META-MORPH (MSc)

META-MORPH

Emergent Technologies and Design 2022-2023 Architectural Association School of Architecture MSc Dissertation Selin Ozasik (MSc), Liuxin Zhao (MSc), Tuotuo Chen (MSc)

ARCHITECTURAL ASSOCIATION SCHOOL OF ARCHITECTURE EMERGENT TECHNOLOGIES AND DESIGN 2022-2023

META-MORPH MSc Dissertation Tuotuo Chen (MSc) Selin Ozasik (MSc) Liuxin Zhao (MSc)

COURSE DIRECTOR: Dr. Elif Erdine FOUNDING DIRECTOR: Dr. Michael Weinstock STUDIO MASTER: Dr. Milad Showkatbakhsh STUDIO TUTORS: Dr. Naina Gupta | Paris Nikitidis | Felipe Oeyen |Dr. Alvaro Velasco Perez | Lorenzo Santelli | Fun Yuen

ARCHITECTURAL ASSOCIATION SCHOOL OF ARCHITECTURE GRADUATE SCHOOL PROGRAMMES PROGRAMME: EMERGENT TECHNOLOGIES AND DESIGN YEAR: 2022-2023 COURSE TITLE: MSc. Dissertation DISSERTATION TITLE: Meta-Morph STUDENT NAMES: Tuotuo Chen, Selin Ozasik, Liuxin Zhao DECLARATION: “I certify that this piece of work is entirely my/our and that my quotation or paraphrase from the published or unpublished work of other is duly acknowledged.”

SIGNATURE OF THE STUDENT:

Tuotuo Chen

DATE: 22 September 2023

Selin Ozasik

Liuxin Zhao

Acknowledgement We would like to express our sincere gratitude to all those who have supported us through our journey in the Emergent Technologies and Design program. Our heartfelt appreciation goes out to our family, friends, and colleagues for their unwavering encouragement and constant source of inspiration.

We are immensely grateful to our faculty members, whose patient guidance, constructive critiques, and unwavering encouragement have been pivotal in the development of this dissertation.

ABSTRACT ‘Meta-Morph’ aims to design a flexible and adaptable system within the retail industry for addressing problems such as the inefficient current architecture of retail, underutilization of customer needs, the evolving product life cycle, increment of vacancy rates in high streets, and constraints in revitalisation.

A participatory design system is used by embedding a Virtual Reality (VR) platform for utilising the collaboration of different stakeholders. By leveraging VR technology, stakeholders can actively participate in the design process, providing feedback and suggestions on the spatial layout. This iterative approach ensures that the architectural system meets the evolving needs and preferences of all stakeholders, resulting in a more engaging and user-centric retail environment.

Throughout the thesis, a novel retail typology emerges, transcending the traditional concept of retail as a mere shopping destination. Instead, it envisions retail spaces as cultural hubs, offering opportunities for diverse social and cultural activities.

To revitalise the high street and increase space efficiency, the project reclaims night-time usage by extending the use from daytime to a 24-hour living environment. The functions are transformed from day to night to host different events. According to the data that is collected from visitors and climatic conditions the whole architectural system is reconfigured in monthly and seasonal changes. The thesis also discusses the space definition in today’s world and provides an extension of physical space to digital.

Additionally, Meta-Morph explores the application of digital fabrication methods in the architectural realm. By utilizing advanced manufacturing techniques such as 3D printing, customizable and sustainable components can be created, allowing for greater design flexibility and efficient implementation of onsite fabrication. The combination of VR and digital fabrication methods in this research contributes to the advancement of design methodologies within the retail industry, fostering adaptive and dynamic spaces that enhance user experiences, flexibility of adaptiveness, and operational performance by providing efficiency in time and economics.

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INTRODUCTION In today’s rapidly evolving consumer landscape, the product cycle has undergone a significant transformation, closely intertwined with shifting consumer habits. With the advent of technology and the rise of e-commerce, the traditional linear product cycle has given way to a more dynamic and iterative process. Brands and businesses now focus on continuous innovation and adaptation to meet the ever-changing needs and preferences of consumers. To succeed in this landscape, businesses should not only deliver high-quality products but also engage in ongoing dialogue with consumers, leveraging data-driven insights to anticipate and cater to their evolving preferences.

Within the retail industry, recent years have witnessed the perceived decline of numerous physical stores One primary reason behind these setbacks is their failure to adapt to the ever-changing landscape of consumer preferences and shopping behaviours. Customers today value convenience, personalized experiences, and seamless integration between online and offline channels. Physical stores that have struggled to provide these elements have faced challenges in attracting and retaining customers. Ineffective store layouts, limited product selections, and outdated or uninspiring designs have also contributed to customer dissatisfaction.

Additionally, lack of innovative technologies or interactive features have driven customers towards more convenient and engaging online shopping options. To succeed in the current retail landscape, businesses should prioritize customer-centric strategies, invest in technology-driven solutions, and create memorable in-store experiences that cater to the evolving needs and expectations of today’s consumers.

The primary objective of this thesis is to address the inefficiencies inherent in contemporary retail architecture. The project seeks to establish a strong and meaningful discourse among various stakeholders, ultimately manifesting as adaptable system configurations. ‘Meta-Morph,’ aspires to conceive a modular design system, leveraging the potential of participatory design within a virtual reality (VR) framework. This system is envisioned as a dynamic solution capable of tailoring itself to evolving demands and requirements within the retail sector.

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CONTENT ABSTRACT

1

INTRODUCTION

2

01 DOMAIN

6

1.1 Context

8

1.2 Opportunity

13

1.3 Challenges

17

1.4 Strategies

21

1.5 Site Selection

28

02 METHODS

32

2.1 Modular Design

34

2.2 Robotic Fabrication

35

2.3 Participatory Design

36

2.4 Virtual Reality Interactive Design Platform

38

m

03 RESEARCH DEVELOPMENT

40

3.1 Module Research

42

3.2 Physical Experiment

58

3.3 VR Platform Formation

82

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04 DESIGN DEVELOPMENT

86

4.1 Module Optimisation

88

4.2 Robotic Fabrication Simulation

92

4.3 Module Catalogue

111

4.4 Functional Division

128

4.5 Urban Strategy

132

4.6 VR Platform Development

159

05 THE DESIGN PROPOSAL

168

5.1 Options for Platform

170

5.2 Final VR Application

178

06 EVALUATIONS/ FUTURE DEVELOPMENT

168

6.1 Conclusion

170

6.2 Future Development

178

APPENDIX

198

BIBLIOGRAPHY

206

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01

THE DOMAIN 1.1 Context 1.2 Opportunity 1.3 Challenges 1.4 Strategies 1.5 Site Selection

This chapter offers a comprehensive exploration of the evolving realm of retail architecture, providing valuable insights into its contextual landscape, existing challenges, emerging opportunities, and innovative strategies. In today’s dynamic consumer-driven world, traditional retail spaces confront a multitude of problems stemming from changing consumer behaviour and the demand for adaptable solutions. Among these challenges, the concept of flexible pop-up spaces has gained prominence as a potential solution to address the changing dynamics of retail. Within this context, Oxford Street serves as the focal point of our research area, a bustling urban district emblematic of the retail landscape’s complexities.

Moreover, this chapter introduces the pivotal concept of a participatory design system, a cornerstone of our research approach. This system seeks to elevate user involvement, granting stakeholders a more significant role in shaping the retail spaces they interact with. As a result, flexibility becomes a paramount objective, and reconfiguration parameters are meticulously explored to adapt to the ever-shifting demands of the retail ecosystem. In the following sections, we will delve deeper into each of these facets, providing a comprehensive foundation for our research exploration.

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1.1 Context MAY APRIL MARCH FEB. JAN. DEC.

Figure 1.1.1 Shops on Oxford Street in 20121

NOV. OCT. SEPT. AUG. JULY JUNE 0

500000 1000000 1500000 2000000 2022-2023

Figure 1.1.2 Shops on Oxford Street in 20221

2021-2022

Figure 1.1.3 Average footfall on Oxford St.2

Research has shown that the Oxford Street in the UK have continued to decline in recent years.1 From 2012 to 2022, a large amount of branded shops shut down or changed to sweet stores and gift shops.

Compared to the past year (2021-2022), there has been an 18% drop in footfall in front of various shops on Oxford Street in this year (2022-2023).2 It is obvious from both the longer time period (10 years) and the one-year change that this high street is in a state of decline.

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Figure 1.1.4 Oxford Street vacancy rate, 2013-20233

In the post-pandemic era, Oxford Street has seen a further increase in retail vacancy rates, reaching 15.6% in 2023.3 There are a number of reasons for this and this thesis examines the key issues and proposes strategies.

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1.1.1 Saturation Offline retail is saturated in terms of market share. During the boom years of the 1990s and the period leading up to the 2008 financial crisis, the industry maintained strong growth. However, due to competition and the rise of new shopping platforms, some of the traditional high street retailers and flagship stores are no longer viable. The loss of these big brands can have a knock-on effect on small businesses, given the increase in rents and the length of contracts for small shops tied to anchor tenants. Tom Ironside, Director of Business & Regulation at the British Retail Consortium, told MailOnline: 'The number of empty storefronts remains around 10 per cent higher than pre-pandemic levels.'4

1.1.2 Stagnation Advances in Internet technology have made online shopping more convenient for customers. And stagnation in the traditional business mode of branded stores is making them unattractive. Oxford Street statistics for the last 10 years (2013-2023)3 show that fashion and general clothing shops have seen the biggest decline in store numbers, with a net loss of six stores over the decade. Although this still tops the category rankings, it is due to the overall decline in retail outlets. The electronics and home entertainment category has seen a net loss of 4 sites on Oxford Street.

Figure 1.1.5 Oxford Street category net unit change 2013-20233

Due to the closure of mobile phone shops and the closure of HMV in 2019. The number of shops in this category has fallen from 3rd in 2013 to 6th in 2023. The banking and financial services has also seen a significant decline.

