.8). The UBP are used to simulate usage cycles for both visitor and resident profiles. The two case studies in this category are: • A project conducted at the MIT Media Lab “Pattern Recognition and Analysis” course. The objective of this analysis was to develop machine learning algorithms that would respond to realtime human activities collected from sensor data throughout test homes (Figure 1.1.9) (Mungia Tapia et al, 2017). • A data analysis study for multi-agent occupancy by Autodesk Research. The research focuses on creating a digital simulation of occupants in a building through the use of Sequential Data Analysis (Figure 1.1.10) (Breslav et al, 2017).

Figure 1.1.7

Figure 1.1.7: Diagram showing the beginnings of subscription based co-living models around the world since 2008. Figure 1.1.8: (Left) Electrical use patterns

The objective of data collection and occupancy mapping is to help understand user behaviour and effectively predict future need. The visualised data provides an understanding of the hierarchy of use of living spaces in a residential setting.

by the UK government are

Economic

Social

16

_1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel

User

Income: 95,000 GBP/ year Savings: 10% of income Assets: 2-bedroom apartment Spending: Rent, food, travel, leisure

Married No children Works remotely Socialises with co-workers

Recurring Age: 21 years old Occupation: Student Stay: 180 days/year

Cultural

used to generate potential user behaviour profiles (right). These behaviour profiles and inferred

Usage pattern

Duration/day

Time

Trendy restaurants Lounges Travel Politics Film

Eat Sleep Work Clean Exercise

0-30 min 4-6 hrs 2-3 hrs 0-20 min 30 min-1 hr

5 pm - 6 pm 12 am - 6 am 10 am - 5 pm 9 am - 3 pm 5 am - 6 am

Income: 8,000 GBP/ year Savings: None Assets: None Spending: Tuition, rent, food

Single No children Works part-time Socialises with other students

Bars Concerts Museums Galleries Music events

Eat Sleep Work Clean Socialise Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs 1-2 hrs 0-1 hrs

11 am - 12 pm & 5 pm - 6 pm 11 pm - 7 am 7 am - 11 pm 8 am - 5 pm 11 am - 3 pm 4 pm - 9 pm 11 am - 12 pm & 4 pm - 6 pm

Constant Age: 27 years old Occupation: Nurse Stay: 335 days/year

Income: 30,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, food, leisure

Engaged 2-year-old son Works night shifts Socialises with other gym-goers

Coffee Comedy clubs Sports events Sports classes

Eat Sleep Work Clean Exercise Socialise Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs 1-2 hrs 0-1 hrs 0-1 hrs

11 am - 1 pm & 4 pm - 6 pm 12 am - 7 am 10 am - 11 pm 8 am - 1 pm & 6 pm - 9 pm 1 pm - 3 pm 2 pm - 4 pm 7 pm - 8 pm 12 pm - 1 pm & 5 pm - 6 pm

Constant Age: 67 years old Occupation: Pensioner Stay: 335 days/year

Income: 18,000 GBP/year Savings: Pension Assets: Owns 2-bedroom home Spending: Rent, food, travel

Widow No children Baby sits during free time Socialises with book club

Libraries Museums Long walks Baking

Eat Sleep Cook Read Clean Socialise Entertainment Leisure

30 min-1hr 6-8 hrs 3-4 hrs 1-2 hrs 0-20 min 1-2 hrs 0-2 hrs 0-1 hrs

4 pm - 6 pm 11 am - 3 pm & 12 am - 4 am 4 pm - 6 pm 1 pm - 10 pm 9 am - 12 pm 1 pm - 11 pm 1 pm - 11 pm 4 pm - 6 pm

Recurring Age: 72 years old Occupation: Pensioner Stay: 180 days/year

Income: 25,000 GBP/year Savings: Pension Assets: Owns 4-bedroom home Spending: Rent, food, travel

Married 2 daughters Occasionally visits daughters in London Owns restaurant

Vintage car shows Cafes Long walks Jazz clubs

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 2-3 hrs 1-2 hrs 1-2 hrs

11 am - 12 pm 11 am - 3 pm & 1 am - 5 am 8 am - 11 pm 5 pm - 11 pm 5 pm - 11 pm

Sporadic Age: 32 years old Occupation: Cabin crew Stay: 24 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Food, leisure, shopping

Single No children Pursuing online degree in psychology Plays rugby

Techno clubs Japanese food Volunteer projects

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 6 pm - 9 pm 6 pm - 9 pm

Sporadic Age: 40 years old Occupation: Academic and Entrepreneur Stay: 24 days/year

Income: 55,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, research, food

Single No children Visits London for lectures and reviews

Museums Galleries Conferences

Eat Sleep Socialise Exercise Research Work Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & 1 pm - 3 pm 12 pm - 11 pm 12 pm - 11 pm 6 pm - 9 pm

Recurring Age: 25 years old Occupation: Personal trainer Stay:

Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel

Spends weekends with girlfriend outside London No children Movie buff

Cinemas Theatres Gyms Parks

Eat Sleep Socialise Exercise Entertainment Work

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs

7 am, 12 pm & 4 pm - 6 pm 11 pm - 5 am 4 pm - 11 pm 10 am - 11 am 4 pm - 11 pm 9 am - 11 am & 1 pm - 3 pm

Sporadic Age: 44 years old Occupation: Banker Stay: 24 days/year

Figures 1.1.10

visualised in a survey conducted

User Behaviour Patterns Profile

Figures 1.1.9

for different social groups

Data

movement of users drive the spatial organization and desired spatial qualities in the living spaces of Dwell.t. Figure 1.1.9: Visualized data collected from 77 sensor distributed through home 1 Figure 1.1.10: Floor plans of hotel depicting recurring user paths. Data-driven design: Refers to the method of collecting user data, either by sensors or time use surveys,

Figure 1.1.8

in order to make inferred simulations of user behaviour.

1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel_

17


1.1.4 Layout, Geometry and Fabrication The strategies employed can be divided into three categories: • A primitive spatial layout is arranged around the movement of the users (Figure 1.1.11). This is a generative system that responds to the users’ activities during their use of the various living spaces, inferred from the data collected. • Compression-only geometry is generated from the primitives (Figure 1.1.12). • Digital fabrication steps are articulated to manufacture a lightweight, transparent structure (Figure 1.1.13).

Figure 1.1.11

Architectural application combines lightweight timber and on - site robotic fabrication with the priority of addressing temporality in construction and building use.

Figure 1.1.11: Studies of how users occupy space comfortably are coupled with time cycles inferred from electrical use surveys to draw

1.1.5 Motivation An underlying connector between all of the motivations of this project is codependency. This is evident in: • Community building, where user groups depend on one another. • The different components of the structure, the timber and the weaving, are also codependent, as one cannot function without the other. • The different aspects of the work flow function on a feedback loop and are thus also codependent. The motivations of Dwell.t include:

• Creating a community that facilitates knowledge exchange • •

the movement of users within the spatial layout. Figure 1.1.12: Diagram showing the architectural geometry generated from a set of primitives. The geometry is based on 3D graphic statics and produces a compression-only network. Figure 1.1.12

Figure 1.1.13: (Left) Example of the lightweight, bent timber fabrication system

between different social groups in London, something that other subscription living models struggle to achieve. Designing a lightweight architecture that is fast and easy to construct. This is the kind of architecture that can be quickly edited to respond to the changing demands of the users. Developing a construction system that responds to London specifically by having its components manufactured and assembled primarily on site. This eliminates the need for large trucks or cranes on the narrow city streets and sites.

used for mock-up and full-scale prototypes. (Right) A woven quad of nodes. Weaving provides a gradient of transparencies to characterise and distinguish interior spaces. It also acts as a tensioning strategy in specific parts of the structure. Data-driven occupancy modelling: Refers to the method of collecting user data, either by sensors or time use surveys, in order to make inferred Figure 1.1.13

18

_1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel

simulations of user behaviour.

1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel_

19


1.1.6 Designing and Fabricating Non-orthogonal Aggregations Dwell.t research endeavours in the task of establishing an architectural expression for the future of urban living. Dwell.t Deductions: Opportunities:

• Lightweight, transparent system. • Fast to deploy. • Allows fabrication, on the site, from the inside out. • • • •

Constraints: Lack of detail e.g: glazing, door, furniture. Absence of tested horizontal surfaces. Rigid spatial grid. Weaving always secondary to, and dependent on, timber frame.

Architectural system in urban context:

• Fast to deploy and edit over time. • Tailored to small, affordable infill sites. Design and fabrication aspects to be investigated:

• Transitioning from cuboid primitives to other tailored polygons • •

as cuboids produce a rigid grid that resists variety in spatial configuration and quality. Establishing a non-orthogonal geometry as a compression-only system places horizontal members under tension and bending, which deters from the system’s ability to carry load efficiently. Finally, developing weaving strategies that act as partitions independent from the timber frame, in order to create opportunities for spatial variety and hierarchy. Figure 1.1.14: Non-orthogonal geometry with regular weaving patterns around accessible openings and random, dense patterns on Figure 1.1.14

closed openings that function as walls or floors. This geometry is to be tested through digital timber fabrication methodology.

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_1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel

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21


Figure 1.1.15:

Figure 1.1.16:

Night time render on site.

Night time render on site.

22

_1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel

1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel_

23


Figure 1.1.17:

Figure 1.1.18:

Night time render on site.

Night time render on site.

24

_1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel

1.1 Own Nothing. Access Everything: Hybrid Typology: Home+Hotel_

25


1.2 Housing for Transient Communities The Amalgamated Housing Cooperative, 1927 Location: Bronx, NY. USA Own Nothing. Access Everything stems from a participation-based socio-economic model called the shared economy. A shared economy model: • Relies on the use and access of shared resources and assets. • Enables a new form of value exchange (Matofska, 2016). • Participatory nature gives rise to a close dependency between the larger system in place and the individual users. The inherent ideals of the shared economy allows Dwell.t to integrate principles of subscription and on demand housing. Dwell.t is situated within historic and contemporary models of cooperative and subscription living. Below are studies of housing models that follow a structure of shared spaces ranging from private to public amenities in order to fulfil goals of community building.

Description: This housing complex catered to industrial workers and their families by providing private units containing sleeping arrangements, bathroom and a kitchen. The architecture responded to shared living models by providing day-care and teaching centres for women. As of 1927 the complex had 300 units, by 1971 it expanded to 25,000 units (Amalgamated Housing Corp., 2016).

ROAM 2016 Location: Miami, Bali, Tokyo, London PodShare 2012 Location: Los Angeles, CA. USA The Collective 2010 Location: London, UK Airbnb 2008 Location: San Francisco, CA. USA Worldwide Figure 1.2.1

Figure 1.2.2

Figure 1.2.1

Figure 1.2.2

Diagram illustrating the models

The first complex of cooperative

of subscription living as a global

buildings in Bronx, NY, following

trend.

a model of shared living.

26 _1.2 Own Nothing. Access Everything: Housing for Dynamic Communities

1.2 Own Nothing. Access Everything: Housing for Dynamic Communities_

27


Airbnb, 2008

The Collective, 2010

Location: 191 countries.

Location: London, UK.

Description: Airbnb is an online community market place where users can list and book unique accommodations around the world. The site has over 4 million listings in 65,000 destinations. The aim of the platform is to provide all users an opportunity to explore a city beyond the conventions of a hotel room by connecting visitors and locals. Accommodations range from a couch at a host’s home to castle or a villa (Airbnb, 2008).

Description: The Collective: Old Oak, is the largest co-living development in London with 535 private bedrooms. The building caters to a community of urban professionals who are looking for a “hassle - free experience” in London (The Collective, 2015). The Collective aims to create a community of creatives who have common interests and ambitions, thus opening a platform for networking. The building provides shared spaces such as kitchen, gym, library, cinema and incubator hubs as well as weekly community events.

Figure 1.2.3

Figure 1.2.4

Figure 1.2.3 Advertisement for Airbnb,

Figure 1.2.4

targeting travellers looking

Visualisation of Old Oak, the

to explore a city beyond the

first building by The Collective

conventions of a hotel room.

in London.

28 _1.2 Own Nothing. Access Everything: Housing for Dynamic Communities

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29


PodShare, 2012

ROAM, 2016

Location: 4 locations in Los Angeles, CA, USA.

Location: 5 locations in London, Tokyo, Miami, San Francisco, Bali.

Description: PodShare is a membership based co-living targeting users looking to create a social network in a temporary accommodation. PodShare aims to create a “social network with a physical address” (Podshare, 2017). All spaces in the 4 premises are shared, including sleeping arrangements (Figure 2.1.4), bathrooms and kitchen. The locations also offer work areas which can be used by external visitors.

Description: ROAM is a network of co-living a community of young professionals. “Feel at home and be productive”, this is the motto of the organization to targeting travellers to work remotely and explore different locations. The private units follow the model of a hotel, including sleeping arrangements and bathroom. Shared spaces include work and kitchen areas as weekly events organized for the community, i.e: yoga classes, cooking classes and workshops.

Figure 1.2.5

Figure 1.2.6

Figure 1.2.5 PodShare has 70 sleeping pods

Figure 1.2.6:

which are all open bunk beds in

Photograph of a compact ROAM

larger shared spaces.

bedroom.

30 _1.2 Own Nothing. Access Everything: Housing for Dynamic Communities

1.2 Own Nothing. Access Everything: Housing for Dynamic Communities_

31


1.3 Design Methodology Feedback Loop 1.2.1 Workflow The workflow is purposely non-linear in order for each step of the process to inform the following and reshape the previous step. The data collected in surveys is used to understand when and for how long different social groups use appliances around their homes. Use patterns are inferred and divided into three groups: sporadic, recurring and constant.

The coloured spheres surrounding the users represent the space where another individual must be in order to initiate verbal or social interaction. These zones are informed by the amount of time each user group spends in a given space. For example, if sporadic users are shown to spend the least amount of time in the kitchen, they will be least likely to initiate interaction with others there and will thus have the smallest spheres. These spheres determine the dimensions of the primitives used to organize the spaces in the aggregation. The order in which different user groups move between their appliances during the day informs the organization of the spaces in the aggregation.

Data

Primitive Layout

210 of 600 Intertek Report R66141 Page 309 Multiple person household with no dependent children Cooking

ENERTECH

INTERTEK

Daily average load curve

ENERTECH

INTERTEK

Multiple person household nodependent dependent children Multiple person household with with no children Without electric heating Structure of the average hourly load curve

160 800

Holidays

700

120 600

Power (W)(W) Power

Economic

Social

Usage pattern

Duration/day

Time

Sporadic Age: 44 years old Occupation: Banker Stay: 24 days/year

Income: 95,000 GBP/ year Savings: 10% of income Assets: 2-bedroom apartment Spending: Rent, food, travel, leisure

Married No children Works remotely Socialises with co-workers

Trendy restaurants Lounges Travel Politics Film

Eat Sleep Work Clean Exercise

0-30 min 4-6 hrs 2-3 hrs 0-20 min 30 min-1 hr

5 pm - 6 pm 12 am - 6 am 10 am - 5 pm 9 am - 3 pm 5 am - 6 am

Recurring Age: 21 years old Occupation: Student Stay: 180 days/year

Income: 8,000 GBP/ year Savings: None Assets: None Spending: Tuition, rent, food

Single No children Works part-time Socialises with other students

Bars Concerts Museums Galleries Music events

Eat Sleep Work Clean Socialise Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs 1-2 hrs 0-1 hrs

11 am - 12 pm & 5 pm - 6 pm 11 pm - 7 am 7 am - 11 pm 8 am - 5 pm 11 am - 3 pm 4 pm - 9 pm 11 am - 12 pm & 4 pm - 6 pm

Constant Age: 27 years old Occupation: Nurse Stay: 335 days/year

Income: 30,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, food, leisure

Engaged 2-year-old son Works night shifts Socialises with other gym-goers

Coffee Comedy clubs Sports events Sports classes

Eat Sleep Work Clean Exercise Socialise Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs 1-2 hrs 0-1 hrs 0-1 hrs

11 am - 1 pm & 4 pm - 6 pm 12 am - 7 am 10 am - 11 pm 8 am - 1 pm & 6 pm - 9 pm 1 pm - 3 pm 2 pm - 4 pm 7 pm - 8 pm 12 pm - 1 pm & 5 pm - 6 pm

Constant Age: 67 years old Occupation: Pensioner Stay: 335 days/year

Income: 18,000 GBP/year Savings: Pension Assets: Owns 2-bedroom home Spending: Rent, food, travel

Widow No children Baby sits during free time Socialises with book club

Libraries Museums Long walks Baking

Eat Sleep Cook Read Clean Socialise Entertainment Leisure

30 min-1hr 6-8 hrs 3-4 hrs 1-2 hrs 0-20 min 1-2 hrs 0-2 hrs 0-1 hrs

4 pm - 6 pm 11 am - 3 pm & 12 am - 4 am 4 pm - 6 pm 1 pm - 10 pm 9 am - 12 pm 1 pm - 11 pm 1 pm - 11 pm 4 pm - 6 pm

Recurring Age: 72 years old Occupation: Pensioner Stay: 180 days/year

Income: 25,000 GBP/year Savings: Pension Assets: Owns 4-bedroom home Spending: Rent, food, travel

Married 2 daughters Occasionally visits daughters in London Owns restaurant

Vintage car shows Cafes Long walks Jazz clubs

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 2-3 hrs 1-2 hrs 1-2 hrs

11 am - 12 pm 11 am - 3 pm & 1 am - 5 am 8 am - 11 pm 5 pm - 11 pm 5 pm - 11 pm

Sporadic Age: 32 years old Occupation: Cabin crew Stay: 24 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Food, leisure, shopping

Single No children Pursuing online degree in psychology Plays rugby

Techno clubs Japanese food Volunteer projects

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 6 pm - 9 pm 6 pm - 9 pm

Sporadic Age: 40 years old Occupation: Academic and Entrepreneur Stay: 24 days/year

Income: 55,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, research, food

Single No children Visits London for lectures and reviews

Museums Galleries Conferences

Eat Sleep Socialise Exercise Research Work Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & 1 pm - 3 pm 12 pm - 11 pm 12 pm - 11 pm 6 pm - 9 pm