These types of retailers are the most vulnerable to the impact of online services. People are more focused on convenience and a better shopping experience. As a result, the number of small shops and restaurants has increased significantly. Branded stores, on the other hand, are increasingly being used as showrooms to try out products such as electronics, or simply to see what the products look like before making a purchase online. The good news is that this behaviour suggests there is still a need for shops. But the operating mode should be changed.

Figure 1.1.6 Oxford Street category rank changes 2013-20233

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1.1.3 Obsolescence

1.2 Opportunity

Priyanka et al (2014) well explained that all store atmospheric factors, have significant impact on customer approach behaviours. Including design factors, intangible factors, image of service personnel, visual stimulus and image of other customers. The most important factor is design. Customers pay attention to the layout and overall structure, the interior decoration, the signs and marks, the display of commodities, etc.5

The evolving retail market demands the next generation of innovative and flexible solutions. New solutions need to analyse product characteristics and consumer choices and preferences to create diverse shopping spaces. Some involve revitalising existing retail developments, reconfiguring and repurposing retail units or mixing uses to ensure vibrancy and engagement.

Retail layout has a significant impact on sales and profits. But outdated layouts destroy the shopping experience for customers. For instance:

1.2.1 Diverse experiences

Poor Store Layout: A poorly designed store layout can make it difficult for customers to navigate and find what they're looking for.

Inefficient Traffic Flow: If the flow of customer traffic is not well-managed, it can lead to bottlenecks and congestion within the store.

Inconsistent Product Placement: Inconsistent placement of products within the store can create confusion and make it challenging for customers to locate specific items. Frequent rearrangements without clear indications or logical categorization can lead to frustration and increased search times.

Ineffective Store Layout for Different Target Segments: Retail stores that fail to consider the diverse needs and preferences of their target customer segments may experience difficulties in catering to their specific requirements.

A report from Cornell University states every product goes through stages during its lifetime. Product life cycles can vary in length - weeks, or months, or years.6 Obviously, the static store layout cannot keep up with the rapidly-changing product trends and shopping needs of customers.

Oxford Street is not only a destination for people to shop. It is also a place for public gatherings in the city. As such, it exists to broaden its appeal by adding cultural events or another interactivity. Young people prefer to spend money and time on interesting experiences rather than just buying goods.7 Shopping centres can convert some of their space to leisure uses such as gyms, games shops, rock climbing, trampolines, etc. to increase attractiveness. These experiential elements are relatively convenient to build and operate (most of them are modular units). Where there is an option to repurpose existing retail assets, experiential elements can be incorporated through the organisation of events to drive awareness and brand engagement.

Selfridges has opened the doors of its Ultralounge venue on the lower ground floor of the store for three months as a new space for musical collaborations, working with artists including A$AP Rocky, Skepta and Ryoji Ikeda.8 The 325 m² space has been designed by London-based The Experience Machine (TEM) Studio, and comprises a modular structure of gauze, mirrors and lighting that can display live projections. A creative space can attract a considerable number of people to stop and watch. If such a temporary stage can be opened in the shopping hall and interact with customers, it is bound to attract more consumers.

Figure 1.1.7 Product life cycle and profits6 Figure 1.2.1 Music Matters campaign, by Selfridges8

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1.2.2 Flexible Pop-up Spaces The spatial organisation of shopping centres cannot adapt to rapidly changing shopping needs. On the one hand, in the Internet age, brands and products are updated very quickly. Shops should offer versatile forms of space organisation to accommodate different types of products. As some merchants leave and new ones move in, the internal space of the mall needs to be reconfigured according to their needs. A variable design solution with flexibility will cope well with this situation. On the other hand, the spatial organisation of some malls is not clear. People are confused while shopping and this will further reduce the attractiveness of the mall. In order to adapt to the changing needs of consumers, pop-up installations can be used in the internal spatial arrangement of large shopping centres, such as internal walls, windows, light boards, showcases, etc. They can be used to guide customers, rationalise flows, create customized spaces for different retailers, or even create temporary fitting rooms, lounges, tills, etc. to suit different periods of shopping.

Pop-up spaces can also be extended outdoors to attract customers in public places. They can be low-cost, small-scale retail brands such as food and fashion shops, set up in locations close to the closed shops to enhance the vibrancy of the location and create the opportunity for the shops to reopen.

Figure 1.2.3 Boxpark Shoreditch10

Figure 1.2.2 Pop-up shop cases9

"This format is perfect for Exploring and Dreaming shopper missions. These are the customers who enjoy interaction, learning, human connection and services. Pop-ups can facilitate these missions in a creative but socially distant way too – thanks to flexibility in modularity, location and leveraging various features or technologies."9 14 | META-MORPH

A key example of this approach is the Boxpark pop-up mall built from converted shipping containers (such as those in Shoreditch and Croydon, London). These food and retail parks are relatively cheap to build, operate on a smaller scale, have lower initial costs and bring retail brands closer together in active 24/7 locations.10 As Boxpark is a modular building consists of a combination of shipping containers, it costs around £1,100 to order such a container. After refurbishment a container can last up to 25 years, which significantly reduces the cost of construction. The cost of renting a container for a shop is £20,000 per year, more than a market stall, but less than bricks and mortar premises.11 The units that make up the parks adapt to changing consumer habits: pods often act as showrooms to support a brand's existing online presence or become workshops, allowing start-ups to physically display their products in a cost-effective way to increase potential online purchases, or they allow small businesses to experiment with high street retailing, giving them the confidence to become large corporate tenants in the future.

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1.2.3 Mixed Use A logical solution for a struggling shop is to change its function. For example, use part of the space for temporary leases to a number of low-cost tenants. Or offer the retail space as office space to flexible workers, freelancers, small businesses or start-ups to create a new revenue stream. The rise of freelance and independent work, and the growing market for dedicated co-working space , suggests this is a source of potential future demand. One example is wework, which is a platform allowing users to book co-working space or a private office by the day and meeting rooms by the hour. In this case, people can utilise the space instead of discarding it.12

1.3 Challenge

Although a number of ideas for renovation or reconstruction have been put forward, there are some challenges to the realisation of these plans. These challenges mainly relate to economic and environmental costs.

1.3.1 Economic costs Renovating the interiors of existing commercial buildings to meet diverse shopping needs is a better option. However, millions of dollars in construction costs are a major challenge for developers, tenants and businesses.

Interior decoration costs are a significant part of a commercial building project. This includes the cost of materials, equipment and payments to designers and builders. In the UK, the cost of fitting out a low specification shop is between £50 and £70 per square foot, while a medium specification shop will cost between £80 and £100 per square foot.13 A high specification shop will cost around £145 per square foot. If labour is used, an additional hourly rate will need to be paid. If a shop or shopping centre is to be refurbished, investors will also need to calculate the cost of removing old equipment.

Figure 1.2.4 Wework solutions12

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Figure 1.3.1 Mall construction cost break down in percentages13

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For large shopping centres:

1.3.2 Environmental costs

However, such a renovated shop would not be able to provide the diversified spaces mentioned above, because once built, people would sell and browse their products in fixed space divisions. Fixed spaces also do not allow for the introduction of new attractive features such as music stages, interactive games and so on. If brands and products change regularly, the mall space can't be adapted to showcase products, guide customers and provide a better shopping experience. If merchants want to make changes, they have to pay again for renovations to get a new interior design. But the financial cost prevents them from making timely changes.

Statistics show that non-structural building materials make up a significant proportion of the interior of commercial buildings.15 When a shopping centre is refurbished, most of these materials become construction waste, which is not renewable. These building materials include plaster, tiles, finishes, wood, glass, etc. The production and transportation of these building materials causes a mass of carbon emissions and other environmental pollution. And the interiors of shopping centres built with these materials do not meet the objective of flexibility. When space requirements change and rebuilding is required, the interior walls, windows, doors, fixtures, etc. made of these materials have to be demolished, which is a huge waste, and rebuilding them incurs environmental costs.

For smaller shops: Reviving a closed shop is not easy for a sole trader, and they will be reluctant to invest until they are confident of making a profit. If the entrepreneur taking over the closed shop is running a completely different business, for example from a clothes shop to a catering outlet, they may need to completely abandon the old facilities and redecorate. The financial cost of this is a disincentive for investors and as a result the vacancy rate of shops continues to rise.

For example, a large shopping centre of 1,000,000 square feet has 2,200 tonnes of non-structural materials, or 39% of the total interior contents. A small shopping centre of 250,000 square feet has 540 tonnes of nonstructural building materials.15 The waste of these materials, as well as the energy consumption and carbon emissions during manufacture and transport, is a sustainability challenge.

Figure 1.3.3 Material category in a large shopping mall 15

Figure 1.3.4 Material category in a small shopping mall 15

Figure 1.3.2 Average shop renovation cost in the UK, 202314

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1.4 Strategies 1.4.1 Participatory Design in Public Space Participatory design, also known as co-design or collaborative design is a design methodology which involves different stakeholders throughout the design process.16 The boundaries between the designer and the user does not exists any longer that they have equal power to transform the space.

Large Shopping Mall15 Estimate based on: 1000000 Square Feet, 56 Stores/anchors, 22 Apparel, 3 Furniture, 3 Electronics, 5 Services/ specialty stores, 5 Books/toys, 2 Jewelry, 2 Restaurants, 2 Fast food/food court

Figure 1.3.5 Material category in a large shopping mall 15

According to Velden et.al. participatory design the fundamental part the participatory design is making contribution for democratising the design process. Because of its dedication to the democratic and community creation of a better future, it is a value-centred design method.17 This method is going to help to democratize the retail industry by a bottom-up approach.

In the VR application that is going to be provided in the project is going to help democratising the design decision in the reconfiguration of the units. According to the feedback that is collected from the users, the number of options is going to be provided and the selection is going to be made by a voting process.

The stakeholders that are going to be participated in this process is; users, entrepreneurs, performance artists and city hall. In the voting system, stakeholders are assigned varying weights that correspond to distinct temporal considerations, including summertime, wintertime, day, and night. These weightings are meticulously determined based on the specific functional requirements of the system.