Recurring Age: 25 years old Occupation: Personal trainer Stay: 180 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel

Spends weekends with girlfriend outside London No children Movie buff

Cinemas Theatres Gyms Parks

Eat Sleep Socialise Exercise Entertainment Work Lounge

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs 0-1 hrs

7 am, 12 pm & 4 pm - 6 pm 11 pm - 5 am 4 pm - 11 pm 10 am - 11 am 4 pm - 11 pm 9 am - 11 am & 1 pm - 3 pm 4 pm - 7 pm

Constant Age: 33 years old Occupation: Travel and fashion blogger Stay: 335 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel, shopping

Single No children Travels to fashion shows

Cinemas Shopping High end restaurants Coffee shops

Eat Sleep Socialise Exercise Entertainment Work Lounge

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & 1 pm - 3 pm 6 pm - 9 pm 12 pm - 11 pm 6 pm - 9 pm

Profile

140 All days

100

User

Cultural

500

80 400

60 300

40

200

20

100

0

00 00:0 :00 01 0 01:0 :00 02 0 02:0 :00 003 0 3:0:00 0 004 4:0:00 0 005 5:0:0 0 0 006 6:0:0 0 0 007 7:0:0 0 0 008 8:0:0 00 009 9:0:0 00 110 0:0:0 00 111 1:0:0 00 112 2:0:0 00 113 3:0:0 00 1144 :0:0 00 1155 :0:0 00 1166 :0:0 00 1177 :0:0 00 1188 :0:0 00 1199 :0:0 00 2200 :0:0 00 2211 :0:0 00 2222 :0:0 00 2233 :0:00 0

0

Hours Hour DEFRA, DECC, EST

Cold appliances Cooking Audiovisual ICT Figure 428 Cooking – Daily average load curve –Lighting Multiple person household with no dependent DEFRA, DECC, EST Washing/drying Water heating Other Not known children – Holidays Figure 278 Structure of the average hourly load curve – All days – Multiple person household with no dependent children - Without electric heating ENERTECH

INTERTEK

Cooking Daily average load curve

ENERTECH

INTERTEK

Multiple person household nodependent dependent children Multiple person household with with no children 180 Workdays 160 Holidays

800

Without electric heating Structure of the average hourly load curve

700

140

600

Power (W)(W) Power

120

500

100

400 80 300 60 200 40

20 100

0

000:0 :00 0 0011:0 :00 0 0022:0 :00 0 0033:0 :00 0 0044:0 :00 0 0055:0 :00 0 0066:0 :00 0 0077:0 :00 0 0088:0 :00 0 0099 :0 :00 0 100 :0 :00 0 111 :0 :00 0 12 :0 :00 0 13 :0 :00 0 14 :0 :00 0 15 :0 :00 0 16 :0 :0 00 17 :0 :0 00 1188 :0 :0 00 119 9:0 :0 00 220 0:0 :0 00 221 1:0 :0 00 222 2:0 :0 00 223 3:0 :0 00

00

Private Unit

Primary Social Unit

Secondary Social Unit

Gym

Hours Hour DEFRA, DECC, EST

Cold appliances

Cooking

Lighting

Audiovisual

Kitchen

ICT

Figure 429 Cooking – Daily average load curve – Multiple person household with no dependent DEFRA, DECC, EST Washing/drying Water heating Other Not known children – Workdays Figure 279 Structure of the average hourly load curve – Holidays – Multiple person household with no dependent children - Without electric heating

Laundry

Macro Scale Data: User Behaviour Patterns

Work Entertainment

Lounge

Circulation

Social Units

Private Units

Intrinsic Rules 23 Units

Sporadic User

Recurring User

Constant User

21 Units

17 Units

Extrinsic Rules

32

_1.3 Own Nothing. Access Everything: Dwell.t Methodology Feedback Loop

1.3 Own Nothing. Access Everything: Dwell.t Methodology Feedback Loop_

33


Finally, the geometry must be prepared for fabrication. In order to CNC flat sheets of timber and bend them to construct the structure, every face must be a developable surface. The angle of the bending must also be large enough to bend using Birch plywood. Otherwise, the geometry must be revised in order to become fabricable.

Architectural Geometry

34

Translation Primitive to Geometry

Developable Surfaces

On-Site Geometry

Bent Timber Skeleton + Woven Enclosure

_1.3 Own Nothing. Access Everything: Dwell.t Methodology Feedback Loop

Zip ties replaced with wood screws and washers

Adjusted finger joint

Asymmetrical node

Labeled pieces

Added openings for weaving

Eliminate unnecessary openings Alignment marks

3 layers of Birch veneer Wet bending in a formwork

Full loop assembly

Additional holes for weaving and tensioning

Connection and bending using zip ties

3 mm plywood, wet bending 3 mm finger connection Connection using zip ties Face-face connection

5.5 mm finger connect Connection and bending using zip ties

1.5 mm plywood, dry b ending 1.5 mm finger connection

1.7 mm zipper connection

1.5 mm zipper connection

1.9 mm zipper connection

0.7 mm polypropylene Merging two surfaces

Bent using formwork

Dry bending Screwed together

1.5 mm plywood, scored Arbitrary connection size

Digital Fabrication

5.5 mm plywood, wet bending Zip tie holes

Architectural geometry is derived directly from the primitive layout using the principles of 3D graphic statics to create a compressiononly network. Once the geometry is evaluated, the primitive layout can be edited to produce more successful geometry.

1.3 Own Nothing. Access Everything: Dwell.t Methodology Feedback Loop_

35


Introduction Objectives


Economic

Social

Usage pattern

Duration/day

Sporadic Age: 44 years old Occupation: Banker Stay: 24 days/year

Income: 95,000 GBP/ year Savings: 10% of income Assets: 2-bedroom apartment Spending: Rent, food, travel, leisure

Married No children Works remotely Socialises with co-workers

Trendy restaurants Lounges Travel Politics Film

Eat Sleep Work Clean Exercise

0-30 min 4-6 hrs 2-3 hrs 0-20 min 30 min-1 hr

Recurring Age: 21 years old Occupation: Student Stay: 180 days/year

Income: 8,000 GBP/ year Savings: None Assets: None Spending: Tuition, rent, food

Single No children Works part-time Socialises with other students

Bars Concerts Museums Galleries Music events

Eat Sleep Work Clean Socialise Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs 1-2 hrs 0-1 hrs

Constant Age: 27 years old Occupation: Nurse Stay: 335 days/year

Income: 30,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, food, leisure

Engaged 2-year-old son Works night shifts Socialises with other gym-goers

Coffee Comedy clubs Sports events Sports classes

Eat Sleep Work Clean Exercise Socialise Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs 1-2 hrs 0-1 hrs 0-1 hrs

Constant Age: 67 years old Occupation: Pensioner Stay: 335 days/year

Income: 18,000 GBP/year Savings: Pension Assets: Owns 2-bedroom home Spending: Rent, food, travel

Widow No children Baby sits during free time Socialises with book club

Libraries Museums Long walks Baking

Eat Sleep Cook Read Clean Socialise Entertainment Leisure

30 min-1hr 6-8 hrs 3-4 hrs 1-2 hrs 0-20 min 1-2 hrs 0-2 hrs 0-1 hrs

Recurring Age: 72 years old Occupation: Pensioner Stay: 180 days/year

Income: 25,000 GBP/year Savings: Pension Assets: Owns 4-bedroom home Spending: Rent, food, travel

Married 2 daughters Occasionally visits daughters in London Owns restaurant

Vintage car shows Cafes Long walks Jazz clubs

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 2-3 hrs 1-2 hrs 1-2 hrs

Sporadic Age: 32 years old Occupation: Cabin crew Stay: 24 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Food, leisure, shopping

Single No children Pursuing online degree in psychology Plays rugby

Techno clubs Japanese food Volunteer projects

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs

Sporadic Age: 40 years old Occupation: Academic and Entrepreneur Stay: 24 days/year

Income: 55,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, research, food

Single No children Visits London for lectures and reviews

Museums Galleries Conferences

Eat Sleep Socialise Exercise Research Work Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs

Recurring Age: 25 years old Occupation: Personal trainer Stay: 180 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel

Spends weekends with girlfriend outside London No children Movie buff

Cinemas Theatres Gyms Parks

Eat Sleep Socialise Exercise Entertainment Work Lounge

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs 0-1 hrs

Constant Age: 33 years old Occupation: Travel and fashion blogger Stay: 335 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel, shopping

Single No children Travels to fashion shows

Cinemas Eat Shopping Sleep Figure 2.1.1 High end restaurants Socialise Coffee The shops Exercisedistinct diagram identifies Entertainment users living in high-productivity Work Lounge These cities such as London.

Profile

2.1 Building Transient Communities

omic del and e shared s such mption nderlying le take f the n the nt ideals s of ocial

The first motivation of the research is to build a community of urban dwellers, formed by a mix of residents and visitors of London. The aim of building transient communities is to foster a contemporary model of subscription living which yields user participation. The participatory nature of such living model enables new forms of value exchange, ranging from resources to intellectual and cultural access.

s of to a r of the begins hared fulfil his model.

The research identifies the following as opportunities to foster a unique community: • London’s geographic gap between residential areas and its touristic centres. This gap yields an opportunity to bring together distinct demographics into a mutually beneficial community. Thus, users is less individualistic and more co-dependant.(2.1.1) • A growing trend of dynamic lifestyles which increase the need for faster and readily available services. In response, a fitting housing paradigm is required, one which is design for cyclical use, rather than a year-round occupancy.

User

Cultural

users are part of the transient Figure 2.1.1

38

_2.1 Objectives: Building Transient Communities

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs 0-1 hrs

community fostered by Dwell.t.

2.1 Objectives: Building Transient Communities_

39


2.2 Data Driven Spatial-Customisation

Sporadic Age: 44 years old Occupation: Banker Stay: 24 days/year

Income: 95,000 GBP/ year Savings: 10% of income Assets: 2-bedroom apartment Spending: Rent, food, travel, leisure

Recurring Age: 21 years old Occupation: Profile Student Stay: 180Sporadic days/year

Income: 8,000 GBP/ year Savings: None Assets: None Economic Spending: Tuition, rent, food

User

The second motivation of the research is spatial customisation, meaning customisation which hinges in data driven design to make informed inferences on user preferences and behaviour patterns. Data driven design provides an opportunity to leverage specific spatial organizations which cater to a spectrum of user profiles found User across transient communities. The research takes as initial framework an Electrical Survey of 260 households across the UK in 2012 in order to extract usage patterns of functions such as kitchen and living rooms. (2.2.1) The data presented is extracted and analysed as follows: • Type of household by category, i.e: single person, multiple person, pensioner, etc. • Inference of amount of time spent at home daily • Extraction of time and duration each house appliance is used. The research concluded the following results: • Categorization of users into behavioural profiles: sporadic, recurring and constant (2.2.2) • Informed deduction of the movement of distinct user around the house. (2.2.3) Intertek Report R66141 • Daily time-use schedules for every user type. Multiple person household with no dependent children ENERTECH

Multiple person household with no dependent children Without electric heating Structure of the average hourly load curve

800

All days 700

Power (W)

600 500 400 300 200 100 0

00 :0 0 01 :0 0 02 :0 0 03 :0 0 04 :0 0 05 :0 0 06 :0 0 07 :0 0 08 :0 0 09 :0 0 10 :0 0 11 :0 0 12 :0 0 13 :0 0 14 :0 0 15 :0 0 16 :0 0 17 :0 0 18 :0 0 19 :0 0 20 :0 0 21 :0 0 22 :0 0 23 :0 0

Figure 2.2.1 Chart indicating average

Hours

hourly use of a multiple person

Cold appliances

Cooking

Lighting

Audiovisual

Washing/drying

Water heating

Other

Not known

household in the UK. “Household

DEFRA, DECC, EST

Electricity Survey A Study of

Figure 278 Structure of the average hourly load curve – All days – Multiple with no dependent children - Without electric heating

Domestic Electrical Product Usage.”, 2012

Occupation: Cabin crew Stay: Constant 24Age: days/year 33 years old Occupation: Travel and Sporadic fashion blogger Age: 40Stay: years old 335 days/year Occupation: ICT Academic and Entrepreneur Stay: days/year person 24 household

Figure 2.2.1 ENERTECH

Multiple person household with no dependent children Without electric heating Structure of the average hourly load curve

800

Income: 95,000 GBP/ year Savings: 10% of income Assets: 2-bedroom apartment Spending: Rent, food, travel, leisure Income: 30,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, food, leisure

Income: 8,000 GBP/ year Savings: None Assets: None Income: 18,000 GBP/year Spending: Tuition, rent, food Savings: Pension Assets: Owns 2-bedroom home Spending: Rent, food, travel

Income: 30,000 GBP/year Savings: 10% of income Economic Assets: None Spending: Rent, food, leisure Income: 25,000 GBP/year Income: Pension 95,000 GBP/ year Savings: Savings: 10% 4-bedroom of income home Assets: Owns Assets: 2-bedroom Spending: Rent, food,apartment travel Spending: Rent, food, travel, leisure Income: 18,000 GBP/year Savings: Pension Assets: Owns 2-bedroom home Spending: Rent, food, travel Income: 20,000 GBP/year

Savings: Income: None 8,000 GBP/ year Assets: None Savings: None Spending: Food, leisure, shopping Assets: None Spending: Tuition, rent, food

Income: 25,000 GBP/year Savings: Pension Assets: Owns 4-bedroom home Income: 55,000 GBP/year Spending: Rent, food, travel Savings: of income Income: 10% 30,000 GBP/year Assets: None Savings: 10% of income Spending: Rent, research, food Assets: None Spending: Rent, food, leisure Income: 20,000 GBP/year Savings: None Assets: None Spending: Food, leisure, shopping Income: 20,000 GBP/year Income: None 18,000 GBP/year Savings: Savings: Pension Assets: None Assets: Owns Spending: Rent,2-bedroom food, travelhome Spending: Rent, food, travel Income: 55,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, research, food Income: 20,000 GBP/year

Savings: Income: None 25,000 GBP/year Assets: None Savings: Pension Spending: Rent,4-bedroom food, travel, shopping Assets: Owns home Spending: Rent, food, travel Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel Income: 20,000 GBP/year Savings: None Assets: None Spending: Food, leisure, shopping

700 _2.2 Objectives: Data Driven Spatial-Customisation

er (W)

600 500 400

Sporadic Age: 44 years old Single Constant Occupation: Age: No children 27 Banker years old Works part-time Stay:other students Socialises with SocialOccupation: 24 days/year Nurse Stay: 335 days/year Married Recurring No children Age: Works remotely Constant 21with years old Socialises co-workers Engaged Age: Occupation: 2-year-old 67son years old Student Works night shifts Occupation: Stay:other gym-goers Socialises with Pensioner 180 days/year Stay: 335 days/year Single No children Constant User WorksProfile part-time Age: Recurring Socialises other Widow 27with years old students Age: No children Occupation: yearsfree old time Sporadic Baby sits72 during Nurse Occupation: Age: Socialises with Stay:book club Pensioner 44335 years old days/year Stay: Occupation: 180 days/year Banker Engaged Stay: Constant 2-year-old son Social 24Age: days/year Works night shifts Sporadic 67with years old gym-goers Socialises other Married Age: Occupation: 2Married daughters 32 years old Pensioner Recurring No children visits daughters in London Occasionally Occupation: Stay: Age: Worksrestaurant remotely Owns Cabin crew 335 days/year 21with years old Socialises co-workers Stay: Occupation: 24 days/year Student Widow Stay: No children Recurring 180 days/year Baby sits during free time Age: Sporadic Socialises book 72with years old club Single Age: Occupation: No children Single 40 Pensioner years old Pursuing online degree in psychology No children Constant Occupation: Stay: Plays Worksrugby part-time Age: Academic and 180 days/year Socialises with other students 27 years old Entrepreneur Occupation: Stay: Nurse Married 24 days/year Sporadic Stay: 2 daughters Age: 335 days/year Occasionally visits daughters in London Recurring 32 years old Owns restaurant Single Age: Occupation: No children Engaged 25 years old Cabin crew Constant Visits London 2-year-old sonfor lectures and reviews Occupation: Stay: Age: Works night shiftstrainer Personal 24 days/year 67 years old Socialises with other gym-goers Stay: Occupation: 180 days/year Pensioner Single Stay: Sporadic No children 335 days/year PursuingAge: online degree in psychology 40 years old Constant Playsweekends rugby Spends with girlfriend outside Occupation: Widow Age: London Academic 33 years old and Recurring Nochildren children No Entrepreneur Occupation: Age: Baby sits during free time Movie buff Stay: Travel and 72with years old club Socialises book 24 days/year fashion blogger Occupation: Stay: SinglePensioner 335 days/year Recurring Stay: No children Age: days/year Visits 180 London for lectures and reviews 25 years old Single Occupation: No children Married Personal trainer Travels toSporadic fashion shows 2 daughters Stay: Age: Occasionally visits daughters in London days/year 32180 years old Owns restaurant Occupation: Cabin crew Spends weekends with girlfriend outside Stay: London Constant 24Age: days/year No children 33 years old Movie buff Occupation: Single Travel and Sporadic No children fashion blogger Age: Pursuing online degree in psychology 40Stay: years old Plays rugby 335 days/year Occupation: Academic and Single Entrepreneur No children Stay: Travels to fashion shows 24 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel, shopping Income: 55,000 GBP/year Single Recurring Savings: 10% of income No children Age: for lectures and reviews Assets: None Visits London 25 years old Spending: Rent, research, food Occupation: Personal trainer Stay: 180 days/year

Recurring Age: 25 years old Occupation: INTERTEK Personal trainer Stay: 180 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel

Constant Age: 33 years old Occupation: Travel and fashion blogger

Income: 20,000 GBP/year Savings: None Assets: None Spending: Rent, food, travel, shopping

Holidays

40

User

Income:restaurants 8,000 GBP/ year Eat Trendy Savings: None Sleep Lounges Assets: None Work Travel Spending: Tuition, rent, food Clean Politics Economic Exercise Film