Small Shopping Mall15 Estimate based on: 250000 Square Feet, 56 Stores/anchors, 22 Apparel, 3 Furniture, 3 Electronics, 5 Services/ specialty stores, 5 Books/toys, 2 Jewelry, 2 Restaurants, 2 Fast food/food court

Figure 1.3.6 Material category in a small shopping mall 15

Figure 1.4.1 Space occupation priority & weighting of user decision

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1.4.2 Adaptability

1.4.3 Reconfiguration

The system that is designed is going to provide adaptability in different parameters as visitor count, functional flexibility and climatic adaptation. According to Cameron (2019), the success of public spaces depends on its ability to change and withstanding against pressures.18 Schneider strengthens this argument by stating “The long-term stability of public space as a system depends on the adaptability of its structure and on the ability to change its uses, its unspecific multi-functionality”19 To apply flexibility in the architectural system, reconfiguration parameters are set that is discussed in the following section.

Parameters of Reconfiguration: Reconfiguration of the modules are divided into three parts as major events in London, day to night transformation and seasonal transformation. Reconfiguration of the modules comes with its own constrains such as time limitation for fabricating required components, economic cost of fabricating each module and movement of modules for reconfiguration. This constrains are discussed detailly in the design development section.

Major Events in London Major events in London have a significant impact on the visitor count and the retail industry. These events, include cultural festivals, sports tournaments, royal celebrations, and other large gatherings draw massive crowds of both domestic and international visitors to the city. According to Kyte, Oxford Street, one of the world’s premier shopping streets, is considered as a tourist attraction in its own right with a quarter of all visitors coming from overseas.19 During major events, the retail industry experiences increased foot traffic as event attendees explore the city and take advantage of their visit to shop. The sudden surge in visitors lead to overcrowding in stores, making it challenging for retailers to maintain efficient customer service.

Since the impact of major events on the retail industry is temporary, with an increment in visitor count during the event period, followed by a decline once the event concludes. Retailers need to carefully plan their strategies accordingly. The new retail typology that is developed in Meta-Morph provides flexibility to retailers for answering the need of change. The major events in London are mapped (fig.13) with the number of visitors and its impact to the retail sector. According to this data, the number of the modular units can be increased for expansion or decreased for the shrinkage by the number of visitors.

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Figure 1.4.2 Major events in London

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Day to Night Transformation (24-hour city)

Seasonal Transformation

The new retail typology is also envisioning a 24-hour city by reclaiming the night and transforming retail shops and restaurants into concert areas and theatres at night on Oxford Street. This presents an opportunity to revitalize the iconic shopping district and establish it as a thriving 24-hour living city. According to the study about exploration of space efficiency that made by Z. Ma, space efficiency can be calculated by dividing into three sections as; floor area, number of potential and actual users and the amount of the time that the space is used.20 By repurposing retail spaces and cafes after regular business hours, Oxford Street can become a dynamic cultural hub that caters to both locals and tourists throughout the night and the space use can be optimised in time. This transformation would create a vibrant nightlife scene, enhancing the city's appeal and promoting a sense of community and engagement. To achieve this vision, the modular design is going to be adapted to night time events to host performances and boost the area's night time vibrancy. Since, it is going to be designed as a cultural hub, in collaboration with local artists, musicians, and theatre groups, a diverse range of events and performances could be curated, catering to various tastes and preferences. Concerts featuring up-and-coming artists, theatrical productions, live comedy shows, and art exhibitions could be part of the vibrant night time line-up.

The thesis involves the dynamic adaptation of module components and their reconfiguration in response to seasonal fluctuations. In the broader scheme of global aggregation, a versatile courtyard layout emerges, designed to accommodate diverse events. To address sun exposure and provide shade, certain components are repurposed as canopies. For optimal ventilation and airflow during warm seasons, a more porous configuration is devised.

Conversely, in the winter months, a shift towards increased enclosure is essential. Additional partition components are introduced to enhance insulation and create cozy, enclosed spaces. The introduction of overhead coverings in intermediate spaces further ensures the practical utilization of semi-open areas during the colder winter period. This thesis explores the fluid and adaptable nature of architectural elements, tailoring them to the evolving demands of the seasons.

Figure 1.4.3 Space efficiency mapping

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1.4.4 Transportation of modules

1.4.5 Option Development for VR Platform

The new retail space system can be adapted into different high streets that the modules can be transported when needed according to the visitor count. This opportunity is going to provide flexibility by making adaptation easier to different high streets and locations. Retailers can quickly set up or move their stores to take advantage of changing market trends or seasonal variations in foot traffic. Comparing to the traditional retail system, transportable modules are cost efficient that retailer can open pop-up stores and avoid the long-term commitments and costs associated with fixed-location leases. They can set up temporary shops during peak times and minimize expenses during slower periods. By transporting the modules into different high streets, brands can do experimentation in the market to find their target audience and they can move their brand to a different location with higher foot traffic and demand for their products or services. Also, when we look at it in city scale, transportable and flexible modular system could encourage fast evolving urban planning and development.

Initial data according to the reconfiguration parameters (major events, day to night transformation, seasonal changes). According to this data, primitive design requirements are going to be formed as; unit count, component count, vertical & horizontal expansion/shrinkage. After this, the set of constrains are going to be added to the system.

These constrains are going to be formed by physical, economic and time-wise limitations.

-Economic limitations: amount of material that can be provided, fabricated unit count and size according to the available material -Physical limitations: horizontal arrangement of the units according to the footprint of the site, vertical arrangement of the units according to the structural abilities.

-Timewise limitations: the number of components/units can be fabricated in the required time.

The options are going to be developed according to these constrains and they are going to be put in the VR platform. Different stakeholders are going to be evaluate these options and make their own selection.

Figure 1.4.4 Option development flow

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1.5 Site Selection

Oxford Street is the Europe’s most popular and busiest shopping area. It is in the first place in daily footfall with 72,700 visitors in Europe top 20 capital cities prime high streets list.21 Gavin Redrupp states that during the worst of the pandemic, the retail industry was the worst damaged; nonetheless, despite these difficulties, Oxford Street and Regent Street continue to be must-visit locations. As a result, they both continue to draw great brands thanks to a tempting offer, which in turn draws substantial traffic. According to Patrick Delcol , brick-and-mortar stores are still popular, city centres are demonstrating their attraction to shoppers, and certain innovative retail models and formats are being effectively implemented in inner cities.

On the other hand, according the data from MyTraffic’s European high street ranking , Oxford Street is still struggling to its pre-pandemic situation. Despite averaging 1.24 million visitors per month in 2021, this number is still 59% below its pre-pandemic level. When we compare Oxford Street to other top European high streets, The Rue Neuve in Brussels is the only street that performs worse.

Figure 1.5.1 Annual footfall on busiest high streets in Europe21

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Because Oxford Street is in decline today, the project aims to revitalise the high street and seeks to address this challenge by introducing a new and innovative retail typology. By focusing on creating a dynamic and multidimensional retail space, the thesis aims experiment design solutions for attracting both locals and tourists.

The new typology would integrate VR technologies for immersive shopping experiences and transforming Oxford High Street into a hub of retail and cultural events. Emphasizing inclusivity, the design would cater to diverse demographics and offer spaces for community events, cultural gatherings, and local initiatives.

The thesis also envisions collaborations with start-up companies fostering a symbiotic relationship between startup and corporate brands.

In Oxford high street a lot of flagship stores including Marks & Spencer, John Lewis, House of Fraser and Topshop is seeking for transformation. Each of them is planning to shrink the retail space up to 55% and transform the remaining space for using in different functions. Marks & Spencer is currently facing a potential demolition as Debenhams. The flagship of Debenhams building is demolished in 2022 for refurbishment and designing a new retail typology on a site where Debenhams once stood presents an opportunity to revitalize the area and reimagine the future of retail. By embracing innovation, flexibility, and a strong connection to the local community, the new retail space can become a hub for hosting different events.

Figure 1.5.2 Oxford Street retail transformation mapping

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Figure 1.0 Research flow of Meta-Morph

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02

METHODS 2.1 Modular Design 2.2 Robotic Fabrication 2.3 Participatory Design 2.4 Virtual Reality Interactive Design Platform

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This chapter outlines the methodologies employed in this thesis to investigate and address the challenges and objectives of enhancing the adaptability and flexibility of retail spaces. The methodologies are structured into four main sections as modular design, robotic fabrication, participatory design and VR platform. These methodologies collectively form the framework for the subsequent phases of the research, culminating in the development of innovative solutions for retail space design and adaptation.

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2.1 Modular Design

Figure 2.1.1 Modular system

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2.2 Robotic Fabrication

To address the challenges identified, including the lack of flexibility and adaptability in retail spaces, the failure to effectively respond to evolving brand trends, and the high costs associated with renovations, a modular design approach is adopted as the core methodology. Through the strategic design and integration of modular building components, we aim to create spaces capable of swift and cost-effective reconfigurations.

This modularity allows for dynamic adjustments in response to shifting brand trends. Through the modular building system, this thesis endeavours to provide a solution that empowers retail spaces respond to evolving brand trends and consumer preferences while minimizing the economic costs.

The development of modular architecture serve as the guiding framework for this approach. Modular architecture is instrumental in laying out the requisite guidelines and specifications for the modularization of systems. It encompasses the systematization of technologies, practices, and methodologies, thus facilitating the utilization of standardized modules in the creation of diverse products for various applications. This methodology significantly reduces design complexity, promoting cost innovation, accelerating development cycles, and fostering greater agility in addressing the dynamic needs of the contemporary retail landscape. Through the integration of modular architecture principles, this research seeks to usher in a transformative era of adaptable, cost-effective, and responsive retail design.

Figure 2.2.1 Robotic fabrication

A series of robotic fabrication simulation experiments were conducted during the research in order to verify the feasibility of the decided fabrication strategy.

By using industrial robotic arm of KUKA KR-30 and tool of pellet extruder in robotic laboratory of AA DPL(digital prototype lab), we were able to not only fabricate the design exploration, but also to simulate and analyse the robotic print path designed for the research.