Single 0-30 min 5 pm - 6 pm No children 4-6 hrs 12 am - 6 am Works part-time 2-3 hrs 10 am - 5 pm Socialises with other students 0-20 min 9 am - 3 pm 30Social min-1 hr 5 am - 6 am

180 days/year

Age: 44 years old Occupation: Constant Banker Age: Stay: old 27 years 24 days/year Occupation:

Nurse Stay: 335Recurring days/year Age: 21 years old Occupation: Constant Student Age: Stay: old 67 years 180 days/year Occupation: Pensioner Stay: 335 days/year Constant Profile Age: 27 years old Recurring Occupation: Sporadic Age: Nurse Age: 72 years Stay: old 44335 years old Occupation: days/year Occupation: Pensioner Banker Stay: Constant Stay: 180 days/year 24Age: days/year 67 years old Occupation: Sporadic Pensioner Age: Recurring Stay: old 32 years Age: days/year Occupation: 21335 years old Cabin crew Occupation: Stay: Student 24 days/year Stay: Recurring 180 days/year Age: 72 years old Sporadic Occupation: Age: Pensioner Constant 40 years Stay: old Age: Occupation: days/year 27180 years old Academic and Occupation: Entrepreneur Nurse Stay: Sporadic Stay: 24 days/year Age: 335 days/year 32 years old Occupation: Recurring Cabin crew Constant Age: Stay: old Age: 25 years Page 210 of 600 days/year 6724 years old Occupation: Occupation: Personal trainer Pensioner Stay: Stay: 180 days/year Sporadic 335 days/year Age: 40 years old INTERTEK Occupation: Constant Academic and Age: Recurring Entrepreneur 33 years old Age: Stay: Occupation: 72 years old 24 days/year Travel and Occupation: fashion blogger Pensioner Stay: Recurring Stay: 335 days/year Age: 180 days/year 25 years old Occupation: Personal trainer Sporadic Stay: Age: days/year 32180 years old

Married Recurring Age: No children 21 years old Works remotely Occupation: Socialises with co-workers Student Profile Stay:

Bars Concerts Museums Galleries MusicCultural events

Eat Sleep Work Clean Socialise Usage pattern Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs Duration/day 1-2 hrs 0-1 hrs

Income: 95,000 GBP/ year Eat 0-30 min Married Trendy restaurants Savings: 10% of income Sleep 4-6 hrs No children Lounges 0-30 EatWork Income: 30,000 GBP/year Engaged Coffee Assets: 2-bedroom apartment 2-3min hrs Works remotely Travel Bars 0-30 min son 11 am - 12 pm & 5 pm - 6 pm Eat 6-80-20 hrs min Sleep Savings: 10%Rent, of income 2-year-old Comedy clubs Spending: food, travel, leisure Clean Socialises with co-workers Politics Concerts 11 pm - 7 am 6-8 hrsnight shifts Sleep 3-430 hrs Work Assets: None Works Sports Exercise min-1 hr Film events Museums 7 amgym-goers - 11 pm 3-4 hrs Work 0-20 min Clean Spending: Rent, food, leisure Socialises with other Sports classes Galleries Cultural Usage pattern 0-20 Duration/day Time 8 am - 5 pm min Clean 1-2 hrs Exercise Music events 11 am - 3 pm 1-2 hrs Socialise 1-2 hrs Socialise 4 pm - 9 pm 1-2 hrs Entertainment 0-1 hrs Entertainment 11 am 12 pm & 4 pm 6 pm 0-1 hrs Cook Eat 0-30 min 5 pm - 6 Trendy restaurants 0-1 hrs Cook Single Bars Income: 8,000 GBP/ year 0-30 min Eat Sleep 4-6 hrs 12 am - 6 am Lounges No Concerts Savings: None 6-8 hrs Sleep Work 2-3 children hrs 10 am - 5 pm Travel Eat Income: 18,000 GBP/year Libraries Widow 303-4 min-1hr Works part-time Assets: None hrs Work Clean 0-20 min 9am am- -13pm pm& 4 pm - 6 pm Museums Politics 11 0-30 min Eat Coffee Sleep Savings: Pension Museums NoSocialises children with other students 6-80-20 hrs min Galleries Spending: Tuition, rent, food Clean Exercise 30 min-1 hr 5 am 6 am Film 12 am - 7 am 6-8 hrs Sleep Comedy clubs2-bedroom Cook Assets: Owns home Long walks Baby sits during free time 3-4 hrshrs Music events 1-2 Socialise 10 am 11 pm 3-4 hrs Work Sports events Read Spending: Rent, food, travel Baking Socialises with book club hrshrs Entertainment 1-21-2 8 am - 1 pm & 6 pm - 9 pm 0-20 min Clean Sports classes Clean 0-20 0-1min hrs Cook 1 pm - 3 pm 1-2 hrs Exercise Socialise 1-2 hrs 2 pm - 4 pm 1-2 hrs Socialise Entertainment 0-2 hrs 7 pm 8 pm 0-1 hrs Entertainment Bars Leisure 11 am - 12 pm & 5 pm - 6 pm 0-30 min Eat 0-1 hrs Income: 0-30 min Eat 1211 pmpm - 1-pm & 5 pm - 6 pm Coffee 0-1Engaged hrshrs Cook Concerts30,000 GBP/year 7 am 6-8 Sleep Economic Social Cultural clubs Usage Savings: 6-8 hrs Sleeppattern Duration/day 2-year-old Comedy Museums10% of incomeWork 3-4 hrs son 7 am - 11 pm Eat Married 0-30 Assets: None 3-4min hrs Work Works night shifts Sports events Income: 25,000 GBP/year Vintage car shows Galleries 4 pm - 6- 5 pm EatClean Libraries 300-20 min-1hr 8 am pm min Sleep 26-8 daughters 4-60-20 hrs min Spending: Rent, food,Sleep leisure Clean Sports classes Socialises with11 other Savings: Cafes Music Pension events amam -gym-goers 3-pm & 12 am - 4 am Museums hrshrs 11 3 pm 1-2 Socialise Socialise Occasionally visits daughters in London 2-3 hrs 1-2 hrs Exercise Eat 0-30 min Income: 95,000 GBP/ year Trendy restaurants Married Assets: Owns 4-bedroom home Long walks 4 pm - 6-pm Cook Long walks hrshrs 4 pm 9 pm Entertainment 3-41-2 Entertainment Owns 1-21-2 Socialise Sleep 4-6 hrshrs Savings: 10% offood, income No children Spending: Rent, travel Jazz 1 pm - 10- pm Read Baking 1-20-1 hrsrestaurant 11 am 12 pm & 4 pm - 6 Lounges pm clubs hrs Cook Lounge 1-2 0-1 hrs Entertainment Work 2-3 hrs Assets: 2-bedroom apartment Travel Works remotely 9 am - 12 pm Clean 0-20 min 0-1min hrs Cook Clean 0-20 Spending: Rent, food, travel, leisure Politics Socialises with co-workers 1 pm - 11 pm Socialise 1-2 hrs Exercise 30 min-1 hr Film 1 pm - 11- pm Entertainment 0-20-30 hrs min 11 am 1 pm & 4 pm - 6 pm Eat Coffee Income: 18,000 GBP/year Eat Libraries Widow 4 pm 6 pm Leisure 30 min-1hr 0-1 hrs 12 am - 7 am 6-8 hrs Sleeppattern Duration/day Comedy Cultural clubs Usage Time Savings: Pension Sleep Museums No children 6-8 hrs 10 am - 11 pm 3-4 hrs Work Sports events Assets: OwnsGBP/year 2-bedroom home Long walks Baby sits during free 0-30 EatCook Income: 20,000 Single Techno clubs 3-4min hrs 8am amtime 1 pm 0-20 min Clean Sports classes - -12 pm & 6 pm - 9 pm Baking food 0-30 min Vintage car shows Spending: Rent, food,Eat travel Read Socialises with11 book club 4-61-2 hrshrs Sleep Savings: None No children 1am pm -3pm 3pm pm& 1 am - 5 amJapanese 1-2 hrs EatExercise 0-30 min 5 pm -6 Trendy restaurants Sleep 11 4-6 hrs Cafes Clean 0-10-20 hrs Socialise Assets: None Pursuing online degree in- psychology Volunteer projects min Bars Single 0-30 min Eat Income: 8,000 GBP/ year 2 pm 4 pm 1-2 hrs Socialise Sleep 4-6 hrs 12 am- 11 - 6 am Lounges 8 am pm 2-3 Long walksFood, leisure,Socialise Socialise 0-11-2 hrshrs Entertainment Spending: shopping rugby Concerts No children 6-8 hrs Sleep Savings: None 7am pm - 8pm pm Entertainment Plays Work 2-30-1 10 5 Travelclubs Entertainment 5 pm - -11 1-2 hrshrs Jazz Entertainment 3-4 0-10-2 hrshrs Lounge Museums Works part-time hrs Work Assets: None 12 pm 1 pm & 5 pm 6 pm 0-1 hrs Cook Clean 0-20hrs min 9 Politics Lounge 5 am pm - 3 11pm pm 1-2 Leisure 0-1min hrs Galleries Socialises 0-20 Clean Spending: Tuition, rent, food Exercise 30 min-1 hrwith other 5 amstudents - 6 am Film Music events 1-2 hrs Socialise 4 pm - 6 pm Eat Libraries 30 min-1hr 1-20-30 hrs min Eat Married 11 am - 3 pm & 12 am - 4 am Sleep Museums 6-8 hrs Vintage car shows Entertainment Income: 25,000 GBP/year 0-14-6 hrshrs Cook Sleep 23-4 daughters 4 pm - 6 pm Cook Long walks hrs Cafes Savings: Pension Income: 55,000 EatSocialise 0-30 Single Occasionally visits daughters 2-3min hrs 1am pm -12 10pm pmin London Museums Read Baking 1-2min hrs Long walks Assets: OwnsGBP/year 4-bedroom home 11 0-30 Eat Techno clubs Savings: 10% of income Sleep 4-6 hrs No children Galleries Entertainment Owns restaurant 1-2 hrs 9 am 12 pm Clean 0-20 min Jazz clubs Spending: Rent, food,Sleep travel 4lectures pm pm 4-6 Japanese food Bars am- -612 pmreviews & 5 pm - 6 pm 0-30hrs min Eat Assets: None Socialise 0-1 hrs Visits London for11 and Conferences 1-2 hrs 1 pm - 11 pm Socialise Income: 30,000 GBP/year 0-30 min EatLounge Coffee Engaged 1-2 hrs 8 pm 11 pm 0-1 hrs Socialise Volunteer projects Concerts 11 pm - 7 am 6-8 hrs Sleep Spending: Rent, research, food Exercise 0-1 hrs 1 pm 11 pm Entertainment Savings: 10% of income 6-8 hrs Sleep Comedy clubs 2-year-old son 0-2 hrs 6 am pm -- 11 9 pm 0-1 Entertainment Museums 7 pm 3-4 hrs hrs Work Research 0-1 4 pm -pm 6 pm Leisure Assets: 3-4 hrs hrs Work Sports events Works night shifts 0-1 hrs 6 pm 9 0-1 hrs Lounge GalleriesNone 8 am - 5 pm 0-20 min Clean Work 0-1 Spending: Rent, food, leisure 0-20hrs min Clean Sports classes Socialises with other gym-goers Music events 11 am - 3 pm 1-2 hrs Socialise Lounge 0-1 1-2 hrs hrs Exercise 4 pm - 9 pm 1-20-30 hrs min Eat 11 am - 12 pm Vintage car shows Entertainment 1-2 hrs Socialise Income: 20,000 GBP/year 0-30 min Eat 1111 amam - 12 0-1Single hrshrs Cook Sleep - 3pm pm&&41pm am- -65pm amTechno clubs 4-6 Cafes 0-14-6 hrshrs Entertainment Savings: None Sleep Japanese food No Socialise 8 am - 11 pm 2-3 children hrs Long walks 0-1 hrs Income: 20,000 Spends weekends degree with girlfriend outside Cinemas EatSocialise 0-30 min Assets: NoneGBP/year 0-1 hrs Volunteer projects Cook Pursuing in psychology pm- -12 11pm pm 1-2 hrs online 115am EatEntertainment 0-30 min Museums Jazz clubs Savings: None London Theatres Sleep 6-80-1 hrshrs Spending: Food, leisure, shopping Entertainment Plays rugby 5am pm -pm 11 1-2 hrs 4 pm - -61 Sleep 4-6 hrs Galleries 11 pmpm & 4 pm - 6 pmGyms 0-30 min EatLounge Coffee None Assets: No children Socialise 0-1 hrs Eat Income: 18,000 GBP/year Libraries Widow hrs Lounge 300-1 min-1hr 8 pm - -11 pm Socialise 0-1 hrs Conferences 12 am 7 am 6-8 hrs Sleep Comedy clubs Spending: Rent, food, travel Movie buff Parks Exercise 1-2 hrs Sleep Savings: Pension No children 6-8 4 am ampm & 1 pm - 3 pm Museums Exercise 0-1 10 am- 6 - 11 3-4hrs hrs Work Sports events Entertainment 0-2 hrs Cook Assets: Owns 2-bedroom home Long walks Baby sits during free time 3-4 12am pm- 1- 11 Research 0-1 hrs 8 pmpm & 6 pm - 9 pm 0-20 min Clean Sports classes Work 0-1 hrs Read Spending: Rent, food, travel Baking Socialises with book club 1-2 12pm pm- 3 - 11 Work 0-1 1 pmpm 1-2hrs hrs Exercise Lounge 0-1 hrs Clean 0-20 min 6 pm 9 pm Lounge 0-1 hrs 2 -4 1-20-30 hrs min Socialise 11 am - 12 pm Eat Techno clubs Socialise 1-2 hrsmin Income: 55,000 GBP/year Museums Eat 0-30 Single 7 pm - 8-pm 0-14-6 hrshrs Entertainment 4 pm 6 pm Sleep Japanese food Entertainment 0-2 hrs Savings: 10% of income Sleep 4-6 hrs children 128pm pmpm & 5 pm - 6 pm Galleries 0-1No hrs Cook pm- -111 0-1 hrs Socialise Volunteer projects Leisure 0-1 hrs Income: 20,000 Cinemas 0-30 min Eat Assets: NoneGBP/year Entertainment Single Conferences Socialise 0-1 hrs Visits and reviews 6lectures pm12 - 9pm pm 0-1min hrsLondon for 7 am, & 4 pm - 6 pm Cinemas Eat 0-30 Savings: None No0-1 children Shopping 6-8 hrs Sleep Spending: Rent, research, food Exercise 0-1 hrs 6pm pm 9am pm 4 - -6-5pm EatLounge Libraries 30 min-1hr 11pm Theatres Sleep 6-8 hrshrs Assets: None Travels to fashion shows High end restaurants 0-1 hrs Socialise Research 0-1 hrs Eat 0-30 min Married Vintage car shows Income: 25,000 GBP/year 11 am- -11 3 pm & 12 am - 4 am Sleep Museums 6-8 hrs 4 pm Gyms Socialise 0-1 Spending: Rent, food, travel, shopping 1-2 hrs Exercise Work 0-1 hrs FigureCoffee 2.2.2 shops Sleep 4-6 hrs 2 daughters Cafes Savings: Pension 4 pmam Cook Long walks 3-4 10pm am- 6 - 11 Parks Exercise 1-2 hrs 0-2 hrs Entertainment Lounge 0-1 hrs Socialise 2-3 hrs Occasionally visits daughters Long walks Assets: home 1 - 10 Read Baking Owns 4-bedroom 1-2 hrs 4 pm 11 pmin London Entertainment 0-2 0-1 hrs hrs Work Entertainment 1-2 Owns restaurant 9 am - 12 Spending: Rent, food, travel Clean 0-20hrs min 11 pm am & 1 pm - 3 pmJazz clubs Work 0-1 0-1 hrs hrs Lounge Lounge 1-2 1 - 11 Socialise 1-2 4 pm 7 pm Lounge 0-1 hrsmin 11 am -pm 12 pm Eat 0-30 Museums Income: Spends with outside Cinemas Eat 0-30 min 1 pm - 11 Entertainment 0-2 hrs 4 pm - girlfriend 6pm pm Sleep 4-6 hrs weekends Galleries20,000 GBP/year Savings: None London Theatres Sleep 6-8 hrs 4 pm - 6-pm Leisure 0-1 hrs 8 pm 11 pm Socialise 0-1 hrs Conferences Assets: None No hrs children Gyms Socialise 0-1 hrs 4 am 6 am & 1 pm 3 pm Exercise 0-1 11 am - 12 pm Cinemas 0-30 min Eat Spending: Rent, food, travel Movie Parks Exercise 1-2 hrs 12 pm - 11 pm Research 0-1 hrsbuff 4 pm 6 pm Shopping 6-8 hrs Sleep Eat 11 am 12 pm 0-30 min Vintage car shows Entertainment 0-30 0-2min hrs Eat Income: 20,000 GBP/year Techno clubs Single 12 pm 11 pm Work 0-1 hrs 8 pm High end restaurants Socialise 0-1 Sleep 11 am- -11 3 pm & 1 am - 5 am 4-6 hrs Cafes Work 4-60-1 hrshrs Sleep Savings: None No children 6 pm 9pm pm Lounge 0-1 hrs 4 am 6-am & 1 pm - 3 pm Japanese food Coffee shops 1-2 hrs Exercise Socialise 8 - 11 2-3 Long walks Lounge 0-1 hrs 0-1 hrs Socialise Assets: None Volunteer projects Pursuing online degree in psychology 6 pm - 11 9 pm 0-2 5 pm 1-2 hrs Jazz clubsFood, leisure,Entertainment 0-1 hrs Entertainment Spending: shopping Plays rugby 12pm pm- 11 - 11pm pm 0-1 Work Lounge 5 1-2 hrs 0-1 hrs Lounge 6 pm - 9 pm 0-10-30 hrs min Lounge 7 am, 12 pm & 4 pm - 6 pm Cinemas Eat Income: Single Cinemas 0-30 min Eat 11 pm - 5 am Theatres20,000 GBP/year Sleep 6-8 hrs Savings: No Shopping 6-8 hrs Sleep 4 pm - 11 pm Gyms None Socialise 0-1 children hrs Assets: Travels High end restaurants Socialise 0-1 hrs am - 11 am Parks None Exercise 1-2 hrs to fashion10shows Spending: Rent, food, travel, shopping Coffee shops 1-2 hrs Exercise pm- 12 - 11pm pm 0-2min hrs 114am EatEntertainment 0-30 Techno clubs FigureEat2.2.2 0-2 hrs Entertainment 0-30 Income: 55,000 GBP/year Work min Museums Single 9 am 11 am & 1 pm - 3 pm 4 pm - 6-pm 4-60-1 hrshrs Sleep Japanese food 0-1 Work Savings: 10% of income Lounge Sleep 4-6 hrshrs Galleries No0-1 children 4 pm - 7pm pm Diagram categorizing user 8 pm - 11 0-1 hrshrs Socialise Volunteer projects Lounge Assets: None Socialise 0-10-1 hrshrs Conferences Visits London for lectures and reviews 6 pm - 9 pm 0-1 hrs Entertainment behavioural sporadic, Spending: Rent, research, food Exerciseprofiles: 0-1 hrs 6 pm - 9 pm 0-1 hrs Lounge Research 0-1 hrs 11 am - 12 pm Cinemas 0-30 min Eat recurring based on Workand constant 0-1 hrs 4 pm - 6 pm Shopping 6-8 hrs Sleep Lounge 0-1 hrs unique time-use schedules. 8 pm - 11 pm High end restaurants Socialise 0-1 hrs 4 am - 6 am & 1 pm - 3 pm Coffee shops 1-2 hrs Exercise pm- 12 - 9 pm 0-2min hrs 116am pm EatEntertainment 0-30 Museums Income: Spends weekends with Cinemas 0-30 min 12 pm - 11 pmoutside 0-1 Work FigureEat 2.2.3 4 pm - girlfriend 6 pm Sleep 4-6 hrshrs Galleries20,000 GBP/year Savings: None London Theatres Sleep 6-8 hrs 6 pm - 9pm pm 0-1 hrs Lounge 8 pm - 11 Socialise 0-1 hrs Conferences Assets: None No children Socialise hrs Simulation of distinct0-1 user 4 am - 6 am & 1 pm - 3 pm Gyms Exercise 0-1 hrs Spending: Rent, food, travel Movie Parks Exercise 1-2 hrs 12 pm - 11 pm Research 0-1 hrsbuff profiles. Entertainment 0-2 hrs 12 pm - 11 pm Work 0-1 hrs Work 0-1 hrs 6 pm - 9 pm Lounge 0-1 hrs Private Units: 4 Lounge 0-1 hrs

Interactions: 8

Spends weekends with girlfriend outside London Constant Age: No children 33 years old Movie buff Occupation: Travel and fashion blogger Stay: 335 days/year

Cinemas Eat Income: Theatres20,000 GBP/year Sleep Savings: Gyms None Socialise Assets: Parks None Exercise Spending: Rent, food, travel, shopping Entertainment

7 am, 12 pm & 4 pm - 6 pm 0-30 min PlaceEat of interactions:0-30 Framed Single Cinemas min 11 pm - 5 am 6-8 hrs No 6-8 hrs Sleep space. FigureShopping 2.2.3 circulation 4 pm - 11 pm 0-1 children hrs Travels to fashion shows High end restaurants 0-1 hrs Socialise 10 am - 11 am 1-2 hrs Coffee shops 1-2 hrs Exercise 4 pm - 11 pm 0-2 hrs 0-2 hrs Entertainment 9 am - 11 am & 1 pm - 3 pm 0-1 hrs 0-1 hrs Work 4 pm - 7 pm 0-1 hrs 0-1 hrs Lounge

Single No children Travels to fashion shows

Cinemas Shopping High end restaurants Coffee shops

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs

Work Lounge

Eat Sleep Socialise Exercise Entertainment Work

2.2 Objectives: Data Driven Spatial-Customisation_ 11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & 1 pm - 3 pm 6 pm - 9 pm 12 pm - 11 pm

11 am - 12 pm 11 pm - 7 am 7 am - 11 pm 8 am - 5 pm 11Time am - 3 pm 4 pm - 9 pm 11 am - 12 pm

5 pm - 6 pm 12 am - 6 am 1110 amam - 1- pm & 5 pm 129am am- -73am pm 105am pm am- -11 6 am 8 am - 1 pm & 6 1 pm - 3 pm 2 pm - 4 pm 7 pm - 8 pm 12 pm - 1 pm & 11 am - 12 pm 11 pm - 7 am 4 pm - 6 pm 7 am - 11 pm 11 am - 3 pm & 8 am - 5 pm 4 pm - 6 pm 11 am - 3 pm 1 pm - 10 pm 4 pm - 9 pm 9 am - 12 pm 11 am - 12 pm 1 pm - 11 pm 1 pm - 11 pm 4 pm - 6 pm 11 am - 1 pm Time 12 am - 7 am 1110 amam - 12 pmpm - 11 118am am- -31pm pm&& am 1 pm -pm 3pm pm 58 pm - 611 5 pm - -11 pm 2am pm - 4am pm 12 6 5 pm - -11 pm 7am pm - 8pm pm 10 5 12 pm - 1 pm 9 am - 3 pm 5 am - 6 am 4 pm - 6 pm 11 am - 3 pm pm- -12 6 pm 114am pm 1 pm 10 pm 4 pm - 6- pm 9am am - 12 pm 8 pm - -11 pm 11 12 pm 1pm pm - pm 11 6 pm - -97 11 ampm 1 pm 11 pm 9- pm 76 am -- 11 pmpm 4 pm 6 pm 8 am - 5-pm

11 am - 3 pm 4 pm - 9 pm 11 am - 12 pm 1111 amam - 12 - 3pm pm 118am am- -12 11pm pm 4 pm - 6- pm 5 pm 11 pm 8 pm - -11 pmpm 5am pm - 11 11 1 pm & 4 am 12 am- -67am am& 1 12 am pm -- 11 11 pm pm 10 pm- 1- 11 812am pmpm &6 pm -- 39 pm pm 16 pm

2 pm - 4 pm 11 am - 12 pm 7 pm - 8-pm 4 pm 6 pm 12 pm -1 7 am, pmpm & 8 pm12 - 11 116pm pm- -59am pm 11 pm 4 pm 6 pm 6 pm - 9 pm 10 am - 311pm am& 11 pm 4 pm - 611pm am - 10 11 pm am & 19 pm pm - 12 7 pm 94 am pm 1 pm - 11-pm 11 am 12 pm 1 pm 11 4 pm - 6pm pm 411pm - 6- -12 pm 8am pm 11pm pm 4 pm - 6- pm 4 am 6 am & 8 pm 11 pm 12 pm 11 11 am - 12 pmp 4 am - -63am 12 -pm 11&p 11 ampm &1 pm 9- pm 6 pm 9pm pm 86 am -- 11 pm- 11 - 11pm pm 512pm pm -- 11 9 pm 56 pm pm

7 am, 12 pm 11 pm - 5 am 4 pm - 11 pm 10 am - 11 am pm- 12 - 11pm pm 114am 9 am 11 am 4 pm - 6-pm 4 pm - 7pm pm 8 pm - 11 6 pm - 9 pm 6 pm - 9 pm 11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & pm- 12 - 9 pm 116am 12 pm - 11 p 4 pm - 6 pm 6 pm - 9pm pm 8 pm - 11 4 am - 6 am & 1 12 pm - 11 pm 12 pm - 11 pm 6 pm - 9 pm

7 am, 12 pm & 11 pm - 5 am 4 pm - 11 pm 10 am - 11 am 4 pm - 11 pm 9 am - 11 am & 4 pm - 7 pm

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & 1 6 pm - 9 pm 12 pm - 11 pm 6 pm - 9 pm

41


Component: SSRC1 Interactions: 8

Data Driven Spatial Customisation Catalogue Size: 1 x 3 m Visibility: None

Component: RSSC1 Interactions: 8

Size: 1 x 6 m Visibility: All

Size: 3 x 6 m Visibility: Varied

Component: CSSR1 Interactions: 2 Component: RSSC2 Interactions: 8

Component: SSRC2 Interactions: 8

Size: 2 x 4 m Visibility: Varied

Size: 1 x 2 m Visibility: All

Component: CSSR2 Interactions: 8

Size: 1 x 2 m Visibility: None

Size: 1 x 2 m Visibility: Toilet

Size: 1 x 2 m Visibility: Bed

Component: SSCR1 Interactions: 8

Size: 1 x 2 m Visibility: Toilet

Component: RC2 Interactions: 0

Component: SCRR2 Interactions: 8

Component: SC4 Interactions: 2

Component: RSCR1 Interactions: 8

Component: SR4 Interactions: 2

Component: RSCR2 Interactions: 8

Component: SC3 Interactions: 2

Component: SC3 Interactions: 2

Component: SRRC1 Interactions: 8 Component: RRSC Interactions: 8

Component: SC2 Interactions: 0

Component: RC2 Interactions: 2

Component: SR3 Interactions: 0

Component: SC1 Interactions: 2

Component: RC1 Interactions: 2

Component: SR2 Interactions: 2

Component: SRRC2 Interactions: 8

Component: RRSC Interactions: 8

Component: SRRC2 Interactions: 6

Component: SR1 Interactions: 2

42

_2.2 Objectives: Data Driven Spatial-Customisation

2.2 Objectives: Data Driven Spatial-Customisation_

43


2.3 User Path Simulation The aim of the User Path Simulation is to visualise space usage within a spatial aggregation. A co-living housing configuration was generated in order to evaluate the concepts explored in chapter 2.2 “Data Driven Spatial-Customisation” in a comprehensive manner. The furnished configuration shown in figure 2.3.1 is used a framework to map behavioural patterns for three distinct user profiles. The simulation provides an understanding of the following: • Areas of highest density: kitchen • Areas of highest interaction between users: vertical core The results of this path simulation will go on to inform site specific spatial configurations.

Figure 2.3.2 Diagram mapping user paths and interactions in aggregation figure 2.3.1. Number of Interactions: 100 Site specific user profile: Figure 2.3.1

20% Sporadic

Furnished aggregation with

60% Recurring

20% Constant

different user profiles.

44

_2.3 Objectives: User Path Simulation

Figure 2.3.1

Figure 2.3.2

2.3 Objectives: User Path Simulation_

45


Figure 2.3.3

Figure 2.3.4

Sample floor plan of the

Sample floor plan of the

furnished aggregation illustrating

furnished aggregation illustrating

paths and interactions between distinct user profiles.

46

_2.3 Objectives: User Path Simulation

paths and interactions between Figure 2.3.3

Figure 2.3.4

distinct user profiles.

2.3 Objectives: User Path Simulation_

47


Threads of Investigation


3.1 Primitive Game: Intersections and Interactions Kitchen Figure 3.1.1

Figure 3.1.2

The primitive game is the first step of the research to physicalize a model of subscription living. This thread of investigation is directly influenced by the data presented in the chapter 2.2 “Data Driven Spatial Customisation”. The aim of the primitive layout is to provide a dimensional framework with spatial qualities and dimensional metrics of interaction to be developed into architectural geometry. The primitive game encompasses the following steps: • Selecting a primitive shape that will be used to organise space, in this case a cuboid. (3.1.1) • Tailoring the primitive according to spatial functions, dimensional metrics and user requirements. (3.1.2) • Developing a catalogue of primitive aggregations, which negotiates spatial qualities as well as site conditions. (3.1.3) • Simulating user path intersections in order to map interactions between them. (3.1.4)

Figure 3.1.3

Figure 3.1.1: Initial cuboid primitive. Figure 3.1.2: Tailored primitive dimensions according to spatial functions. Figure 3.1.3: Aggregation of primitives negotiating site constraints. Figure 3.1.4: Simulation of path intersections Figure 3.1.4

50

_3.1 Primitive Game

between different users.

3.1 Primitive Game_

51


3.1.1 Seminal Projects: Dimensional Metrics of Interactions

The research of the primitive layout is anchored by seminal projects which provide a foundation for cataloguing spatial requirements and dimensional metrics for interactions: The layout of the primitives is influenced by the following:

• Frankfurt Kitchen by M. Schutte - Lihotzky, 1926. (3.1.1.1)

- The project is an attempt at “rationalising the housewife’s work” (Schutte, 1927) by carefully studying logical work-flow sequences within the kitchen. The project presents the potential for Dwell.t to re-design spaces according to usage patterns. Architect’s Data by E. Neufert, 1936 (3.1.1.2) - The book provides an extensive compilation of space layout according to ergonomic principles and building typology (Neufert, 1970). The layouts present an initial reference for spatial requirements in building design, which Dwell.t seeks to apply to shared living spaces.

Figure 3.1.1.1

Proxemics by E. Hall, 1963 (3.1.1.3) - A branch of knowledge developed by an American anthropologists which studies “the human use of space and the effects it has on behaviour, communication and social patterns” (Hall, 1966). Proxemics provides a foundation for Dwell.t to differentiate dimensional metrics of interactions between residents and visitors.

Figure 3.1.1.1: Image of original kitchen. Floor plan of kitchen layout outlining the recurring usage paths. (Schutte, 1927) Figure 3.1.1.2: Diagrams illustrating the distinct ergonomic dimensions depending on activities in the kitchen. (Neufert, 1970) Figure 3.1.1.2

Figure 3.1.1.3

Figure 3.1.1.3: Diagram demarcating zones of interpersonal distances. (Hall, 1966)

52

_3.1 Primitive Game: Seminal Projects

3.1 Primitive Game: Seminal Projects_

53


Kitchen

3.1.2 Co-living Neufert Digital Neufert refers to the combination of dimensional accuracy and proxemics as a way to digitalize spatial requirements for shared living. This combination provides a new measure of space which delineates the minimum distance required by each user type to initiate verbal / social interactions. (3.1.2.1)

User Ratio: Sporadic: 3 Recurring: 3 Constant: 4

The research investigates digital proxemics within different social functions such as kitchen, work and lounge areas. (3.1.2.2 - 3.1.2.4) The contextual functions of the space directly correlate to the size of the bubbles around the users. Whereby, a sporadic user is more likely to initiate an interaction in a work area rather than the kitchen. Each of these sample catalogues illustrate the space at a maximum capacity, even though each user has a different time schedule, as seen in chapter 2.2 “Data Driven Spatial Customisation�.

User Ratio: Sporadic: 6 Recurring: 2 Constant: 2

Zone of interaction: Arms side to side

Sporadic User

User Ratio: Sporadic: 2 Recurring: 6 Constant: 2

Zone of interaction: Elbows bent

Recurring User

User Ratio:

Figure 3.1.2.1:

Sporadic: 2

Dimensional diagram

Sample catalogue of kitchen

Constant: 6

interpersonal distance required by each user type to initiate

Zone of interaction: Arms extended

verbal or social interactions.

Figure 3.1.2.1

54

Figure 3.1.2.2:

Recurring: 2

demarcating the minimum

_3.1 Primitive Game: Co-living Neufert

iterations, outlining spatial

Constant User

requirements according to user Figure 3.1.2.2

ratio within a group of 10 users.

3.1 Primitive Game: Co-living Neufert_

55


Figure 3.1.2.3: Sample catalogue of work area iterations, outlining spatial

Work Area

Lounge

User Ratio:

User Ratio:

Sporadic: 3

Sporadic: 3

Recurring: 3

Recurring: 3

Constant: 4

Constant: 4

User Ratio:

User Ratio:

Sporadic: 6

Sporadic: 6

Recurring: 2

Recurring: 2

Constant: 2

Constant: 2

User Ratio:

User Ratio:

Sporadic: 2

Sporadic: 2

Recurring: 6

Recurring: 6

Constant: 2

Constant: 2

User Ratio:

User Ratio:

Sporadic: 2

Sporadic: 2

Recurring: 2

Recurring: 2

Constant: 6

Constant: 6

Figure 3.1.2.4: Sample catalogue of lounge iterations, outlining spatial requirements according to user

requirements according to user ratio within a group of 10 users.

56

Figure 3.1.2.3

_3.1 Primitive Game: Co-living Neufert

Figure 3.1.2.4

ratio within a group of 10 users.

3.1 Primitive Game: Co-living Neufert_

57


3.1.3 Intrinsic Rules

Figure 3.1.3.1

The Primitive Game is a negotiation of intrinsic and extrinsic rules which are motivated by the objective of maximizing path intersections that can lead to interactions between different user profiles. The intrinsic rules are those belonging to the aggregation of the cuboid primitive, without regarding site or structural constraints. The rules are as follows:

• Distribution of circulation through the aggregation of primitives,

in order to ensure that different user profiles traverse social areas in every floor, rather than circulating through a single vertical core. (3.1.3.1)

Gym

Kitchen Laundry Work Entertainment

Lounge

• Stacking of one social unit per floor. At its preferred state, each level consists of one social function to maximize the circulation across the aggregation. (3.1.3.2)

Figure 3.1.3.2

• Placement of private units around perimeter of social area to

encourage a codependency between the user and the community at large (3.1.3.3) Figure 3.1.3.1: Diagram outlining circulation patterns through the primitive aggregation. Figure 3.1.3.2: Diagram illustrating stacking order or social units in primitive aggregation. Figure 3.1.3.3: Sample aggregation illustrating placement of private units at Figure 3.1.3.3

58

_3.1 Primitive Game: Intrinsic Rules

perimeter area of social units.

3.1 Game Layout: Intrinsic Rules_

59


3.1.4 Extrinsic Rules

Figure 3.1.4.1

The intrinsic rules illustrated in the previous chapter are negotiated with extrinsic rules steaming from the site. Beginning with Site 01 located in the borough of Islington in the area of Clerkenwell. (3.1.4.1) The context of each site is investigated in order to determine a specific user ratio. (3.1.4.2). In the case of Site 01, a ratio of 2 sporadic user per each recurring and constant user was identified. (3.1.4.3) The application of the intrinsic rules on site begins with the negotiation of following: • Structural requirements, i.e: minimizing of cantilevers. • Sunlight and ventilation for all social and private units • Street frontage which provides public space on the ground floor as well as terracing throughout the aggregation. The Primitive Game: Intersections and Interactions negotiates intrinsic and extrinsic rules multiple times. Each iteration has a unique starting condition and prioritizes one or two rules at a time. (3.1.4.4 - 3.1.4.5).