Robotic tool path design involves using parameter design software and robots to plan and optimize the movement of tools in the robotic manufacturing process. By employing advanced algorithms, the robots follow precise paths, maximizing efficiency and accuracy in tasks like cutting, assembling, or 3D printing, resulting in enhanced productivity.

In this project, the Grasshopper plug-ins, such as “KUKA PRC” and “Robots” and other visual programming methods were used to experiment in order to generate the optimal robotic manufacturing tool path for the robotic 3d printing experiment.

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Case Study24

2.3 Participatory Design

A traditional architectural project is decided by professionals such as designers and engineers in a top-down process. And non-professional people, who are the users of the building, have very little opportunity to express their views on the design. It is impossible for any users to design a building with using sophisticated design software such as Rhino or Revit, and even to read the drawings and analyses of an architectural project requires a degree of professional training. Popular participation in architectural and urban design projects is not new and has been discussed since the 1970s. However, little progress has been made in terms of methodology and presentation, as most applied design processes still follow the hegemony of intellectual thinking.22 This project, on the other hand, aims to create a simple, truly bottom-up design model that involves the average user, thus increasing the adaptability of architectural solutions. The flexibility of the modular system and the participation of the VR platform provide opportunities for this mode.

La Borda housing cooperative is a development self-organized by its users to access decent, non-speculative housing that places its use value in the center, through a collective structure. This is a unique form of social housing that required a dynamic form of participatory design process when the architects, Lacol, were invited to design the scheme.

Through continuous consultation, workshops, and debates with the cooperative, the architects developed a wooden high-rise scheme consisting of 28 housing units of different sizes, as well as 280m² of community space insisted upon by the members. These communal areas were planned for domestic and everyday use, including housing play spaces, bike parks, washing facilities, and rental shops. These spaces bring people together and complement the rest of the neighbourhood.

Self-promotion and subsequent collective management implies that the participation of future users in the process (design, construction and use) is the most important and differential variable of the project, generating an opportunity to meet and project with them and their specific needs. During the design, the participation was articulated through the architecture commission, which was the link between the technical team and the general assembly, and the one in charge of preparing the architectural workshops. We have conducted an imaginary workshop, program, project strategies, environmental strategies, typology, and sessions for the validation of the preliminary project.

Custom modules Figure 2.3.1 Participatory design23

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Building section Figure 2.3.2 La Borda diagrams24

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2.4 Virtual Reality Interactive Design Platform

Virtual Reality (VR) technology offers functionality and user experience beyond traditional 3D presentations.

Instead of receiving information from a flat screen or page, using a VR application allows one to be directly immersed in the 3D world. It provides the user a more vivid and immersive experience.

In addition, the VR platform is more than just a showcase for a completed architectural design project, it is an application with interactive features. Similar to Minecraft or other construction video games, users can directly participate in the design of the project. However, they do not need to understand everything about architectural design or how to use specialised software, as the platform provides them with optimised options from a modular system. In this way, the platform offers people the opportunity to participate in the customisation of the design, simplifying the design process and giving every user of this architectural project an equal right to express their demands. And for the design project as a whole, such an approach will increase the level of participation in the design and improve the adaptability of the building through the collection of user opinions.

Case Study SENTIO VR is a virtual reality design plugin based on the Meta Quest device that can be applied to Revit, SketchUp and other design software. Models edited in the design software can be uploaded to the VR device for viewing by designers or stakeholders. At the same time, users can check real-time building information based on BIM data, such as dimensions, annotations, etc., and generate diagram or reports. The plug-in also addresses the need for team collaboration, allowing users to view or edit projects from multiple devices in different locations at different times, facilitating remote working.26 The idea from SENTIO VR for this project is the multi-platform data synchronisation and interactive VR editing capabilities. However, such software is even more complex for a construction platform that serves the majority of general non-professional users, as it is primarily intended to be used by designers and professional construction practitioners for the main purpose of project presentation. When users use such an application, they can only view the results of a particular building and cannot make subjective changes.

Therefore, a simplified platform thaat is more playful and engaging, combined with a modular customisation system, is a better choice for this project.

Multi-User Collaboration

Conceptual & photorealistic walkthroughs Figure 2.4.2 SENTIO VR examples26

Figure 2.4.1 Virtual reality in architecture25 38 | META-MORPH

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03

RESEARCH DEVELOPMENT 3.1 Module Research 3.2 Physical Experiment 3.3 VR Platform Formation

This chapter is divided into three sections as module development, fabrication experiment and platform formation. The research in this project requires the integration of several tools of design, analysis, and experiment at different phases and scales. This chapter illustrates in detail the methodologies and technologies used for research development, design exploration, and experiment process.

The methods introduced in this chapter are defined in two categories: digital tool and physical technology. Digital tools were mainly used to generate and further analyse the design scheme and physical technologies were implemented in simulation and experiment in order to verify and refine the determined fabrication strategies. But at some stages, digital tools and physical technologies were integrated to better produce strategies for physical experiments and evaluate the results of experiments. Also, the platform formation section discusses the intersection of participatory design and modular building system to build an adaptable system, a digital extension of physical space.

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3.1 Module Research

5m

7m

Figure 3.1.1 Module development process

According to the previous research, a set of parameters are set to develop the morphology. There are three main aims that need to be reached as; inhabiting different functions as retail, food and event space. Second aim is to create different axis of connections to increase the level of configurational variation. Third aim is to create more tessellation for removable panels that are going to be changed according to the seasonal and functional changes.

For reaching the first aim, second step is applied to design an embedded wall system which is going to inhabit requirements of different functions. For the second aim, step 3 and 4 is applied to create different axis and increase the possibility of different connections. Step 5,6 and 7 is applied to reach the third aim which is to create a removable panelling and structure system to adapt different functional and seasonal requirements.

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3.1.1 Division of Structure

Initial Module

Removable base & roof for expanding floor area or ceiling height

Removable panelling for replacing according to the functional differentiation

Division of module in 8 different part for expansion in different axis

Figure 3.1.2 Division of structure

The module offers the capacity for connections in four distinct axes: along the X, Y, Z, and Diagonal directions. These versatile connections serve to generate diverse spatial configurations tailored to accommodate a wide range of spatial requirements.

3.1.2 Connection Axis

Expansion in X-axis

The module is intentionally designed with the flexibility to be divided into distinct sections. Initially, it can be separated into a base and a roof, both of which can be replaced with various surfaces to either expand the available floor space or adjust the ceiling height.

Furthermore, the panels are designed to be removable, allowing for adaptation to various seasonal changes. Lastly, the module can be further subdivided into eight distinct parts, each accommodating potential expansion in different axes through the addition of specific components.

Expansion in Y-axis

Expansion in Z-axis

Expansion Diagonally

Once the module has been developed in alignment with the predefined objectives, the research progresses to the optimization phase. To enhance the adaptability and performance of the module in response to the identified challenges, a multi-objective evolutionary algorithm is employed which will be explained in the following section.

Figure 3.1.3 Four connection axis

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3.1.3 Module Morphology Optimisation

Based on the study of the development and division of the morphology of the modules, a multi-objective evolutionary algorithm is introduced to further optimise the morphology of the modules to better cope with the addressed challenges.

: FITNESS CRITIRION 1

FITNESS CRITIRION 2

Maximize Space for Users

Maximize Ratio of Users’ Space and Module Volumne

FITNESS CRITIRION 3

FITNESS CRITIRION 4

Minimize Structure Material

Minimize Displacement of finite element analysis

Figure 3.1.4 Primitive of the modular morphology

Optimisation Set-up The primitive of the module was divided into 8 isomorphic components.

The whole module can be composed of horizontal and vertical mirrors of these components.

Considering the complexity of this component, the primitive of the component was simplified into a body-plan consisting of points and lines. Each point and line has very flexible movement and rotation intervals, which constitutes a large dataset in this evolutionary algorithm to provide a large pool of alternatives.

The optimisation objective of the modular morphology is transformed into four conflicting fitness criteria.

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Figure 3.1.5 Body Plan for evolutionary algorithm

Figure 3.1.6 Fitness criteria of evolutionary algorithm

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FITNESS CRITIRION 1 Maximize Space for Users

FITNESS CRITIRION 2 Maximize Ratio of Users’ Space and Module Volume

FITNESS CRITIRION 3 Minimize Structure Material

FITNESS CRITIRION 4 Minimize Displacement of finite element analysis

Figure 3.1.8 Standard deviation graphs Figure 3.1.7 Pareto front solutions

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Standard deviation graphs of the algorithm results show different levels of optimisation for each of the four established objectives.

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Figure 3.1.9 Diamond chart

Figure 3.1.10 The best performing individuals

Individual Selection

Generation : 82 FITNESS CRITIRION 1

Individual : 42

Maximize Space for Users

The results of different solutions including average of fitness, relative difference between fitness and pareto front were observed and analysed.

Eventually the best solution in the average of fitness was chosen as the basic morphology of the module to be developed in the further step of the construction of the architectural scale.

FITNESS CRITIRION 2 Maximize Ratio of Users’ Space and Module Volumne

Unit: Millimetres

Above Figure 3.1.11 Morphology of best average solution

FITNESS CRITIRION 3 Minimize Structure Material

FITNESS CRITIRION 4 Minimize Displacement of finite element analysis Below Figure 3.1.12 Diamond chart of selected individual

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3.1.4 Refining Morphology Selected Individual An optimisation of the original morphology was conducted, focusing on the rationalisation of the structure and construction of the module.

The entire modular system was rationalised into a structural system of 300 X 250mm and an outer skin system of 30mm thickness.

Above Figure 3.1.13 Morphology of best average solution

Refined Morphology

STRUCTURAL SYSTEM

OUTER PANEL

Dimension : 50 x 50mm

Thickness : 0mm

STRUCTURAL SYSTEM

OUTER PANEL

Dimension : 300 x 250mm

Thickness : 30mm

Below Figure 3.1.14 Refined morphology

Right Above Figure 3.1.15 Original morphology a. Structure system; b. Panel Right Below Figure 3.1.16 Refined morphology a. Structure system; b. Panel

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Division Strategy

Structure System

Figure 3.1.17 First level division

Figure 3.1.18 Exploded diagram of structural system

The modular design allows this modular building unit to be divided more simply. The first level of division takes its constructive principle and divides the entire module into a total of 14 pieces of 3 specifications.