Figure 3.1.4.2

Figure 3.1.4.1: Map illustrating area of Islington, Clerkenwell. Figure 3.1.4.2: Map illustrating the 6 infill sites deployed in the are delineated in figure 3.1.4.1. Figure 3.1.4.3: Map outlining user ratio according to facilities and Figure 3.1.4.3

60

_3.1 Primitive Game: Extrinsic Rules

amenities in proximity of Site 01.

3.1 Primitive Game: Extrinsic Rules_

61


Negotiation Site 01 Sunlight + Structure 16 Units

Game 01 23 Units

Game 02 21 Units

Game 03 19 Units

Game 04 17 Units

Game 05 20 Units

Figure 3.1.4.4: Catalogue illustrating iterations of Primitive Game in which the intrinsic rules are negotiated with on site restrictions, in this case sunlight and structure.

62

_3.1 Primitive Game: Extrinsic Rules

Game 06 Figure 3.1.4.4

3.1 Primitive Game: Extrinsic Rules_

63


Negotiation Site 01 Structure + Street Frontage 20 Units

Game 07 11 Units

Game 08 8 Units

Game 09 17 Units

Game10 6 Units

Game 11 23 Units

Figure 3.1.4.5: Catalogue illustrating iterations of Primitive Game in which the intrinsic rules are negotiated with on site restrictions, in this case structure and street frontage.

64

_3.1 Primitive Game: Extrinsic Rules

Game 12 Figure 3.1.4.5

3.1 Primitive Game: Extrinsic Rules_

65


3.1.5 Evaluative Metrics The resulting iterations from the Primitive Game are evaluated by the following parameters: Firstly, • Number of private units achieved in the final aggregation. The iterations showing a magenta box in figures 3.1.4.4 and 3.1.4.5 are deemed successful in terms of unit count; thus they are evaluated by a second set of metrics: • Total of square meters on the ground floor available to the public • Total of square meters dedicated to terracing throughout the aggregation. The resulting iterations shown in figures 3.1.5.1- 3.1.5.3 are further evaluated through a time-use occupant simulation, which will determine the number of possible interactions between users within the primitive aggregation. Figure 3.1.5.2

Figure 3.1.5.2 Game 03 negotiating intrinsic rules + sunlight and structure. The game totalled 21 units in the aggregation. Figure 3.1.5.1

Figure 3.1.5.3

Game 02 negotiating intrinsic

Game 07 negotiating intrinsic

rules + sunlight and structure.

rules + structure and street frontage. The game totalled 20

The game totalled 23 units in the aggregation.

66

Figure 3.1.5.1

_3.1 Primitive Game: Evaluative Metrics

Figure 3.1.5.3

units in the aggregation.

3.1 Primitive Game: Evaluative Metrics_

67


3.1.6 Time-Use Occupancy Simulation

Profile

Profile

The aim of the time-use occupancy simulation is the following: • Analyse a spatial configuration, in this case the primitive aggregations, in order to identify possible spaces for user interaction. • Visualize daily usage patterns of functions such as kitchen, work areas and lounge • Simulate a path following users daily cycles from real time data, in this case the research follows the data provided by the UK government Electrical Survey, 2012 as outlined in chapter 2.2“Data Driven Spatial Customisation”. Game 02 is taken as spatial framework to run a time-use simulation. (3.1.6.1). Three individual simulations are ran for each user type, sporadic, recurring and constant. The different colour in the individual paths indicate the time of the day a user was at a given space. (3.1.6.2) Thus the simulation can precisely locate any given user in time and space. The three unique user paths are cross-referenced to find specific moments of path intersections between the users. (3.1.6.3) Such intersections are identified as possible moments on interactions. (3.1.6.4) Game 02 Gym

Recurring Age: 21 years old Occupation: Student Stay: 180 days/year

Constant Age: 27 years old Occupation: Nurse Stay: 335 days/year

Recurring Age: 72 years old Occupation: Pensioner Stay: 180 days/year Sporadic Age: 32 years old Occupation: Cabin crew Stay: 24 days/year

Sporadic Age: 40 years old Occupation: Academic and Entrepreneur Stay: 24 days/year Recurring Age: 25 years old Occupation: Personal trainer Stay: 180 days/year

Constant Age: 33 years old Occupation: Travel and fashion blogger Stay: 335 days/year

Laundry

Sporadic Age: 44 years old Occupation: Banker Stay: 24 days/year

Recurring Age: 21 years old Occupation: Student Stay: 180 days/year

Work

Entertainment

Figure 3.1.6.1 Social areas of game 02, which serve as a spatial framework

Lounge

for an example of time-use occupant simulation.

68

Figure 3.1.6.1

_3.1 Primitive Game: Time-Use Occupancy Simulation

Economic

Social

Income: 95,000 GBP/ year Savings: 10% of income Assets: 2-bedroom apartment Spending: Rent, food, travel, leisure

Married Recurring No children Age: Works remotely 21with years old Socialises co-workers Occupation: Student Stay: 180 days/year

Economic

Social

Income: 95,000 GBP/ year Savings: 10% of income Assets: 2-bedroom apartment Spending: Rent, food, travel, leisure

Married No children Works remotely Socialises with co-workers

Cultural

Usage pattern

Eat Trendy restaurants Income: 8,000 GBP/ year Sleep Lounges Savings: None Work Travel Assets: None Clean Politics Spending: Tuition, rent, food Exercise Film

Duration/day

Cultural Trendy restaurants Lounges Travel Politics Film

Usage pattern

Duration/day

Time

Eat Sleep Work Clean Exercise

0-30 min 4-6 hrs 2-3 hrs 0-20 min 30 min-1 hr

5 pm - 6 pm 12 am - 6 am 10 am - 5 pm 9 am - 3 pm 5 am - 6 am

Time

0-30 min 5 pm - 6 pm Single 4-6 hrs 12 am - 6 am No 2-3 children hrs 10 am - 5 pm Works part-time 9 am - 3 pm 0-20 min Socialises other 30 min-1 hrwith Profile 5 amstudents - 6 am

Bars Concerts Museums Economic Galleries

11 am - 12 pm & 5 pm - 6 pm 0-30 min Eat 11 pm - 7 am 6-8 hrs Sleep 3-4 hrs Social 7 am - 11 pm Work Cultural 8 am - 5 pm 0-20 min Clean 11 am - 3 pm 1-2 hrs Socialise 4 pm - 9 pm 1-2 hrs Entertainment Income: 95,000 GBP/ year Married Trendy restaurants Sporadic 11 am - 12 pm & 4 pm - 6 pm 0-1 hrs Cook Savings: 10% of income No children Lounges Age: Assets: 2-bedroom apartment Works remotely Travel 44 years old Single Bars Spending: Rent, food, travel, leisure Socialises with co-workers Politics 11 am - 12 pm & 5 pm - 6 pm 0-30 min Eat Income: 8,000 GBP/ year Occupation: Income: 11 am - 1 pm & 4 pm - 6 pm 0-30 min Eat Engaged Coffee Concerts30,000 GBP/year No children Film Constant 11 pm - 7 am 6-8 hrs Sleep Savings: None Banker Savings: 12 am - 7 am 6-8 hrs Sleep 2-year-old son Stay: Comedy clubs Museums10% of incomeWork Works part-time Age: 7 am 11 pm 3-4 hrs Assets: None User Assets: Economic Social Cultural 10 am - Time 11 pm 3-4 hrs Duration/day Work Usage pattern Sports events Works night shifts Profile Socialises other GalleriesNone 27with years old students am - 5 pm 0-20 min Clean Spending: Tuition, rent, food 248 days/year Spending: Rent, food, leisure 8 am - 1 pm & 6 pm - 9 pm 0-20 min Clean Sports classes Socialises with other gym-goers Music events Occupation: 11 am - 3 pm 1-2 hrs Socialise 1 pm - 3 pm 1-2 hrs Exercise Nurse 4 pm - 9 pm 1-2 hrs Entertainment Eat pm - 6 pm Income: 95,000 GBP/ year Trendy restaurants Married 1-2 hrs 0-30 min2 pm - 45pm Socialise Stay: Sporadic 11 am - 12 pm & 4 pm - 6 pm 0-1 hrs Cook Bars Recurring Income: 8,000 GBP/ year Sleep 4-6 hrs 7 pm - 812 Savings: 10% of income Lounges No children pmam - 6 am 0-1 hrs Single Entertainment Age: 335 days/year Concerts Age: Savings: None Cook Work 2-3children hrs 12 pm - 10 am&- 55 pm pm- 6 pm Assets: 2-bedroom apartment Works remotely Travel 1 pm 0-1 hrs No 44 years old Works part-time 9 am - 3 pm Museums 21with years old Assets: None Clean 0-20 min Spending: Rent, food, travel, leisure Socialises co-workers Politics Occupation: 11 am - 1 pm & 4 pm - 6 pm 0-30 min Eat Income: 30,000 GBP/year Coffee Engaged Socialises with other Galleries Occupation: Spending: Tuition, rent, food Exercise 30 min-1hr 30 min-14hrpm 5pm amstudents - 6 am Film Banker Income: 18,000 GBP/year 6 Eat Libraries Widow Constant 12 am - 7 am 6-8 hrs Sleep Savings: 10% of income Comedy clubs 2-year-old son Music events Student Stay: Savings: Pension 11 am 3 pm & 12 am 4 am Sleep Museums No children 6-8 hrs Age: 10 am - 11 pm 3-4 hrs Work Assets: None Works night shifts Sports events Stay: 24 days/year Assets:classes Owns 2-bedroom home 4 pm - 6 pm Cook Long walks Baby sits during free time 3-4 hrs 67with years old gym-goers 8 am 1 pm & 6 pm 9 pm 0-20 min Clean Spending: Rent, food, leisure Socialises other Sports 180 days/year Spending: Rent, food, travel 1 pm - 10 pm Read Baking Socialises with book 1-2 hrs Occupation: 1 pmclub - 3 pm 1-2 hrs Exercise 9 am - 12 pm Clean 0-20 min Pensioner 2 pm - 4 pm 1-2 hrs Socialise Socialise 1-2 hrs 0-30 min1 pm - 11 Stay: Recurring Bars 11pm am - 12 pm & 5 pm - 6 pm Eat Income: 8,000 GBP/ year 7 pm - 8 pm 0-1 hrsSingle Entertainment Income: 30,000 GBP/year Coffee Entertainment 0-2 hrs Engaged 335 days/year Concerts Age: Constant 11pm pm - 7 am 6-8 hrs 1 pm - 11 Sleep Savings: None Cook 12 pm - 1 pm & 5 pm - 6 pm 0-1 hrsNo children Savings: 10% of Leisure incomeWork Comedy clubs pm - 67pm 0-1 hrs 2-year-old Museums Works part-time 21 years old Age: am - 11 pm 3-4 hrs 4 son Assets: None Assets: None Works night shifts Sports events Galleries Socialises other students Occupation: 274with years old 8 am - 5 pm 0-20 min Clean Spending: Tuition,Eat rent, food pm - 6 pm Income: 18,000 GBP/year Widow Libraries 30 min-1hr Spending: Rent, food, leisure Socialises with other gym-goers Sports classes Music events Student Occupation: Socialise 0-30 min1-2 hrs 11 am - 11 Eat Married 12 am pm - 3 pm 11 am - 3 pm & 12 am - 4 am Sleep Savings: Pension No children Museums 6-8 hrs Vintage car shows Income: 25,000 GBP/year Recurring Stay: Nurse Sleep Entertainment 23-4 daughters 3 pm pm -&91pm am - 5 am 4-6 hrs 1-2 hrs 11 am - 4 4 pm - 6 pm Cook Assets: Owns 2-bedroom home Baby sitsAge: during free time Long walks hrs Cafes Savings: Pension 180 days/year Stay: 11 am 12 pm & 4 pm 6 pm 0-1 hrs Cook Socialise Occasionally visits daughters 8 am - 11 pm 2-3 hrs 1 pm - 10 pmin London Read Spending: Rent, food, travel Socialises book Baking 1-2 hrs Long walks Assets: Owns 4-bedroom home 72with years old club 335 days/year Entertainment Owns restaurant 9 am - 12 pm 5 pm - 11 pm 1-2 hrs Clean 0-20 min Jazz clubs Spending: Rent, food, travel Occupation: Lounge 5 pm - 11 pm 1-2 hrs 1 pm - 11 pm Socialise 1-2 hrs Pensioner 11 am - 1 pm & 4 pm - 6 pm 0-30 min Eat Income: 30,000 GBP/year Coffee Entertainment 0-2 hrsEngaged 1 pm - 11 pm Stay: Constant Income: 18,000 GBP/year Libraries Widow Constant 12 am - 7 am 6-8 hrs Sleep Savings: 10% of income Comedy clubs pm - 6 pm Leisure 0-1 hrs2-year-old 4son 180 days/year Age: Savings: Pension Museums No children Age:shifts 10 am - 11 pm 3-4 hrs Work Assets: None Sports events Works night 27 years old Assets: Owns 2-bedroom home Long walks Baby sits during free time 67with years old gym-goers 8 am - 1 pm & 6 pm - 9 pm 0-20 min Clean Spending: Rent, food, leisure Sports classes Socialises other Occupation: Spending: Rent, food, travel Baking Socialises with book club Eat 11 am - 12 pm 0-30 min Married Occupation: Income: 25,000 GBP/year Vintage car shows pm - 3 pm Exercise 0-30 min1-2 hrs 11 am - 1 Income: 20,000 GBP/year 12 pm Eat Sporadic Techno clubs Single Nurse Sleep 11 am - 3 pm & 1 am - 5 am 4-6 hrs 2 daughters Pensioner Savings: Pension Cafes pm - 4 pm Savings: None Sleep Socialise 4-6 hrs 1-2 hrs 4 pm - 62pm Age: visits Japanese food No children Stay: Socialise 8 am 11 pm 2-3 hrs Occasionally daughters in London Stay: Assets: Owns 4-bedroom home Long walks 7 pm Entertainment Assets: None pm - 8 pm 0-1 hrs 0-1 hrs 8 pm - 11 Socialise 32 years Volunteer projects Pursuing degree 335old days/year Entertainment 5 pm - in 11psychology pm 1-2 hrs online335 Owns restaurant days/year Spending: Rent, food, travel Jazz clubs Cook Spending: Food, leisure,Lounge shopping pmpm - 1 pm & 5 pm - 6 pm 0-1 hrs 0-1 hrs 6 pm - 912 Entertainment Occupation: Plays rugby 5 pm - 11 pm 1-2 hrs 6 pm - 9 pm 0-1 hrs Lounge Cabin crew 4 pm - 6 pm Eat Income: 18,000 GBP/year Widow Libraries 30 min-1hr Stay: Constant Married 11 am - 3 pm & 12 am - 4 am Sleep Savings: Pension No children Museums Income: 25,000 GBP/year Recurring Vintage car shows 6-8 hrs Age: 24 days/year 23-4 daughters 4 pm - 6 pm Cook Assets: Owns 2-bedroom home Baby sitsAge: during free time Long walks Savings: Pension Cafes hrs 67 years old Occasionally visits daughters 1 pm - 10 pmin London Read Spending: Rent, food, travel Socialises book Baking Assets: Owns 4-bedroom home 72with years old club Long walks 1-2 hrs Occupation: 11 am - 12 pm 0-30 min Eat Income: 20,000 GBP/year Single Techno clubs Owns restaurant Clean Spending: Rent, food, travel Occupation: Jazz clubs 0-20 min Pensioner Eat 0-30 min Income: 55,000 11 am - 9 12am pm- 12 pm Sporadic Museums Single 4 pm - 6 pm 4-6 hrs Sleep Savings: None No children Japanese food GBP/year pm - 11 pm Socialise 4-6 hrs 1-2 hrs 4 pm - 61pm Pensioner Stay: Sleep Savings: 10% of income Age: Galleries No children 8 pm - 11 pm 0-1 hrs Socialise Assets: None Pursuing online degree in psychology Volunteer projects 1 pm - 11 pm Entertainment Stay: 0-2 hrs 8 pm - 11 335old days/year Socialise 0-1 hrs Assets: None pm 40 years Conferences Visits London for lectures and reviews 6 pm - 9 pm 0-1 hrs Entertainment Spending: Food, leisure, shopping Plays rugby pm&-16pm pm- 3 pm Leisure 0-1 hrs 0-1 hrs 4 am - 64am 180 days/year Exercise Spending: Rent, research, food Occupation: 6 pm - 9 pm 0-1 hrs Lounge Research 0-1 hrs 12 pm - 11 pm Academic and Work Eat 0-1 hrs 0-30 min12 pm - 11 11 am pm - 12 pm Entrepreneur Married Recurring Income: 25,000 GBP/year Vintage car shows Income: 20,000 Lounge GBP/year Sporadic 0-1 hrs Single pmam - 3 pm & 1 am - 5 amTechno clubs Stay: Age: Sleep 4-6 hrs 6 pm - 911 2 daughters Savings: Pension Cafes Savings: None Age: visits daughters in London No Japanese food 24 days/year Socialise 8 am - 11 pm 2-3children hrs Occasionally 72 years old Assets: Owns 4-bedroom home Long walks Assets: None 32 years old Pursuing Volunteer projects Entertainment 5 pm - in 11psychology pm 1-2 hrs online degree Owns restaurant Occupation: Spending: Rent, food, Jazz clubs Eat travel 0-30 min 11 am 12 pm Income: 55,000 GBP/year Single Museums Spending: Food, leisure,Lounge shopping Occupation: Plays rugby 5 pm & - 11 pm- 6 pm Pensioner 4 pm Recurring Income: Spends with- girlfriend outside Cinemas Eat 0-30 min1-2 hrs 7 am, 12 Sleep 4-6 hrs weekends 4 pm 6 pm Savings: 10% of income No children Galleries20,000 GBP/year Cabin crew 11 pm - 5 am Age: Stay: Savings: None London Theatres Sleep 6-8 hrs Socialise 0-1 hrs 8 pm - 11 pm Assets: None Visits London for lectures and reviews Conferences Stay: 180old days/year 4 pm - 11 pm 25 years Assets: None No hrs children Socialise 0-1 hrs Exercise 0-1 am - 6 am & 1 pm - 3 pm Gyms Spending: Rent, research, food 244 days/year 10 am - 11 am Spending: Rent, food, travel Movie Parks Occupation: Exercise 1-2 hrs Research 0-1 hrsbuff 12 pm - 11 pm 4 pm - 11 pm Personal trainer Entertainment 0-2 hrs Work 0-1 hrs 12 pm - 11 pm pm - 3 pm Stay: Sporadic 0-1 hrs 0-30 min9 am - 11 11am am&-112 pm Income: 20,000 GBP/year Techno clubs Work Eat Lounge 0-1 hrsSingle 6 pm - 9 pm Income: 55,000 Sporadic Museums 180 days/year LoungeSleep 0-1 hrs Single pm - 6 pm 4-6 hrs 4 pm - 74pm Age: Savings: None No children Japanese food GBP/year Savings: 10% of incomeSocialise No Galleries 8 pm - 11 pm 0-1children hrs 32 years old Assets: None PursuingAge: online degree in psychology Volunteer projects Assets: None 40 years old Visits and reviews Conferences pm - 9 pm 0-1 hrsLondon for6lectures Entertainment Occupation: Spending: Food, leisure, shopping Plays rugby 7 am, 12 pm & 4 pm - 6 pm Income: 20,000 GBP/year Spends weekends with girlfriend outside Cinemas Eat 0-30 min Spending: Rent, research, food Occupation: pm - 9 pm 0-1 hrs 11 am - 6 Lounge Cabin crew 12 pm Eat Single Cinemas Income: 20,000 GBP/year 0-30 min Constant 11 pm - 5and am Savings: None London Theatres Sleep 6-8 hrs Academic Stay: 4 pm 6 pm Sleep Savings: None No children Shopping 6-8 hrs Age: 4 pm - 11 pm Assets: None No children Gyms Socialise 0-1 hrs Entrepreneur 24 days/year 8 pm - 11 pm Assets: Travels shows High end restaurants Socialise 0-1 hrs 33 years old 10 am 11 am Spending: Rent, food, travel Movie buff Parks None Exercise 1-2 hrs to fashion Stay: 4 am - 6 am & 1 pm - 3 pm Exercise Spending: Rent, food, travel, shopping Coffee shops 1-2 hrs Occupation: pm - 11 pm Entertainment 0-2 hrs 244 days/year 6 pm - 9 pm Entertainment 0-2 hrs Travel and 9 am - 11 am & 1 pm - 3 pm Work 0-1 hrs pm - 12 pm Work Eat 0-1 hrs 0-30 min 12 pm - 11 am fashion blogger Sporadic Income: 55,000 GBP/year Museums 4 pm - 7 pm Lounge 0-1 hrsSingle Recurring Income: 20,000 GBP/year Spends with- girlfriend outside Cinemas 6 pm - 94pm LoungeSleep 0-1 hrs 4-6 Stay: Age: pm 6 pm Savings: 10% of income hrs weekends No children Galleries Age: for lectures and reviews Savings: None London Theatres 335 days/year 8 pm - 11 pm 40 years old Assets: None Socialise 0-1 hrs Visits London Conferences Assets: None No children 25 years old 4 am - 6 am & 1 pm - 3 pm Gyms Occupation: Spending: Rent, research, food Exercise 0-1 hrs 11 am - 12 pm Eat Income: 20,000 GBP/year Single Cinemas 0-30 min Spending: Rent, food, travel Movie buff Parks Occupation: User Economic Social Cultural Usage pattern Duration/day Time 12 pm - 11 pm Research 0-1 hrs Profile Academic and 4 pm - 6trainer pm Sleep Savings: None No children Shopping 6-8 hrs Personal 12 pm - 11 pm Entrepreneur Work 0-1 hrs 8 pm - 11 pm Assets: None Travels to fashion shows High end restaurants Socialise 0-1 hrs Stay: 6 pm - 9 pm Stay: Lounge 0-1 hrs 4 am - 6 am & 1 pm - 3 pm Exercise Spending: Rent, food, travel, shopping Coffee shops 1-2 hrs 180 days/year Income: 95,000 GBP/ year Eat 0-30 min 5 pm - 6 pm Married Trendy restaurants Sporadic24 days/year 6 pm - 9 pm Entertainment 0-2 hrs Savings: 10% of income Sleep 4-6 hrs 12 am - 6 am No children Lounges Age: 12 pm - 11 pm Work 0-1 hrs Assets: 2-bedroom apartment Work 2-3 hrs 10 am - 5 pm Works remotely Travel 44 yearsRecurring old 7 am, 12 pm & 4 pm - 6 pm Income: 20,000 GBP/year Cinemas Eat 0-30 min 6 pm - 9 with pm girlfriend outside Lounge 0-1 hrsSpends weekends Spending: Rent, food, travel, leisure Clean 9 am - 3 pm11 pm - 5 am SocialisesLondon with co-workers Politics Theatres Income: 20,000 GBP/year Cinemas Occupation: Constant Age: Savings: None Sleep 0-20 min Single 6-8 hrs 30 min-1 hrNo 5 am - 6 am4 pm - 11 pm Film Savings: NoneExercise Socialise Shopping Banker 25 years old Age: Assets: None No children Gyms 0-1children hrs Assets: None Travels High end restaurants Stay: Occupation: 33 years old am - 11 am Spending: Rent,Usage food, pattern travel Movie buff Parks Exercise 1-2 hrs to fashion10shows Economic Social Cultural Duration/day Time Spending: Rent, food, travel, shopping Coffee shops 24 days/year Occupation: 4 pm - 11 pm Personal trainer Entertainment 0-2 hrs Travel and 9 am - 11 am & 1 pm - 3 pm Stay: Work 0-1 hrs fashion blogger 4 pm - 7 pm 180 days/year Lounge 0-1 hrs Eat 0-30 min 5 pm - 6 pm Income: 95,000 GBP/ year Married Trendy restaurants Stay: Single Bars Recurring Income: 11 am - 12 pm & 5 pm - 6 pm 0-30 min Eat Sleep 4-6 hrs 12 am - 6 am Savings: 10% of income No children Lounges8,000 GBP/ year 335 days/year No Concerts Age: Savings: 11 pm - 7 am 6-8 hrs Sleep Work 2-3 children hrs 10 am - 5 pm Assets: 2-bedroom apartment Travel None Works remotely Works part-time MuseumsCinemas 21with years old Assets: 7 am - 11 pm 3-4 hrs Work 0-20 min Spending: Rent, food, travel, leisure Politics None Socialises co-workers 11 am - 12 pm Income: 20,000Clean GBP/year Single 9 am - 3 pm 0-30 min Eat Constant Socialises other Galleries Shopping Occupation: Spending: Tuition, None rent, food 8 am - 5 pm4 pm - 6 pm Clean Exercise 30 min-1 No hrwith 5 amstudents - 6 am Film children Savings: Sleep 0-20 min 6-8 hrs Age: Music events Student 33 years old 11 am - 3 pm 1-2 hrs Socialise Socialise 8 pm - 11 pm Assets: None Travels to fashion shows High end restaurants 0-1 hrs Stay: Occupation: 4 pm - 9 pm4 am - 6 am & 1 pm - 3 pm 1-2 hrs Entertainment Spending: Rent, food, travel, shopping Coffee shops 1-2 hrs Exercise 180 days/year 11 am 12 0-1 hrs Cook 6pm pm& -49pm pm- 6 pm 0-2 hrs Entertainment Travel and 12 pm - 11 pm 0-1 hrs Work fashion blogger 6 pm - 9 pm 0-1 hrs Lounge Stay: Single Bars 11 am - 12 pm & 5 pm - 6 pm 0-30 min Eat Income: 8,000 GBP/ year Income: 30,000 GBP/year 11 am - 1 pm & 4 pm - 6 pm 0-30 min Eat Engaged Coffee 335 days/year No children Concerts Constant 11 pm - 7 am 6-8 hrs Sleep Savings: None Savings: 12 am - 7 am 6-8 hrs Sleep 2-year-old son Comedy clubs Works part-time Museums10% of incomeWork Age: 7 am - 11 pm 3-4 hrs Assets: None Assets: 10 am - 11 pm Work 3-4 hrs Works night shifts Sports events Socialises other GalleriesNone 27with years old students 8 am - 5 pm 0-20 min Clean Spending: Tuition, rent, food Spending: Rent, food, leisure 8 am - 1 pm & 6 pm - 9 pm Clean 0-20 min Socialises with other gym-goers Sports classes Music events Occupation: 11 am - 3 pm 1-2 hrs Socialise 1 pm - 3 pm Exercise 1-2 hrs Nurse 4 pm - 9 pm 1-2 hrs Entertainment 2 pm - 4 pm Socialise 1-2 hrs Stay: 11 am - 12 pm & 4 pm - 6 pm 0-1 hrs Cook 7 pm - 8 pm 0-1 hrs Entertainment 335 days/year 12 pm - 1 pm & 5 pm - 6 pm 0-1 hrs Cook

User

Recurring

User

Constant Age: 27 years old Occupation: Nurse Stay: 335 days/year

Income: 30,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, food, leisure

Engaged Constant 2-year-old son Age: Works night shifts 67 years old Socialises with other gym-goers Occupation: Pensioner Stay: 335 days/year

Eat Coffee Income: 18,000 GBP/year Sleep Comedy clubs Savings: Pension Work Sports events Assets: Owns 2-bedroom home Clean Sports classes Spending: Rent, food, travel Exercise Socialise Entertainment Cook

11 am - 1 pm & 4 pm - 6 pm 0-30 min Widow Libraries 12 am - 7 am 6-8 hrs No children Museums 10 am - 11 pm 3-4 hrs Baby sits during free time Long walks 8 am - 1 pm & 6 pm - 9 pm 0-20 min Socialises with book club Baking 1 pm - 3 pm 1-2 hrs 2 pm - 4 pm 1-2 hrs 7 pm - 8 pm 0-1 hrs 12 pm - 1 pm & 5 pm - 6 pm 0-1 hrs

Constant Age: 67 years old Occupation: Pensioner Stay: 335 days/year

Income: 18,000 GBP/year Savings: Pension Assets: Owns 2-bedroom home Spending: Rent, food, travel

Widow Recurring No children Baby sitsAge: during free time 72with years old club Socialises book Occupation: Pensioner Stay: 180 days/year

Eat Libraries Income: 25,000 GBP/year Sleep Museums Savings: Pension Cook Long walks Assets: home Read Baking Owns 4-bedroom Spending: Rent, food, travel Clean Socialise Entertainment Leisure

4 pm - 6 pm 30 min-1hr Married Vintage car shows 11 am - 3 pm & 12 am - 4 am 6-8 hrs 23-4 daughters Cafes 4 pm - 6 pm hrs Occasionally visits daughters Long walks 1 pm - 10 pmin London 1-2 hrs Owns restaurant 9 am - 12 pm Jazz clubs 0-20 min 1 pm - 11 pm 1-2 hrs 1 pm - 11 pm 0-2 hrs 4 pm - 6 pm 0-1 hrs

Recurring Age: 72 years old Occupation: Pensioner Stay: 180 days/year

Income: 25,000 GBP/year Savings: Pension Assets: Owns 4-bedroom home Spending: Rent, food, travel

Married Sporadic 2 daughters Age: Occasionally visits daughters in London 32 years old Owns restaurant Occupation: Cabin crew Stay: 24 days/year

Eat Vintage car shows Income: 20,000 GBP/year Sleep Cafes None Savings: Socialise Long walks Assets: None Jazz clubsFood, leisure,Entertainment Spending: shopping Lounge

11 am - 12 pm 0-30 min Single Techno clubs 11 am - 3 pm & 1 am - 5 am 4-6 hrs No children Japanese food 8 am - 11 pm 2-3 hrs Pursuing online degree in psychology Volunteer projects 5 pm - 11 pm 1-2 hrs Plays rugby 5 pm - 11 pm 1-2 hrs

Sporadic Age: 32 years old Occupation: Cabin crew Stay: 24 days/year

Income: 20,000 GBP/year Savings: None Assets: None Spending: Food, leisure, shopping

Single Sporadic No children Age: Pursuing online degree in psychology 40 years old Plays rugby Occupation: Academic and Entrepreneur Stay: 24 days/year

Eat Techno clubs Income: 55,000 GBP/year Sleep Japanese food Savings: 10% of income Socialise Volunteer projects Assets: None Entertainment Spending: Rent, research, food Lounge

11 am - 12 pm 0-30 min Single 4 pm - 6 pm 4-6 hrs No children 8 pm - 11 pm 0-1 hrs Visits London for lectures and reviews 6 pm - 9 pm 0-1 hrs 6 pm - 9 pm 0-1 hrs

Sporadic Age: 40 years old Occupation: Academic and Entrepreneur Stay: 24 days/year

Income: 55,000 GBP/year Savings: 10% of income Assets: None Spending: Rent, research, food

Single Recurring No children Age: for lectures and reviews Visits London 25 years old Occupation: Personal trainer Stay: 180 days/year

Eat Museums Income: Sleep Galleries20,000 GBP/year Savings: None Socialise Conferences Assets: None Exercise Spending: Rent, food, travel Research

0-30 min 11 am - 12 pm Spends with- girlfriend outside 4-6 hrs weekends 4 pm 6 pm London 0-1 hrs 8 pm - 11 pm No hrs children 0-1 4 am - 6 am & 1 pm - 3 pm Movie 0-1 hrsbuff 12 pm - 11 pm 0-1 hrs 12 pm - 11 pm 0-1 hrs 6 pm - 9 pm

Work Lounge

Usage pattern

Duration/day

Time

Eat Sleep Work Clean Exercise

0-30 min 4-6 hrs 2-3 hrs 0-20 min 30 min-1 hr

5 pm - 6 pm 12 am - 6 am 10 am - 5 pm 9 am - 3 pm 5 am - 6 am

Eat Sleep Work Clean Socialise Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs 1-2 hrs 0-1 hrs

11 am - 12 pm & 5 pm - 6 pm 11 pm - 7 am 7 am - 11 pm 8 am - 5 pm 11 am - 3 pm 4 pm - 9 pm 11 am - 12 pm & 4 pm - 6 pm

Eat Sleep Work Clean Exercise Socialise Entertainment Cook

0-30 min 6-8 hrs 3-4 hrs 0-20 min 1-2 hrs 1-2 hrs 0-1 hrs 0-1 hrs

11 am - 1 pm & 4 pm - 6 pm 12 am - 7 am 10 am - 11 pm 8 am - 1 pm & 6 pm - 9 pm 1 pm - 3 pm 2 pm - 4 pm 7 pm - 8 pm 12 pm - 1 pm & 5 pm - 6 pm

Eat Sleep Cook Read Clean Socialise Entertainment Leisure

30 min-1hr 6-8 hrs 3-4 hrs 1-2 hrs 0-20 min 1-2 hrs 0-2 hrs 0-1 hrs

4 pm - 6 pm 11 am - 3 pm & 12 am - 4 am 4 pm - 6 pm 1 pm - 10 pm 9 am - 12 pm 1 pm - 11 pm 1 pm - 11 pm 4 pm - 6 pm

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 2-3 hrs 1-2 hrs 1-2 hrs

11 am - 12 pm 11 am - 3 pm & 1 am - 5 am 8 am - 11 pm 5 pm - 11 pm 5 pm - 11 pm

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 6 pm - 9 pm 6 pm - 9 pm

Eat Sleep Socialise Exercise Research Work Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & 1 pm - 3 pm 12 pm - 11 pm 12 pm - 11 pm 6 pm - 9 pm

Eat Sleep Socialise Exercise Entertainment Work Lounge

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs 0-1 hrs

7 am, 12 pm & 4 pm - 6 pm 11 pm - 5 am 4 pm - 11 pm 10 am - 11 am 4 pm - 11 pm 9 am - 11 am & 1 pm - 3 pm 4 pm - 7 pm

Eat Sleep Socialise Exercise Entertainment Work Lounge

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & 1 pm - 3 pm 6 pm - 9 pm 12 pm - 11 pm 6 pm - 9 pm

Music events

Sporadic

Constant Age: 67 years old Occupation: Pensioner Stay: 335 days/year

Profile

Kitchen

User

Sporadic Age: 44 years old Occupation: Banker Stay: 24 days/year

User

Sporadic Age: 44 years old Occupation: Banker Stay: 24 days/year

Eat Sleep Cook Read Clean Socialise Entertainment Leisure

30 min-1hr 6-8 hrs 3-4 hrs 1-2 hrs 0-20 min 1-2 hrs 0-2 hrs 0-1 hrs

4 pm - 6 pm 11 am - 3 pm & 12 am - 4 am 4 pm - 6 pm 1 pm - 10 pm 9 am - 12 pm 1 pm - 11 pm 1 pm - 11 pm 4 pm - 6 pm

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 2-3 hrs 1-2 hrs 1-2 hrs

11 am - 12 pm 11 am - 3 pm & 1 am - 5 am 8 am - 11 pm 5 pm - 11 pm 5 pm - 11 pm

Eat Sleep Socialise Entertainment Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 6 pm - 9 pm 6 pm - 9 pm

Museums Galleries Conferences

Eat Sleep Socialise Exercise Research Work Lounge

0-30 min 4-6 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs 0-1 hrs

11 am - 12 pm 4 pm - 6 pm 8 pm - 11 pm 4 am - 6 am & 1 pm - 3 pm 12 pm - 11 pm 12 pm - 11 pm 6 pm - 9 pm

Cinemas Theatres Gyms Parks

Eat Sleep Socialise Exercise Entertainment Work Lounge

0-30 min 6-8 hrs 0-1 hrs 1-2 hrs 0-2 hrs 0-1 hrs 0-1 hrs

7 am, 12 pm & 4 pm - 6 pm 11 pm - 5 am 4 pm - 11 pm 10 am - 11 am 4 pm - 11 pm 9 am - 11 am & 1 pm - 3 pm 4 pm - 7 pm

Figure 3.1.6.2 Time-use simulation of individual

Constant

users, following a day cycle extracted from UK government Figure 3.1.6.2

Electrical Survey, 2012.