Outer Panels

The construction of the entire module can be simplified to the robotic fabrication of three specification components and subsequent robotic assembly.

Specification 01 Above Figure 3.1.19 Exploded diagram of panel system

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Figure 3.1.20 Exploded diagram of Module

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3.1.5 Second Level Division Division Strategy

Explosion Diagram

Component Dimension

Above Figure 3.1.22 Best average solution

2225

Above Figure 3.1.21 Most complex component

Outer Panel

Structural System Below Figure 3.1.23 Structural system

33

92

82

27

Unit: Millimetres

The most complex of the three specifications of the components was chosen as a sample for the research of robotic fabrication and physical experimentation.

With the secondary division of the panel system at the turnaround end, each panel can be easily assembled to the structural system after fabrication, using the normal vector as the robotic arm tool path.

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Left Figure 3.1.24 Connection of the component

Right Figure 3.1.25 Dimension of the component

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3.2 Physical Experiment

Based on the studies related to the construction of the most complex of the three specification components, two physical experiments on the structural system of this component were conducted in order to draw conclusions on the location of the divisions and connections of the structural system.

The first experiment focused on the way of dividing the structural system. Physical load-bearing experiments were carried out on different joints in linear and angular connections to compare which connection has a better load-bearing behaviour. The results lead to a decision on the division position of the structural system.

The next step in this experiment was to compare the different joint patterns in order to select the type with the best load-bearing behaviour, based on the conclusion that straight joints have better performance.

The second physics experiment builds on the first experiment by exploring the limits of robotic 3d printing technology on non-planar print paths.

Experiment 01 Joinery System Load Test

Experiment 02 Max Bending Angle

Left Figure 3.2.1 Joint of the structural system Right Figure 3.2.2 Detail of the structure

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L = 1 1/4

3/8

3/8

1/2

3.2.1 Joinery System

L=1

L = 1 1/4

3/8

3/8

Linear Joint L=1

1/4 1/2

AIM The structural system of the components has to be further divided due to their excessive dimensions and complex morphology.

The aim of this experiment was to select whether the main part of the member should be divided at a turn or not, by comparing the results of load-bearing tests of linear and angular joints.

1/2

Below Figure 3.2.4 Joint pattern of Type A & B

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L=1

3/8

1/2

L=1

3/8

Max Load : 92N

1/4

1/4

Type B

1/2 L=1

3/8

1/2

Figure 3.2.6 Joint pattern of Type B Left. Linear joint; Right. Angular joint

3/8

Type A

Max Load : 75N

L=1

1/4

L=1

1/4

3/8 3/8

L=1

3/8

Max Load : 126N 1/4

3/8

TypeLB= 1

1/4

L=1

1/4

Max Load : 81N 3/8 3/8

L=1

1/4

3/8

Type A - Primitive3/4 L = 20mm L=1 L = 1 1/4 1/2

Two joint patterns were tested for each way of joint to avoid erroneous conclusions due to experimental errors.

Above Figure 3.2.3 Indication of the experimental position

Figure 3.2.5 Joint pattern of Type A Left. Linear joint; Right. Angular joint

1/2

METHOD The experiment was carried out by 3D printing models with different connections using the same parameters, and then recording the process of pulling the model down with a measuring device using a high-speed camera. The maximum reading recorded by the measuring device will represent the maximum load for this joint.

3/8

Angular Joint

1/4

Type A

L = 1 1/4

L=1

1/4

Type A

3/8 5/8

L=1

1/4

L = 1 1/4

1/2

3/8

1/16

1/2 1/2

Type B 1/4

3/8

3/8

L=1

1/4

3/8

Figure 3.2.8 3D printed Type B Joint Left. Linear joint; Right. Angular joint

Type B

L=1

1/4

3/8

L=1

1/4

3/8

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1/4 L = 1 1/4

Type A

1/4

Figure 3.2.7 3D printed Type A Joint Left. Linear joint; Right. Angular joint

1/2 1/2

TypeLB= -1Primitive 1/4

L = 20mm L=1

1/4

CONCLUSION

SELECTED CONNECTING WAY

The results of the four experiments with the 2 types of joints showed that the linear joints generally had better load-bearing performance compared to the angular joints. Therefore, the linear connection was chosen as the connection method for this structural section. As a result, this structural section was chosen to be divided at a non-turning edge.

This division results in three parts that make up the structural element. The middle section has a more complex turned form.

The next experiment will explore the possibility of 3d printing this part.

Figure 3.2.9 Process of load-bearing test experiment

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Division 01 Linear Joint

Division 02 Angular Joint

Figure Figure 3.2.10 Division of linear joint

Figure Figure 3.2.11 Division of angular joint

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1/2 L=1

3/8

LOAD TEST OF LINEAR JOINT

3/4 L=1

Max Load: 159N 1/4

A - 1 - D1

Experiments with more linearly joined alternatives based on the prototypes of Type A and B were implemented.27 The result of the experiment was that B-1-D3 had the best load-bearing performance which was chosen as the final joint.

Middle Figure 3.2.13 Joint pattern of Type A Right Figure 3.2.14 3D printed Type A Joint

A - 1 - D2

Max Load: 164N

1/2

Max Load: 29N

1/2

3/8

Max Load: 340N

1/2

L = 1 1/4

3/8

A-2-E L=1

B - 1 - D3

B-2 1/4

L=1

1/4

1/2 1/2

1/16

Max Load: 212N 1/4

1/2 1/2

1/16

Max Load: 532N 1/4

Max Load: 545N

1/2 1/2

1/16

1/4

Max Load: 303N

1/8

1/4

1/2 1/2

B-3 1/2

1/16

1/2 1/2

Max Load: 16N

1/2

1/2

Max Load: 135N 1/2

Max Load: 25N

3/4

1/2

B - 1 - D2

L=1

1/2

3/8

A-3 L=1

Max Load: 38N

1/2

3/8

B - 1 - D1

L = 1 1/4 1/8

1/2

L=1

1/4

1/4 L = 1 1/4

1/4

A-2

L=1

Max Load: 219N

L = 1 1/4 1/4

3/8

L = 1 1/4

A - 1 - D3

B-1

3/8

L = 1 1/4

5/8 1/2

A-1 L=1

1/2

Type B Variations

Type A Variations

Left Figure 3.2.12 Indication of the experimental position

1/2

1/2 1/2

Left Figure 3.2.15 Joint pattern of Type B

5/8 1/2

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Right Figure 3.2.16 3D printed Type B Joint

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1/4

1/4

3.2.2 Structural Detail

EXPERIMENT 2 Building on the conclusion of Experiment 1, Experiment 2 focuses on the details of the turning part of the structural element. A series of 3D printing simulation experiments based on 1:2 scale models were conducted in order to verify their constructibility.

NON-PLANAR PRINT PATH Traditional 3D printing solutions with planar print paths have many limitations and constraints, such as the appearance of lamination at the top of the object, limited overhangs, the need for supports, and more wasted material.

0

30 °

Strucutre Detail

24

Therefore, novel 3D printing solutions with nonplanar print paths have been introduced. This is a solution that distributes its print path in such a way that it follows the shape of the object, aiming at reducing material usage, increasing overhang angles and eliminating laminations, among others.28

Below Figure 3.2.18 Dimensions of experimental geometry

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240

Above Figure 3.2.17 Indication of the experimental position

Proportion: 1 : 2 Unit: Millimetres

75

150

Above Figure 3.2.19 Lamination of planar print path

Below Figure 3.2.20 Lamination of non-planar print path

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3.2.3 Principle of Non-planar Printing Path

PRINCIPLE

PRINT SPEED: 53MM/S TO 45MM/S

Unlike planar print paths, which have uniform layer heights, non-planar print paths result in non-uniform layer heights, which, depending on the layout of the print path, sometimes show very disparate layer height ranges.

Therefore, a basic principle of controlling the print volume to cope with different layer heights by controlling the print speed was determined.

The robot will move at a reduced speed to leave more material at high layer height requirements and the opposite at low layer heights.29

DISTANCE DISTRIBUTION

Figure 3.2.21 Distance distribution

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1.395

1.706

Figure 3.2.22 3D Printing Simulation of non-planar print path

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METHOD

01_Extracting Range of Distances

02_Fitted Speed Experiment Min Distance 1.395mm

Based on this basic principle, we propose a set of methods which is to extract the maximum and minimum values of layer heights, and then conduct printing experiments on them for simple shapes with different printing speeds respectively, and select the most suitable fastest and slowest printing speeds by observing their printing processes and results.

Print Speed: 50mm/s

03_Selecting Range of Speed Min Distance

Max Speed

1.395mm

53mm/s

1.706mm

45mm/s

Print Speed: 53mm/s

All of parameters of layer height are then remapped into this printing speed range to give each path a suitable speed corresponding to its layer height.

Print Speed: 45mm/s

Left Figure 3.2.23 Distance distribution

Right Figure 3.2.24 3D printed sample for understanding the speed setting a.50mm/s; b.53mm/s; c.45mm/s; d.50mm/s;

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The basic principle that faster speeds leave less material behind and slower speeds leave more material behind is used to control print speeds in order to solve the problem of varying heights associated with non-planar print paths.

Distance Range

Number of Layers

1.395 to 1.706

259

Print Speed: 50mm/s

1.706mm Max Distance

Max Distance

Min Speed

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3.2.4 30 Degree Printing Test

AIM

The first experiment is the printing of a shape with a maximum non-planar printing angle of 30 degrees.

1.395 Low

1.706 High

Max Degree 30 ° Number of Layer 259 Height 1.395 to 1.706 Print Speed 53/s to 45/s

Distance Distribution

Strucutre Detail

0

Above Figure 3.2.25 Indication of the experimental position

24

30 °

Based on the proposed method, a series of 3d printing simulation experiments were implemented in order to learn the angular limits of non-planar print paths on this shape.