3.1 Primitive Game: Time-Use Occupancy Simulation_

69


Δx 2 +Δy 2 +Δz 2 +Δt 2

= User Intersections

Figure 3.1.6.3 Figure 3.1.6.4

Figure 3.1.6.4 Intersections between users

Figure 3.1.6.3

are identified if unique path

Cross reference of the three

simulations overlap in time and

distinct user simulation paths.

space.

70

_3.1 Primitive Game: Time-Use Occupancy Simulation

3.1 Primitive Game: Time-Use Occupancy Simulation_

71


3.2 Architectural Geometry The term Architectural Geometry is referring to a field of research which is located at the junction of applied geometry and architecture (H. Pottmann, 2007). Helmut Pottmann coined that term in his book “Architectural Geomtery” (3.2.1) In the context of our research, Architectural Geometry is used a tool to explore the following concepts: • Developable structural skeletons • Compressive structural behaviour • Developable surfaces of timber Figure 3.2.2 illustrates an application of Architectural Geometry with Site 01 as context. Its digital development is explained in the following chapter.

Figure 3.2.2: Structural skeleton of

Figure 3.2.1:

developable surfaces of timber

Cover of the book “Architectural Geometry” by H. Pottmann, 2007

72

_3.2 Architectural Geometry

Figures 3.2.1

Figures 3.2.2

for Site 01

3.2 Architectural Geometry

73


3.2.1 Seminal Projects: Form-Finding Diagram Graphic statics is a intuitive way of structural form finding. In graphic statics, the geometry and equilibrium of forces are represented by two reciprocal diagrams: form and force. The geometrical relationship between these diagrams provides the following: • Explicit control over both form and forces of a structure simultaneously. • An axially loaded structure, which is translated into, structures that are compressive or tensile only. 2D Graphic statics dates back to 1725 to the work of P. Varignon and later continued by W.J.M Rankine in 1864. (3.2.1.1 - 3.2.1.2) Both, investigated in drawing the static equilibrium through geometric constructions using polygons of forces. In the 19th century this method was further investigated and devolved to a 3D reciprocal diagram method using polyhedra packing. The research lead by Block Research Group and M. Akbarzadeh expand on the application of 3D graphic statics. (3.2.1.3)

Figure 3.2.1.1: P. Varignon “Nouvelle mechanique ou statique.”, (1725) Figure 3.2.1.3: Figure 3.2.1.2:

M. Akbarzadeh “Three-

W.J.M Rankine “A Manual of Applied Mechanics”, (1864)

74

dimensional graphic statics”, Figure 3.2.1.1

_3.2.1 Seminal Project: Form-finding Diagram

Figure 3.2.1.2

Figure 3.2.1.3

(2016)

3.2.1 Seminal Projects: Form-finding Diagram_

75


Figure 3.2.1.4

Figure 3.2.1.6

Figure 3.2.1.4:

Figure 3.2.1.6:

Faces of the Polyhedron

If the area of the face gets doubled, the force diagram

Figure 3.2.1.5:

adjust accordingly.

Force gets applied perpendicular Figure 3.2.1.7:

to the face. The amount of force

Forces travel always

is represented in the area of the face.

76

Figure 3.2.1.5

_3.2.1 Seminal Project: Form-finding Diagram

Figure 3.2.1.7

perpendicular to the faces.

3.2.1 Seminal Projects: Form-finding Diagram_

77


Figure 3.2.1.8:

Figure 3.2.1.9:

Catalogue of unitary form and

Catalogue of aggregate form

force diagrams using 3D graphic statics.

78

and force diagrams using 3D Figure 3.2.1.8

_3.2.1 Seminal Project: Form-finding Diagram

graphic statics.

3.2.1 Seminal Projects: Form-finding Diagram_

79


Figure 3.2.1.9: Catalogue of aggregate form and force diagrams using 3D graphic statics. Figure 3.2.1.10: Catalogue of aggregate from diagrams and their resultant force / structure diagram.

80

_3.2.1 Seminal Project: Form-finding Diagram

Figure 3.2.1.9

3.2.1 Seminal Projects: Form-finding Diagram_

81


Figure 3.2.1.10

82

_3.2.1 Seminal Project: Form-finding Diagram

3.2.1 Seminal Projects: Form-finding Diagram_

83


Figure 3.2.1.10

84

_3.2.1 Seminal Project: Form-finding Diagram

3.2.1 Seminal Projects: Form-finding Diagram_

85


Figure 3.2.1.10

86

_3.2.1 Seminal Project: Form-finding Diagram

3.2.1 Seminal Projects: Form-finding Diagram_

87


Figure 3.2.1.10

88

_3.2.1 Seminal Project: Form-finding Diagram

3.2.1 Seminal Projects: Form-finding Diagram_

89


3.2.2 Primitive to Architectural Geometry Transformation

As the research develops, Architectural Geometry becomes a digital generative system that responds to user activities. In order to translate the volume of the primitive layout to architectural geometry, it is necessary to construct additional polyhedra around the original volume. Figure 3.2.2.1 is illustrating each step of the transformation. Geometric catalogues are developed in order to investigate the following geometrical operations: • Subdivision of space within a single primitive to articulate spatial qualities. (3.2.2.2 - 3.2.2.4) • Subdivision at a larger scale and the geometrical repercussion to the space by changing the central arrangement of the polyhedra packing. (3.2.2.5) • Vertical transitions from floor to floor and the geometrical implications to the neighbouring polyhedra (3.2.2.6 - 3.2.2.8) The iteration of geometrical operations serve as a bespoke catalogue to articulate the Primitive Game presented in chapter 2.1 into Architectural Geometry. (3.2.2.9 - 3.2.2.12)

Figure 3.2.2.1: The primitive unit (yellow) is translated by the necessary polyhedra (blue) to the Figure 3.2.2.1

90

_3.2.2 Primitive to Architectural Geometry Transformation

architectural geometry.

3.2.2 Primitive to Architectural Geometry Transformation_

91


Figure 3.2.2.3: Catalogue of outcome after using different polyhedra to translate the same primitive unit. Figure 3.2.2.4: Showing the variety of outcome with the primitive unit (magenta) as reference. Figure 3.2.2.5: Catalogue of aggregations of primitive units. Figure 3.2.2.6: Geometrical transitions between a top and a bottom. Figure 3.2.2.2: Figure 3.2.2.7:

Single primitive unit gets

Transition polyhedra influencing

translated. Figure 3.2.2.2

92

_3.2.2 Primitive to Architectural Geometry Transformation

Figure 3.2.2.3

all further connections.

3.2.2 Primitive to Architectural Geometry Transformation_

93


Figure 3.2.2.4

94

_3.2.2 Primitive to Architectural Geometry Transformation

3.2.2 Primitive to Architectural Geometry Transformation_

95


Figure 3.2.2.5

96

_3.2.2 Primitive to Architectural Geometry Transformation

3.2.2 Primitive to Architectural Geometry Transformation_

97


Figure 3.2.2.5

98

_3.2.2 Primitive to Architectural Geometry Transformation

3.2.2 Primitive to Architectural Geometry Transformation_

99


Figure 3.2.2.6

100 _3.2.2 Primitive to Architectural Geometry Transformation

Figure 3.2.2.7

3.2.2 Primitive to Architectural Geometry Transformation_ 101


Figure 3.2.2.8: Architectural Geometry outcome after transitioning between to different types.

Figure 3.2.2.8

102 _3.2.2 Primitive to Architectural Geometry Transformation

3.2.2 Primitive to Architectural Geometry Transformation_ 103


Figure 3.2.2.9

Figure 3.2.2.11

Figure 3.2.2.11: Architectural Geometry after Figure 3.2.2.9:

translation.

Outcome of the primitive game. Figure 3.2.2.12: Figure 3.2.2.10:

Architectural Geometry with

Necessary polyhedra to fulfil the primitive game.

primitive game outcome as Figure 3.2.2.10

104 _3.2.2 Primitive to Architectural Geometry Transformation

Figure 3.2.2.12

reference.

3.2.2 Primitive to Architectural Geometry Transformation_ 105


3.2.3 Outcome Evaluation

The resulting Architectural Geometry on Site 01 is evaluated with by the following metrics: • Structural stability, due to the small footprint of the plot additional structure is necessary for cantilevering. (3.2.2.4 - 3.2.2.5). • Asymmetry to create spatial differentiation. • Hierarchy between structural member to emphasize the inherent properties of 3D Graphic Statics.

Figure 3.2.3.2

Figure 3.2.3.2: View insight the furnished proposal cut as a section. Figure 3.2.3.3: Potential spaces for private units, according to the architectural

Figure 3.2.3.1:

geometry, are left open due to

View insight the furnished proposal cut as a floor plan.

106 _3.2.3 Outcome Evaluation

Figure 3.2.3.1

Figure 3.2.3.3

the primitive layout rules.

3.2.3 Outcome Evaluation_ 107


Figure 3.2.3.4

Figures 3.2.3.5

Figure 3.2.3.4

Figure 3.2.3.5:

Branching support structure to

Truss structure variation to allow

allow cantilever.

the cantilever.

108 _3.2.3 Outcome Evaluation

3.2.3 Outcome Evaluation_ 109


4th level floor plan: work area


Roof plan with view on multilevel terraces.


South elevation


West elevation


4.3 Digital Fabrication The priorities of digital fabrication within the context of Dwell.t are: • Create a compression-only system that carries load more efficiently than a standard system of vertical and horizontal elements. • Use lightweight materials efficiently, leading to a construction process that doesn’t require high-skill or large equipment. • On-site fabrication that can be accomplished using flat-packed components and a set of simple guidelines. • Employ a structural and fabrication system that is open to addition and/or modifications as user demands vary over time. The digital fabrication aspect of the project is comprised of two areas:

• Timber bending. • 3D robotic weaving.

It is crucial that the two are spatially and structurally codependent; one cannot stand without the other.

Figure 4.3.2: 1:3 prototype. The weaving is

Figure 4.3.1: 1:3 prototype made with 2mm Birch plywood and woven with

used to strengthen the nodes

Figure 4.3.1

and as a partition strategy. Zip ties are used to hold the strips of

nylon thread using wood screws as a tensioning fastener.

126 _4.3 Digital Fabrication

Figure 4.3.2

wood together.

4.3 Digital Fabrication_ 127


4.3.1 Seminal Projects: Wood Bending and Architectural Models

Shigeru Ban Tamedia Office Building Location/year: Switzerland/2013 Material: Engineered timber Relevant logic: Wood joinery techniques and wood-only construction in a 2+ storey building.

Seminal projects include: • Charles and Ray Eames steam bent chairs and splint • Shigeru Ban Tamedia Office Building • Penda scale models • ICD/ITKE woven pavilions • DNA Charles and Ray Eames Chairs Location/year: USA/1946 Material: Birch plywood Relevant logic: Strategies of shaping sheet wood to fold in specific curvature.

Figure 4.3.1.1

128 _4.3.1 Digital Fabrication: Wood Bending and Doll House Precedents

Figure 4.3.1.2

Figure 4.3.1.3

4.3.1 Digital Fabrication: Wood Bending and Doll House Precedents_ 129


Penda Scale Models for House # Location/year: China/2014 Material: Wood Relevant logic: 2+ storey wood construction in a grid. Detailed architectural model showing glazing, mullions and occupants.

Figure 4.3.1.4

130 _4.3.1 Digital Fabrication: Wood Bending and Doll House Precedents

ICD/ITKE Woven Pavilions Location/year: Germany/2013 Material: Fibre reinforced polymer Relevant logic: Geometric flexibility and minimal form-work for robotic weaving using fibre reinforced polymers.

Figure 4.3.1.5

4.3.1 Digital Fabrication: Wood Bending and Doll House Precedents_ 131


DNA Location/year: England/2016 Material: Wood, polypropylene, metal wire Relevant logic: Strategy for constructing a compression only network and meeting members of different angles at a node using sheet material.

Figure 4.3.1.7

Figure 4.3.1.6

132 _4.3.1 Digital Fabrication: Wood Bending and Doll House Precedents

4.3.1 Digital Fabrication: Wood Bending and Doll House Precedents_ 133


4.3.2 Digital Timber and 3D Robotic Weaving Process The steps of the fabrication process can be summarized as follows: 1. Translate digital architectural geometry into fabricable geometry that is unrolled and registered. 2. Prepare tool paths and CNC wooden strips out of 1/8� Birch plywood. 3. Soak the wood for two hours, then use taut line hitch knot to bend it. 4. Use same knot to assemble all parts of the node together. 5. Allow to dry before finishing node with high-gloss lacquer and enamel. 6. Using the robot, weave the node to fulfil structural and spatial requirements. 7. Remove all excess rope.

Figure 4.3.2.2

Figure 4.3.2.3 Figure 4.3.2.2: Early model showing an attempt to connect the plywood strips using zip-ties only. Figure 4.3.2.3: Eliminating the use of zip-ties for strip-strip connections and using them only for assembly as a strategy to gradually pull opposing faces towards one another until all strips lock together using finger joints. Figure 4.3.2.1:

Figure 4.3.2.4:

Eliminating the use of zip-ties by

Early finger joints were problem-

elongating the finger joints and

atic in terms of proportion and

using them as weaving hooks.

led to heavy reliance on zip-ties,

The weaving here secures the plywood strips in place.

Figure 4.3.2.1

134 _4.3.2 Digital Fabrication: Digital Timber and 3D Robotic Weaving Process

Figure 4.3.2.4

an unscalable fabrication technique.

4.3.2 Digital Fabrication: Digital Timber and 3D Robotic Weaving Process_ 135


Figure 4.3.2.5

Figure 4.3.2.7

Figure 4.3.2.5:

Figure 4.3.2.7:

Successful techniques for

Weaving using bolts as hooks

node-node connections rely less

is unsuccessful as the thread

on zip-ties and more on material

is easily removed from the bolt

overlap.

head. The thread easily tangles and tears upon attempting

Figure 4.3.2.6:

to screw down the bolt for

In order to allow node-node

tensioning.

connections, the wood can be chamfered to fit with the neighbouring pieces like a puzzle. This

Figure 4.3.2.6

Figure 4.3.2.8

Figure 4.3.2.8: Zip-ties were successful in

was unsuccessful as there is no

tensioning the thread through

material overlap and the joint line

tightening. However, they are not

becomes significantly weak.

usable at full-scale fabrication.

136 _4.3.2 Digital Fabrication: Digital Timber and 3D Robotic Weaving Process

4.3.2 Digital Fabrication: Digital Timber and 3D Robotic Weaving Process_ 137


Figure 4.3.2.9 Figure 4.3.2.12

Figure 4.3.2.10 Figure 4.3.2.13

Figure 4.3.2.9: Manual three-dimensional weaving using wood screws and

Figure 4.3.2.12:

washers as hooks.

First attempt at robotic weaving using large wooden hooks.

Figure 4.3.2.10: Robotic weaving increases the

Figure 4.3.2.13:

speed and accuracy of weaving

Using transparent nylon thread

complex patterns in thick layers.

is not scalable and limits variety in opacity.

Figure 4.3.2.11: Figure 4.3.2.14:

Variety in colour gives opportu-

Weaving using carbon fibre set

nities for a gradient of opacities and spacial definitions.

Figure 4.3.2.11

138 _4.3.2 Digital Fabrication: Digital Timber and 3D Robotic Weaving Process

Figure 4.3.2.14

with craft glue.

4.3.2 Digital Fabrication: Digital Timber and 3D Robotic Weaving Process_ 139


Figure 4.3.2.16

Figure 4.3.2.16: Example of woven quad of nodes as a floor/wall strategy. This is problematic in that horizontal members exhibit tension in a compression-only network. Figure 4.3.2.17: 3D printed end effector used for robotic weaving. Components include a vertical plate to hold a tensioner for the thread. The spool is attached to the end Figure 4.3.2.15:

effector and the thread runs out

Full scale construction using

through a flexible rubber-and-

metal wire to weave opposing

metal spring nozzle to avoid damages upon accidental

faces together and eliminating the need for any other fasteners.

Figure 4.3.2.15

140 _4.3.2 Digital Fabrication: Digital Timber and 3D Robotic Weaving Process

Figure 4.3.2.17

collisions with weaving hooks.

4.3.2 Digital Fabrication: Digital Timber and 3D Robotic Weaving Process_ 141


4.3.3 Structural Tests Fabrication evaluative metrics for Dwell.t: • Fabrication system must resolve the meeting of members at different angles at a node • Stable strips that are perpendicular to one another. • No tension except in the weaving. • Finger joints that function to close the seam and facilitate the weaving. • All materials and methods used must be scalable and contribute to spatial articulation.

Figure 4.3.3.1

Figure 4.3.3.3: Applying force in any direction non-perpendicular to section of the structural members breaks Figure 4.3.3.1:

the node immediately. This is

Carbon fibre exhibited some

expected as it places members

flexibility but was resilient under

designed to transfer weight in

weight.

compression under tension.

Figure 4.3.3.2:

Figure 4.3.3.4:

Structural tests are employed

Stress test of a 1:1 prototype.

to help determine thickness and

The total weight placed on the

proportions of materials needed for full-scale fabrication.

prototype was 450 kg. It did not Figure 4.3.3.2

142 _4.3.3 Digital Fabrication: Metrics of Success

Figure 4.3.3.3

exhibit significant deformation.

4.3.3 Digital Fabrication: Metrics of Success_ 143


Image Captions here: Numbering of images by section. I,e: 1.1 Preface Image Captions here: Image: 1.1.1 Numbering of images by section. 1.2 Introduction

I,e:

Image: 1.2.1

1.1 Preface Image: 1.1.1 1.2 Introduction Image: 1.2.1

144 _1.1 Introduction: Thesis

1.1 Introduction: Thesis_ 145


Digital Timber and 3D Robotic Weaving Prototyping Workshop


5.1 22-Node Proposal

Autodesk BuildSpace is a research and fabrication workshop in Boston. BuildSpace served as a platform for Dwell.t to begin prototyping at full scale. Below is the proposal used to apply for a month-long residency at BuildSpace. From this proposal, the team chose to prototype one node as proof of concept. The 1:1 prototype is constituted of a series of hollow timber nodes. The unique shape of each node is derived to achieve an optimal distribution of weight and forces throughout the structural timber skeleton. Each node is composed of 9 - 12 developable timber strips that connect to each with interlocking finger joints.

7.70 m

4.35 m

Figure 5.1.2

Figure 5.1.3:

Figure 5.1.1

Geometry (more saturated

6.45 m

Bounding Box: 7.70 x 6.45 x

4.35 m

Figure 5.1.1:

Volume: 216.3 m3 4.35m Nodes: 22

colour) of the proposed

Smallest Node: 0.95 x 1.10

prototype nested within

x 2.3 m Largest Node: 2.05 x 2.15 x

the primitives. The overall dimensions of the prototype are 4x6 m.

148 _5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: 22-Node Proposal

Figure 5.1.3

2.3 m

5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: 22-Node Proposal_ 149


150

1.1 Introduction: Thesis_ 151


152 _1.1 Introduction: Thesis

1.1 Introduction: Thesis_ 153


5.2 Timber to Nylon Fabrication Process 5.2.1 Construction Manual of One Node A. Digital Process 1. 2. 3. 4. 5. 6. 7. 8.

Cube polyhedra input to Spatial Slur Grasshopper script. Spatial slur, using 3D graphic statics, outputs a 6-armed node. Bake low polygonal geometry. Loft individual strips to produce 12 strips. Assign a number to each edge of every strip. Unroll strips and obtain their outlines. Define pairs of edges (length based) and order of fingers. Add finger joints to strips with FingerOnCurve Grasshopper script. 9. Add circular openings for rope bending/assembly. 10. Prepare CNC files, 2 strips per 8x4’ 1/4” Birch plywood sheet. 11. Prepare caps to cover open ends of node. 12. CNC strips using 1/4’ drill bit for cutting and v-bit for engraving. 13. Package and ship to site.

B. Physical Process 14. Sand-down any excess chipping on the strips. 15. Fill inflatable pool and soak all strips for 2 hours. 16. Bend strips to a right angle using a Taut Line Hitch and 1/8” nylon para-cord. 17. Using the same knot and rope, assemble the bent strips together. Match edges together using numbering from digital model. Plywood must remain moist during this process. 18. Allow the node to dry and cut away excess rope. 19. In a spray chamber, finish the node with 5-8 layers of alternating Hi-Gloss enamel paint and clear, wood lacquer. 20. After the paint dries, use robotic weaving to seal seams and apply force to open ends of the node. 21. After the weaving is complete, fully remove the rope used to attach the strips together.

Figure 5.2.4

Figure 5.2.1: Cuboid primitive input Figure 5.2.4:

Figure 5.2.2: Geometry generated from face normals inside primitive.

Figure 5.2.1

Figure 5.2.2

Figure 5.2.3:

Node with lofted strips.

Figure 5.2.3 Figure 5.2.5

Figure 5.2.5: Detailed labelling on every edge

Baked low polygonal geometry

of each strip for identification

(node).

during assembly.

154 _5.2 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process

5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process_ 155


Figure 5.2.6

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O I O I O ...

I O I O I ...

O I O I O ...

I O I O I ...

O I O I O ...

I O I O I ...

O I O I O ...

Figure 5.2.10

O I O I O ...

O I O I O ...

O I O I O ...

O I O I O ...

O I O I O ...

O I O I O ...

O I O I O ...

O I O I O ...

I O I O I ...

O I O I O ...

I O I O I ...

O I O I O ...

I O I O I ...

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O I O I O ...

Figure 5.2.7

Figure 5.2.11

O I O I O ...

O I O I O ...

O I O I O ...

O I O I O ...

O I O I O ...

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O I O I O ...

O I O I O ...

Figure 5.2.10: Plywood sheet on the CNC bed. The machine cuts all holes and openings, engraves the labels

Figure 5.2.6:

and then cuts out the outline of

Outlines of the unrolled strips.

the strip.

Figure 5.2.7:

Figure 5.2.8

Figure 5.2.11:

Paired edges, each pair must

Preparing the strips for

have finger patterns that will fit

assembly by sanding away

together.

any excess chipping using a Dremmel and a wood file.

Figure 5.2.8: Strip outlines after finger

Figure 5.2.12:

patterns and construction-

The wooden strips soaking in

related openings are applied.

water for two hours prior to bending and assembly. The container is a standard inflatable

Figure 5.2.9: Strips laid out on a plywood sheet, ready for the CNC.

Figure 5.2.9

156 _5.2 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process

Figure 5.2.12

children’s pool with a double layer of plastic sheeting on it.

5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process_ 157


Figure 5.2.13 Figure 5.2.16

Figure 1.2.16: Top view of some assembled strips and some others in the process of assembly. The same knot used to bend them is employed here. In this case, the rope runs through two strips at a time. This happens to four strips, pairing them in twos that are Figure 5.2.17 Figure 1.2.13:

pulled together until they all lock into place using the fingers.

The top and the bottom sides of a Taut Line Hitch knot. On one end is the knot and on the other

Figure 1.2.17:

Figure 5.2.14

The assembled node being

is a stopper, here a simple screw.

finished using a spray gun, high

The knot behaves like a zip-tie in

gloss white enamel and high

that it can only be tightened in

gloss clear wood lacquer.

one direction, without slipping. Figure 1.2.18: Figure 1.2.14:

The finished, mounted node

One sheet of plywood bent using

being woven by an ABB robot

the Taut Line Hitch.

to seal its seams and allow the interior rope holding it together

Figure 1.2.15:

to be cut away. Weaving the

Top view of the assembly area

limbs back towards the core of

with some of the bent strips ready for assembly.

Figure 5.2.15

158 _5.2 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process

Figure 5.2.18

the node applies necessary force to stabilize it structurally.

5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process_ 159


5.3 Full Scale Prototype

Figure 5.2.20

Figure 5.2.21

Figure 5.2.20: View to the centre of the node showing the overlap of all assembly ropes. Figure 5.2.21: The ropes tie opposite (facing) strips to one another in order to pull them into place, allowing the finger joints to lock into each other. Figure 1.2.19: The finished, fully woven node.

Figure 5.2.22:

This node was structurally

The process of gradually closing

tested and withstood the weight

the gaps between the strips by

of 500 kg without significant deformation.

160 _5.2 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process

Figure 5.2.22

tightening the Taut Line Hitch knots.

5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process_ 161


Figure 5.2.23

Figure 5.2.26

Figure 5.2.24

Figure 5.2.27

Figure 5.2.23: Detail image of three strips

Figure 5.2.26:

meeting at the centre of the

Finished node mounted for

node.

weaving.

Figure 5.2.24:

Figure 5.2.27:

Engraved registration of the

Wooden mount used to angle

strips and assembly knots

the node correctly for weaving.

before painting and weaving. Figure 5.2.28: Figure 5.2.25: View of the node from the top.

Figure 5.2.25

162 _5.2 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process

Figure 5.2.28

Close up of the end effector with attached nylon spool.

5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process_ 163


Figure 5.2.29

Figure 5.2.32

Figure 5.2.30

Figure 5.2.33

Figure 5.2.32: Detail of how the weaving tapers towards the periphery of the node. Figure 5.2.33: The meeting point of three strips with interlocking finger joints. Figure 5.2.34: Figure 5.2.29:

The weaving fans out towards

Upright, woven node.

the centre of the node. In doing so, it pulls on the vertical and

Figure 5.2.30:

horizontal members towards

Woven node, tilted forward.

the middle, simulating a force applied perpendicular to the

Figure 5.2.31: Woven node, tilted backward.

Figure 5.2.31

164 _5.2 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process

Figure 5.2.34

members as would occur if the node were loaded.

5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process_ 165


Figure 5.2.36:

Figure 5.2.35: Finished and woven node, sitting at an angle in an urban setting.

Figure 5.2.35

166 _5.2 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process

Figure 5.2.36

Finished and woven node, sitting at an angle in an urban setting.

5.1 Digital Timber and 3D Robotic Weaving Prototyping Workshop: Timber to Nylon Fabrication Process_ 167


Image Captions here:

Image Captions here:

Numbering of images by section.

Numbering of images by section.

I,e:

I,e:

1.1 Preface

1.1 Preface

Image: 1.1.1

Image: 1.1.1

1.2 Introduction

1.2 Introduction

Image: 1.2.1

Image: 1.2.1

168 _1.1 Introduction: Thesis

1.1 Introduction: Thesis_ 169


170

171


References


5.1 Bibliography

Primitive Layout

Introduction

Neufert, Ernst. Neufert Architects’ Data. Wiley-Blackwell, 2012.

“About Us” . Airbnb. https://www.airbnb.co.uk/about/about-us.

Schütte-Lihotzky, Margarete. Das Neue Frankfurt, 1926.

“Cooperation for Service, Not Profit.” n.d. Amalgamated Housing Cooperative. http://www.amalgamated-bronx.coop/. Accessed 19 Apr 2017

Architectural Geometry

“International Network of Coliving Spaces.” n.d. ROAM. https://www roam.co/. Accessed 19 Apr 2017 “Membership Based Co-Living.” n.d. PodShare. http://podshare.co/. Accessed 19 Apr 2017 “Our Story”. The Collective. https://www.thecollective.co.uk/our-stor ?gclid=CKvU7ceIp9YCFUtNfgodwJkIaQ. Benita, Matofska. “What Is the Sharing Economy?” The People Who Share, September 1, 2016. http://www.thepeoplewhoshare.com/ blog/what-is-the-sharing-economy/. Breslav, Simon, Rhys Goldstein, Azam Khan, and Kasper Hornbaek. 2017. “Exploratory Sequential Data Analysis for Multi-Agent Occupancy Simulation Results.” Autodesk Research, Toronto, Canada. Accessed April 6. https://d2f99xq7vri1nk.cloudfront.net/ legacy_app_files/pdf/Breslav__Data_Analysis_Occupancy_Apr21. pdf. Mungia Tapia, Emanuel and Rockinson, Randy. “Activity Recognition in the Home Setting Using Simple and Ubiquitous Sensors.” MIT Media Lab. Accessed April 6, 2017. http://courses.media.mit. edu/2004fall/mas622j/04.projects/home/. Zimmermann, Jean-Paul, Matt Evans, Jonathan Griggs, Nicola King, Les Harding, Penelope Roberts, and Chris Evans. “Household Electricity Survey A Study of Domestic Electrical Product Usage.” Intertek Testing & Certification Ltd, May 2012.

174 _5.1 References: Bibliography

Hall, Edward T. The Hidden Dimensions, 1966.

Block P, Ochsendorf J. Thrust network analysis: a new methodology for three dimensional equilibrium. J Int Assoc Shell Spat Struct, 2007. H. Pottmann; A. Asperl; M. Hofer; A. Kilian. Architectural Geometry Bentley Institute Press, 2017. Rankine M. A manual of applied mechanics. London: R. Griffin, 1858. Rankine M. Principle of the equilibrium of polyhedral frames. Phil Mag, 1864. Varignon P. Nouvelle mécanique ou statique. Paris: Claude Jombert, 1725. Digital Fabrication DNA. Begum Aydinoglu, Federico Borello, Philipp Siedler .“DNA” Architectural Association Design Research Lab. Accessed 23 Apr 2017. ICD. ICD ITKE Research Pavilion 2013-14, 2014. https://vimeo .com/98783849. Penda. “HOUSE #.” Home Of Penda, 2014. http://www .home-of-penda.com/Home/Index/showWorkInfo?work_info_ id=b02b97a3bc5cb9d1329f1fbcce365312. Tamedia Office Building, Shigeru Ban “http://www.world-architects .com/en/projects/41967_Bueroneubau_Tamedia” . Accessed 19 Apr 2017. World-Architects, and Europaconcorsi. “Shigeru Ban Tamedia Office Building.” Hic Arquitectura, 2017. http://hicarquitectura.com/2014/04/shigeru-ban-architects-tamedia-office-building/.

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5.2 Image Credits Figure 1.1.1: Smallworks Studios. “Small Works.” Photograph, Accessed September 19, 2017. https://www.smallworks.ca/ laneway-house-design-build-vancouver/. Argo’s. The Bedroom Shop. Photograph, n.d. http://www.argos. co.uk/static/ArgosPromo3/includeName/bedroom-shop.htm. B&Q. Bathroom Suite. Photograph, Accessed September 19, 2017. http://www.diy.com/departments/bathroom/bathroom-suites/ DIY837565.cat. Ornament, Avi. Best Colours For Study Room. Photograph, Accessed September 19, 2017. https://www.youtube.com/ watch?v=QOS7lsT0OdA. JTC Furniture Group. Communal Kitchens. Photograph, Accessed September 19, 2017. http://www.jtcfurnituregroup.co.uk/products/ JTC-student-accomodation/communal-kitchens. Bath Echo. Parents across Bath Being Urged to Check Entitlement for Additional Childcare. Photograph, July 26, 2017. http://www. bathecho.co.uk/news/education/parents-across-bath-urged-checkentitlement-additional-childcare-74309/. Clark, Jaime. Small Laundry Rooms. Photograph. Accessed September 19, 2017. https://www.pinterest.co.uk/pin/ q8mnYlBM9MXo5ri3If9FWVeLA8D14VxkuHqSn2d0g/. Figure 1.1.2: “Cooperation for Service, Not Profit.” n.d. Amalgamated Housing Cooperative. http://www.amalgamated-bronx.coop/. Figure 1.1.3: Eames Office. “Leg Splint.” Eames Office, 2017. http://www. eamesoffice.com/the-work/leg-splint/. Figure 1.1.4: ICD/ITKE Research Pavilion 2016/7. (2017). University of Stuttgart. Institute for Computational Design (ICD). Institute of Building Structures and Structural Design (ITKE)

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Figure 1.1.5: Citycenter Land. Aria Sky. Photograph, 2017. https://www.aria.com/ en.html. SEO. Kensington and Chelsea - Related Images & Keyword Suggestions. Photograph. Accessed September 19, 2017. http:// keywordsuggest.org/gallery/24986.html. Figure 1.1.8: Zimmermann, Jean-Paul, Matt Evans, Jonathan Griggs, Nicola King, Les Harding, Penelope Roberts, and Chris Evans. “Household Electricity Survey A Study of Domestic Electrical Product Usage.” Intertek Testing & Certification Ltd, May 2012. Figure 1.1.9: Breslav, Simon, Rhys Goldstein, Azam Khan, and Kasper Hornbaek. 2017. “Exploratory Sequential Data Analysis for Multi-Agent Occupancy Simulation Results.” Autodesk Research, Toronto, Canada. Accessed April 6. https://d2f99xq7vri1nk.cloudfront.net/ legacy_app_files/pdf/Breslav__Data_Analysis_Occupancy_Apr21. pdf. Figure 1.1.10: Mungia Tapia, Emanuel and Rockinson, Randy. “Activity Recognitionin the Home Setting Using Simple and Ubiquitous Sensors.” MIT Media Lab. Accessed April 6, 2017. http://courses. media.mit.edu/2004fall/mas622j/04.projects/home/. Figure 1.2.2: “Cooperation for Service, Not Profit.” n.d. Amalgamated Housing Cooperative. http://www.amalgamated-bronx.coop/. Accessed 19 Apr 2017 Figure 1.2.3: “About Us” . Airbnb. https://www.airbnb.co.uk/about/about-us. Figure 1.2.4: “Our Story”. The Collective. https://www.thecollective.co.uk/our-stor ?gclid=CKvU7ceIp9YCFUtNfgodwJkIaQ. Figure 1.2.5: “Membership Based Co-Living.” n.d. PodShare. http://podshare.co/. Accessed 19 Apr 2017 Figure 1.2.6: “International Network of Coliving Spaces.” n.d. ROAM. https://www. roam.co/. Accessed 19 Apr 2017

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Figure 4.3.1.1: Eames Office. “Leg Splint.” Eames Office, 2017. http://www. eamesoffice.com/the-work/leg-splint/. Figure 4.3.1.2: didier boy de la tour. Shigeru Ban: Tamedia Office Building in Zurich Completed. Photograph, 2013. https://www.designboom. com/architecture/shigeru-ban-tamedia-office-building-in-zurichcompleted/. Figure 4.3.1.3: World-Architects, and Europaconcorsi. “Shigeru Ban Tamedia Office Building.” Hic Arquitectura, 2017. http://hicarquitectura. com/2014/04/shigeru-ban-architects-tamedia-office-building/. Figure 4.3.1.4: Penda. “HOUSE #.” Home Of Penda, 2014. http://www. home-of-penda.com/Home/Index/showWorkInfo?work_info_ id=b02b97a3bc5cb9d1329f1fbcce365312. Figure 4.3.1.5: ICD. ICD ITKE Research Pavilion 2013-14, 2014. https://vimeo. com/98783849. Figure 4.3.1.6: DNA. Begum Aydinoglu, Federico Borello, Philipp Siedler .“DNA”. Architectural Association Design Research Lab. Accessed 23 Apr 2017. Figure 4.3.1.7: DNA. Begum Aydinoglu, Federico Borello, Philipp Siedler .“DNA”. Architectural Association Design Research Lab. Accessed 23 Apr 2017.

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5.2 References: Image Credits_ 179

Dwell.t Phase 1  

Dwell.t Time-based subscription dwelling. Robotically woven, lightweight timber structure for infill sites in high density cities. Document...

Dwell.t Phase 1  

Dwell.t Time-based subscription dwelling. Robotically woven, lightweight timber structure for infill sites in high density cities. Document...

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