Below Right Figure 3.2.27 Dimensions of experimental geometry

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240

Below Left Figure 3.2.26 Distance distribution

Proportion: 1 : 2 Unit: Millimetres

75

150

Figure 3.2.28 Photos of 3d printing process of 30 degree

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3.2.5 45 Degree Printing Test

The printing process of the model with a maximum non-planar printing angle of 45 degrees was observed to be smoother and the resulting model from the experiment was considered to be of good quality, so we set the maximum angle for the next experiment to 55 degrees.

1.309 Low

1.791 High

Max Degree 45 ° Number of Layer 259 Height 1.309 to 1.791 Print Speed 55/s to 45/s

Distance Distribution

Strucutre Detail

23

1

45 °

Above Figure 3.2.29 Indication of the experimental position

Below Right Figure 3.2.31 Dimensions of experimental geometry

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231

Below Left Figure 3.2.30 Distance distribution

Proportion: 1 : 2 Unit: Millimetres

75

150

Figure 3.2.32 Photos of 3d printing process of 45 degree

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3.2.6 55 Degree Printing Test

1.174 Low

1.744 High

Above Figure 3.2.33 Indication of the experimental position

Max Degree 55 °_ Flawed Number of Layer 275 Height 1.174 to 1.744 Print Speed 65/s to 40/s

Distance Distribution

Structure Detail

239

55 °

Although print simulations of models with a maximum nonplanar print angle of 55 degrees were able to be completed, the completed models were observed to have large imperfections at the turns. Through observation of the printing process, this defect was thought to be due to an excessive overhang angle.

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239

Below Left Figure 3.2.34 Distance distribution Proportion: 1 : 2 Unit: Millimetres

75

150

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3.2.7 60 Degree Printing Test Max Degree 60 °_ Failed Number of Layer 259

Printing simulations of models with a maximum non-planar printing angle of 60 degrees were conducted to confirm the possibilities. The printing process was finally stopped at two thirds of the way due to the extruder stopping the extruded material.

Height 1.143 to 1.776 Print Speed 53/s to 45/s

Gravity

The cause of this condition was thought to be the large tilt angle of the extruder due to the large angle of the non-planar print path, which prevented the material from being supplied and extruded properly.

Above Figure 3.2.37 3D printed Model

Structure Detail

243

60°

Distance Distribution

Below Right Figure 3.2.39 Dimensions of experimental geometry

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243

Below Left Figure 3.2.38 Distance distribution

Proportion: 1 : 2 Unit: Millimetres

75

150

Pellets Screwter

Figure 3.2.40 Diagram showing the orientation of extruder

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L=1

1/4

1/16

1/4

1/2 1/2

L = 1 1/4 1/4

1/16

1/4

1/2 1/2

1/4 L = 1 1/4

1/16

1/4

1/2 1/2 L = 1 1/4 1/8

1/16

1/4

1/2 1/2 L=1

1/4

1/8

1/4

Angle Constraint

1/2 1/2 Straight Connection

45°

Type B - 1 - D3

Figure 3.2.41 Angle constraint

L=1

1/2Figure 3.2.42

1/2

Selected connecting way

A series of physical and robotic fabrication experiments were conducted to better formulate design and construction strategies for the modular units.

In the physics experiments in this chapter, two conclusions were confirmed, including that linear connections have better load-bearing performance than angular connections, and that non-planar print paths enable the printing of models with a maximum angle of 55 degrees.

Based on the conclusion of the maximum print angle, a maximum tilt angle of 45 degrees was recognised as the constraint for this structural detail, considering the flawed end result of a non-planar print with a maximum tilt angle of 55 degrees.

This constraint will be used as a constraint parameter for the evolutionary optimisation in Design Development stage.

1/2 1/2

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3.3 VR Platform Formation

Rebuild

The project integrates modular systems, participatory design platform and robotic fabrication techniques.

In this phase, a series of module research introduced the basic module of the project and physical experiments verified the feasibility of module construction.

Global

Regional

Modular Building System (OPTIONS)

Local Three Levels of Participation (CUSTOMISATION)

On-site Robotic Fabrication (PRODUCTION)

Based on the modular research and physical experiments, the VR participatory platform will develop this operational logic: The module research will provide customisable module options for participants; while the participants will design on the platform at three different levels; and the design results obtained through the platform will be produced by the on-site robotic fabrication system. If, after a period of time, new spatial requirements arise, the participants can redesign and build the regions that need to be changed. This participatory design approach thus creates a loop that allows adjustments to be made in response to changes in time and demand, increasing the flexibility and adaptability of the retail spaces.

In addition, this section introduces the tools needed for the VR participatory platform

Figure 3.3.1 Operating logic of the platform

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3.3.1 Devices and Basic VR Settings

Design scene

Figure 3.3.2 Tool: Quest 2 all-in-one VR headset Figure 3.3.2 Device and view inside

Movement LEFT STICK

Quest 2

UI canvas

VR headset

STREAMING MODE PC CONNECTION

The device in this project is Quest 2. It needs to be connected to a PC and activated in streaming mode. The user can see the virtual reality scene through the headset and roam freely. The left stick is to control the user's position and rotation in the virtual scene, where the left stick controls the character's movement and the right stick controls the character's facing direction.

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Figure 3.3.3 Tool: Unity VR

Free view HEADSET

Rotation RIGHT STICK

The engine used to build the VR platform is Unity, which provides a convenient device interface that allows developers to use different hardware to develop games or applications. During the initial scene editing phase, the ground and vitural camera are created in the scene so that the participants can move freely in the future design scenario and find the appropriate locations.

Figure 3.3.4 Introduction of Quest 2 headset and controllers

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04

DESIGN DEVELOPMENT 4.1 Module Optimisation 4.2 Robotic Fabrication Simulation 4.3 Module Catalogue 4.4 Functional Division 4.5 Urban Strategy 4.6 VR Platform Development

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In this chapter, after the initial research and experimentation is conducted on the module, fabrication, and VR platform, an in-depth exploration is undertaken in the design development phase. The chapter commences with module optimization, aiming for a refined design, followed by the fabrication simulation to validate the manufacturability of the module. Subsequently, a versatile module catalogue is curated to accommodate diverse functions, and a range of design options is generated in alignment with the chosen urban strategy for integration into the VR platform. Finally, the chapter illustrates the development of VR platform.

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4.1 Module Optimisation 4.1.1 Module Morphology Optimisation with New Constraint Based on the conclusions of a series of physical experiments, a new evolutionary optimisation algorithm is implemented. All settings are consistent with those of the previous phase, except for the newly added angle constraints for one of the structural components.

Four objectives including maximizing space for users, Maximizing Ratio of Users’ Space and Module volume, Minimizing Structure Material, and Minimizing Displacement of finite element analysis.

CONSTRAINT Constraint strategies can greatly influence the optimisation direction of an evolutionary optimisation algorithm. In this case, for example, all individuals exceeding the 45-degree limit are considered invalid by the algorithm and need to be regenerated with another random individual to replace them.

At the same time the algorithm will avoid optimising in a direction that frequently generates invalid individuals.

Above Right Figure 4.1.2 Primitive of the modular morphology Above Left Figure 4.1.1 Angular constraint

: Fitness Critirion 1

Fitness Critirion 2

Fitness Critirion 3

Fitness Critirion 4

Maximize Space for Users

Maximize Ratio of Users’ Space and Module Volume

Minimize Structure Material

Minimize Displacement of finite element analysis

Figure 4.1.3 (a.b.c.d) Fitness criteria of evolutionary algorithm

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INDIVIDUAL SELECTION After comparing the optimisation results of a total of 5000 individuals over 100 generations, the top ranked individual in the average fitness solution was selected as the base morphology for the final module.

FITNESS CRITIRION 1

FITNESS CRITIRION 2

Maximize Space for Users

Maximize Ratio of Users’ Space and Module Volume

Generation : 97 Individual : 33 Unit: Millimetres

FITNESS CRITIRION 3

FITNESS CRITIRION 4

Minimize Structure Material

Minimize Displacement of finite element analysis

Figure 4.1.4 (a.b.c.d) Standard deviation graphs

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Above Figure 4.1.5 Morphology of best average solution

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4.2 Robotic Fabrication Simulation

AIM After defining the basic morphology of the final module, fabrication simulation experiments for the most complex components of this morphology were conducted to demonstrate the constructibility of this morphology.

The simulation experiment was divided into two main parts: panel and structure robotic 3D printing simulations for the most complex geometries of this component.

Left Figure 4.2.1 Panel printing simulation Right Figure 4.2.2 Structure printing simulation

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Experiment 03 Panel Printing Simulation

Experiment 04 Structure Printing Simulation

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4.2.1 Component Morphology Optimisation

Considering that the original geometry of this component presents hard creases, which are difficult to achieve by additive manufacturing techniques, morphological optimisation of this component was undertaken.

This optimisation was implemented by reconstructing the structural and panel systems of the component using polygon modelling to ensure that every point of the new model was consistent with the original model. The model is then optimised to a uniform and smooth curved geometry using polygon subdivision techniques.

Above Figure 4.2.5 Original geometry

Above Figure 4.2.3 Schematic diagram

Below Figure 4.2.4 Exploded diagram of the experimental section

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Below Figure 4.2.6 Optimised geometry

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4.2.2 Panel Fabrication Simulation 1 AXIS NON-PLANAR PRINT PATH For the super-twisted triangular surface geometry with this panel, a single-axis, non-planar print path is used. The failure of this experiment was due to the fact that the deformation of the complex forms upon cooling resulted in a reduction in printing accuracy.

Experiment 01 1 Axis Non-Planar

Figure 4.3.6 Schematic diagram

Print Speed 60/s to 40/s

Below Figure 4.2.7 Distance distribution

0.862 Low

Number of Layer 358 Height 0.862 to 2.142

2.142 High

Proportion: 1 : 4 Unit: Millimetres

Distance Distribution

Figure 4.2.8 Robotic 3D printing process

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2 AXIS NON-PLANAR PRINT PATH To address the problem of deformation, the second this experiment uses a 2-axis non-planar print path in an attempt to reduce the degree of deformation by following the geometrical orientation of the model and arranging the print path.

Experiment 02 2 Axis Non-Planar

Figure 4.2.9 Schematic diagram

Print Speed 70/s to 40/s

Below Figure 4.2.10 Distance distribution

0.688 Low

Number of Layer 389 Height 0.688 to 1.941

1.941 High Proportion: 1 : 4 Unit: Millimetres

Distance Distribution

Figure 4.2.11 Robotic 3D printing process

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PLANAR PRINT PATH Combining the failures of the previous experiments, the third experiment used a planar print path and the addition and fixing of a base. The results proved that this method can effectively deal with the deformation problem.

Experiment 03 Planar Print Path

Figure 4.2.12 Schematic diagram

Print Speed 50/s to 40/s

Below Figure 4.2.13 Distance distribution

1.406 Low

Number of Layer 259 Height 1.406 to 2.396

2.396 High

Proportion: 1 : 4 Unit: Millimetres

Distance Distribution

Figure 4.2.14 Robotic 3D printing process

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4.2.3 Structure Fabrication Simulation

PART A After verifying the constructibility of the panel, robotic 3d printing simulations of its corresponding structural components were undertaken.

Part A of the experiment was easily accomplished due to the relative simplicity of the geometry.

Number of Layer 351 Height 1.477 to 1.585 Print Speed 32/s to 28/s

1.477 Low

1.585 High

Proportion: 1 : 4 Unit: Millimetres

Distance Distribution Left Above Figure 4.2.15 Schematic diagram Left Below Figure 4.2.16 Distance distribution

Right Figure 4.2.17 Robotic 3D printing process

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PART B The structure of part B is difficult to fulfil by conventional flat printing solutions due to its excessive twisting.

Number of Layer 331

In this experiment, a non-planar print path that follows the direction of the geometry’s twist was deployed. This print path ultimately completed this part of the simulation experiment.

Print Speed 40/s to 20/s

Height 1.043 to 1.796

1.043 Low

1.796 High

Proportion: 1 : 4 Unit: Millimetres

Distance Distribution Left Above Figure 4.2.18 Schematic diagram Left Below Figure 4.2.19 Distance distribution

Right Figure 4.2.20 Robotic 3D printing process

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PART C The structure of part C is difficult to be completed by conventional planar printing solutions due to its excessive overhangs.

Number of Layer 339

In this experiment, a non-planar print path was deployed that followed the direction of the overhangs of the geometry. This print path ultimately completed this part of the simulation experiment.

Print Speed 45/s to 20/s

Height 0.964 to 1.811

0.964 Low

1.811 High

Proportion: 1 : 4 Unit: Millimetres

Distance Distribution Left Above Figure 4.2.21 Schematic diagram Left Below Figure 4.2.22 Distance distribution

Right Figure 4.2.23 Robotic 3D printing process

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4.2.4 Conclusion

The experiments also demonstrated that using different print paths for different geometries is beneficial for achieving better manufacturing quality.

1690

A series of robotic 3d printing simulation experiments for the structure and panels of the most complex parts of the module proved the manufacturability of this module.

Based on the results of robotic 3d printing, the study of robotic assembly of these components can be the next step in the research on the construction of modules.

For different architectural functions, users will have the opportunity to customise a wide range of panels based on different materials and printing methods. This part should be studied deeply in future development.

19

00

Unit: Millimetres

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780

Figure 4.2.24 Dimension of the experimental panel

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4.3 Module Catalogue

Exploring Component Reuseability for Multi-Axis Spatial Expansion A set of experiments are conducted to test which components can be used in the initial module to expand the space in different axis and spatial creation. The expansion experiments are conducted on x, y and z axis.

After that, the usability of the components as a cantilever system is tested to create a overhang which its porosity can be changed according to the seasonal requirements.

01

02

03

04

Module Optimisation

Fabrication Simulation

Module Catalogue

Urban Strategy

The experiments are focused on testing the possibilities of expanding space in steps of adding more components from the initial module and decreasing the surface area of newly fabricated components.

In the experiment 01.1 and 01.2 the expansion in x and y axis is tested and in both experiments, by reusing the components, the newly fabricated material surface area can be reduced almost 50%.

In the experiment 01.03 expansion in Z axis is tested to create spaces with double height ceiling. In this experiment newly fabricated material surface area reduced 2/3. Similarly, in the experiment for cantilever system, new material use reduction is 2/3 as well.

Following the completion of optimization research and the fabrication simulation phase, the next step involves the development of module catalogue. This catalogue is intended for integration into the VR platform, where it will serve as a foundation for experimentation with various urban strategies, specifically focusing on expansion and shrinkage scenarios. Concurrently, the printing simulation experiment validates the fabricability of these modules, while additional research aims to explore aspects such as module expansion and shrinkage, as well as their potential for reuse.

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4.3.1 Expansion in X-axis

An experiment was conducted based on the panel and structural division to assess the feasibility of utilizing pre-fabricated components from the original module for expansion purposes. The results of the x-axis expansion revealed a reduction of 52% in the need for newly fabricated pieces through the reutilization of module components.

Total Area of Newly Fabricated Components

A=37.5

Total Area of Newly Fabricated Components

A=41.1

Total Area of Newly Fabricated Components

A=33.7

Total Area of Newly Fabricated Components

A=28.1

Total Area of Newly Fabricated Components

A=25.4

Total Area of Newly Fabricated Components

A=19.3

Newly Fabricated Components Reused Components

Figure 4.3.1 Expansion in X-Axis

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4.3.2 Expansion in Y-axis

Total Area of Newly Fabricated Components

A=32.5

Total Area of Newly Fabricated Components

A=25.2

Newly Fabricated Components Reused Components

Figure 4.3.2 Expansion in Y-Axis

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4.3.3 Expansion in Z-axis

Total Area of Newly Fabricated Components

A=19.0

Total Area of Newly Fabricated Components

A=14.9

The same experiment was conducted along the Y-axis, demonstrating that 46% of the material could be saved by re-using it.

Total Area of Newly Fabricated Components

A=61.3

Figure 4.3.3 Expansion in Z-Axis

Total Area of Newly Fabricated Components

A=45.5

Total Area of Newly Fabricated Components

A=32.5

The experiment was repeated along the Z-axis, and the results indicated a significant material saving of 53% achieved through the process of reusing components.

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4.3.4 Cantilever Use

Newly Fabricated Components Reused Components

Incorporating cantilevered components within the tessellation framework, with the purpose of strategically removing elements in response to seasonal fluctuations to achieve diverse porosity and distinct shading effects, results in a remarkable 80% reduction in material consumption.

Total Area of Newly Fabricated Components

A=65.6

Total Area of Newly Fabricated Components

A=168.84

Total Area of Newly Fabricated Components

A=23.64

Figure 4.3.4 Cantilever use

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4.3.5 Expansion of Module

Expansion in X-Axis

Expansion in Y-Axis

Combination of X & Y Axis Expansion

The integration of various expansion axes offers an opportunity to create diverse spatial configurations according to the specific functional demands and user populations.

Through the implementation of adaptable modules designed to meet specific square footage requirements, a wide spectrum of combinations and arrangements can be generated. This variation offers flexibility for entrepreneurs to customize their spaces precisely according to their needs.

Figure 4.3.5 Expansion in XY-Axis

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4.3.6 Small to Medium Modules

S Floor Area= 20.19 Floor Area Ratio=x Weight=0.76

Figure 4.3.6 Small to medium modules

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S1 Floor Area= 53.06 Floor Area Ratio=2.62 x Weight=1.99

S2 Floor Area= 49.75 Floor Area Ratio=2.46 x Weight=1.87

M Floor Area=112.19 Floor Area Ratio=5.55 x Weight=4.22

The module catalogue is developed by the consideration for panel reusability and adaptability, enabling modules to dynamically scale in response to spatial needs. Within each module category, floor area calculations are conducted, facilitating the establishment of floor area ratios concerning other modules.

Weightings are then assigned in direct correlation to the floor area, indicating the module’s capacity to accommodate varying numbers of individuals based on its size.

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4.3.7 Medium to Large Modules Figure 4.3.7 Medium to Large Module

M Floor Area=112.19 Floor Area Ratio=5.55 x Weight=4.22

M1 Floor Area=169.67 Floor Area Ratio=8.4 x Weight=6.39

M2 Floor Area=171.42 Floor Area Ratio=8.79 x Weight=6.69

L Floor Area=265.13 Floor Area Ratio=13.13 x Weight=10

EXPANSION IN Z AXIS

Figure 4.3.8 Medium to large expansion in Z-Axis

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4.3.8 Small Configurations

S3 Floor Area= 51.6 Floor Area Ratio=2.55 x Weight=1.94

S4 Floor Area= 71.84 Floor Area Ratio=3.55 x Weight=2.70

S5 Floor Area= 67.99 Floor Area Ratio=3.36 x Weight=2.55

S6 Floor Area= 81.16 Floor Area Ratio=4.01 x Weight=3.05

S7 Floor Area= 131.27 Floor Area Ratio=6.50 x Weight=4.95

S8 Floor Area= 101.40 Floor Area Ratio=5.02 x Weight=3.8

Figure 4.3.9 Configuration of small modules

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Module Catalogue

SMALL TO MEDIUM MEDIUM TO LARGE

Figure 4.3.10 All configuration types

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4.4 Functional Division

4.4.1 Emerge Market (Retail)

The functions are divided into three as Emerge Market, Gastrova Nexus and Futura Fusison Gatherings.

Emerge Market hosts retail spaces which aims to transform the shopping experience by integrating technology and immersiveness. It creates an experimentation hub for entrepreneurs that how customers interact with new technologies and products. Emerge Market aims to redefine how consumers interact with products and brands, making shopping not just a transaction but an immersive and enjoyable journey.

Emerge Market Contains Spaces as: Pop-Up Showcases: Brands are going to showcase their new products to experiment it on the market. According to the customer interaction, they will have the opportunity to develop the product.

Fashion Trend Simulation Zones: Customers are going to be able to experience fashion trends of the past, present, and future through immersive trend simulation zones. These zones will provide historical context, showcase current styles, and even offer speculative glimpses into fashion evolution.

Interactive Experience Hubs: The store will be able to host virtual fashion shows where customers’ avatars model the latest trends.

Interactive zones will allow customers to test out products in virtual scenarios.

Sustainable Fashion Labs: On-site sustainable fashion labs are going to be integrated to put an emphasis on sustainability in retail industry. Customers can observe the creation of eco-friendly clothing items using 3D printing, upcycled materials, and other innovative techniques.

Holographic Galleries: Products are going to be displayed as interactive holograms. Shoppers can examine products from all angles, see them in different settings, and even interact with virtual prototypes. The galleries can rotate themes, showcasing different product categories or collaborating with artists to create different displays.

Figure 4.4.1 Emerge market interior view

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4.4.2 Gastronova Nexus (Food)

Gastronova Nexus Gastronova Nexus is a revolutionary dining experience that transports guests into a world of culinary innovation and sensory exploration. Gastronova nexus will inhabit spaces as: Nano-Cuisine Labs & 3D-Printed Artisanal Dishes: Chefs will utilize molecular gastronomy techniques, 3D food printing, and nano-ingredient manipulation to create dishes. Customised dishes will be formed layer by layer from edible nano-components.

Collaborative Creation Lab: Visitors can co-create their own dishes using interactive touchscreens. Diners can experiment with different flavor combinations, molecular structures, and cooking techniques, collaborating with the chefs to create their own dishes

Figure 4.4.2 Gastronova Nexus interior view

4.4.3 Futura Fusion Gatherings (Event)

Virtual Gastronomy Tours: AR & VR devices are going to be equiepped that will transform dining space into virtual landscapes. Visitors are going to be taken visual and sensory journey.

Futura Fusion Gatherings This innovative event space aims to elevate gatherings and experiences by incorporating advanced technologies, interactive elements, and innovative design principles. They offer opportunities for attendees to engage, connect, and be part of events that transcend traditional boundaries.

Multi-Sensory Event Theatres: The theatre will stimulate all the senses. In addition to visual and auditory experiences, it will incorporate scent diffusers, haptic feedback seating, and taste-enhancing technologies to create a truly immersive multisensory journey.

Responsive Dynamic Stages: Stages with responsive surfaces and lighting that could adapt to the energy of the music. The space will change in color, and texture in real-time, enhancing the visual and emotional impact of the performances.

Figure 4.4.3 Futura Fusion Gatherings interior view

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Immersive VR Event Pods: There will be VR pods where attendees can virtually attend events happening in different parts of the world.

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4.5 Urban Strategy

01

02

ZONING

CLOSENESS CENTRALITY

AIM: Functional Division

Figure 4.5.1 Urban strategy experiments flow

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AIM: Shifting Attractiveness from Oxford St.

03

04

SEASONAL CHANGES

PEDESTRIAN SIMULATION

AIM: Comfortable Outdoor Space (summer/winter)

AIM: Set Initial Site Configuration Options for VR Platform

Following the completion of module development, the urban strategy is defined and experiments are executed accordingly. The primary aim of this urban strategy is to redirect both the attractiveness and the crowd from Oxford Street to Henriette Pl. To achieve this goal, the research encompasses a series of five distinct experiments. These experiments involve the determination of zoning configurations, the computation of closeness centrality metrics, the design of comfortable outdoor spaces capable of accommodating seasonal variations, and the implementation of a pedestrian simulation within the VR application to provide guidance to stakeholders.

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4.5.1 Zoning Strategy

I F

J

K

G

H

D

E A

01 Dividing the site into squares

Figure 4.5.2 Zoning strategy

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02 Creating 17 metre squares by leaving 3 meters in between

03 Selecting the squares that can be used for zoning within site boundary

B

C

04 Adjusting the zones according to the site area

As per the module catalogue specifications, the maximum allowable dimension for a module is 17 meters.

Consequently, the site has been systematically partitioned into square areas, each with 17-meter edges.

This division process allocates a minimum of 3 meters for circulation paths between these squares.

Subsequently, the delineated squares serve as the foundation for identifying functional zones within the site area. Additionally, some of these squares have been strategically adjusted to ensure their compatibility with the site, optimizing their use for zoning purposes. In total, this approach has yielded the creation of 11 distinct zones, designated for the placement of modules within the project’s framework.

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4.5.2 Closeness Centrality

Figure 4.5.3 Closeness centrality introduction

The urban strategy of this project aims to address the issue of overcrowding and discomfort along Oxford Street by strategically redirecting pedestrian traffic to Henriette Pl., a parallel road that runs adjacent to Oxford Street. Oxford Street’s overwhelming congestion has led to discomfort for pedestrians and compromised the overall urban experience. This strategy seeks to channel and redistribute pedestrian traffic, creating a more pleasant and navigable environment for visitors.

By encouraging a migration of foot traffic to Henriette Pl., the project not only alleviates the strain on Oxford Street but also aims to revitalize and enhance the urban experience in this parallel thoroughfare.

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FOOD & RETAIL

EVENT SPACE

Small Floor Area= 20.19 x WEIGHT= 0.76

Large Floor Area=265.13 13.13 x WEIGHT= 10

Figure 4.5.4 Small and large module

Two distinct weightings are assigned based on the zone’s function, differentiating between retail & food and event spaces. Given that event spaces encompass a larger floor area and accommodate more people, they carry a higher weight compared to the food & retail space. These weights are scaled on a range from 0 to 10 in proportion to their respective floor areas. The maximum floor area a module can attain is 265 sqm, assigned a weight of 10, while the minimum module size is 20 sqm, corresponding to a weight of 0.076.

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Option 01

Option 02

Public Space

Figure 4.5.5 Option 01 zoning with weights Zone Weighing

Closeness Centrality Values

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76

793.34 803.68 934.33 879.03 890.61 833.14 907.47 1562.65 4268.43 881.77 763.86 1631.74 1006.69 3960.82 852.31

Figure 4.5.6 Option 01 closeness centrality result Most Centralised Zones 08 4268.43 13 3960.82 11 1631.74

12

13

14

9

10

11

7

8

4

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In option 01, equal weight is assigned to each zone, resulting in minimal variation in closeness centrality values across zones, except for zones 8, 13, and 11, which exhibit a higher degree of centralization.

5

6

Figure 4.5.7 Option 02 zoning with weights Zone Weighing

Closeness Centrality Values

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

0.76 0.76 0.76 0.76 0.76 10 10 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76

793.34 803.68 934.33 879.03 890.61 44985.61 48998.8 1562.65 4268.43 881.771 763.86 1631.74 1006.69 3960.82 852.31

Figure 4.5.8 Option 02 closeness centrality result Most Centralised Zones 06 4268.43 05 44985.61 08 1631.74

12

13

14

9

10

11

7

From Option 02 to Option 10, each zone accommodates two designated event zones. This strategic placement of event spaces serves as an experimentation to evaluate which configuration effectively enhances the degree of closeness centrality towards Henriette Pl.

8

4

5

6

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Option 03

Option 04

Public Space

Public Space

Figure 4.5.9 Option 03 zoning with weights Zone Weighing

Closeness Centrality Values

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

0.76 0.76 0.76 0.76 0.76 0.76 0.76 10 10 0.76 0.76 0.76 0.76 0.76 0.76

793.34 803.68 934.33 879.03 890.61 833.14 907.47 84375.23 230473.89 881.77 763.86 1631.74 1006.69 3960.82 852.31

Figure 4.5.10 Option 03 closeness centrality result Most Centralised Zones 08 230473.89 07 84375.23 13 3960.82

12

13

14

9

10

11

7

8

4

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5

6

Figure 4.5.11 Option 04 zoning with weights Zone Weighing

Closeness Centrality Values

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 10 10 0.76 0.76 0.76

793.34 803.68 934.33 879.03 890.61 833.14 907.47 1562.65 4268.43 881.77 41244.92 88106.08 1006.69 3960.82 852.31

Figure 4.5.12 Option 04 closeness centrality result Most Centralised Zones 11 88106.08 10 41244.92 08 4268.43

12

13

14

9

10

11

7

8

4

5

6

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Option 05

Option 06

Public Space

Figure 4.5.13 Option 05 zoning with weights Zone Weighing

Closeness Centrality Values

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 10 10

793.34 803.68 934.33 879.03 890.61 833.14 907.47 1562.65 4268.43 881.77 763.86 1631.74 1006.69 213864.55 46020.60

Figure 4.5.14 Option 05 closeness centrality result Most Centralised Zones 13 213864.55 14 46020.60 08 4268.43

12

13

14

9

10

11

7

8

4

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5

6

Figure 4.5.15 Option 06 zoning with weights

Figure 4.5.16 Option 06 closeness centrality result

Zone Weighing

Closeness Centrality Values

Most Centralised Zones

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

08 230473.89 10 41244.92 13 3960.82

0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 10 0.76 10 0.76 0.76 0.76 0.76

793.34 803.68 934.33 879.03 890.61 833.14 907.47 1562.65 230473.89 881.77 41244.92 1631.74 1006.69 3960.82 852.31

12

13

14

9

10

11

7

8

4

5

6

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Option 07

Option 08

Figure 4.5.17 Option 07 zoning with weights Zone Weighing

Closeness Centrality Values

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 10 0.76 0.76 0.76 10

793.34 803.68 934.33 879.03 890.61 833.14 907.47 1562.65 4268.43 881.77 41244.92 1631.74 1006.69 3960.82 46020.60

Figure 4.5.18 Option 07 closeness centrality result Most Centralised Zones 14 46020.60 10 41244.92 08 4268.43

12

13

14

9

10

11

7

8

4

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5

6

Figure 4.5.19 Option 08 zoning with weights Zone Weighing

Closeness Centrality Values

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 10 0.76 0.76 10 0.76 0.76 0.76

793.34 803.68 934.33 879.03 890.61 833.14 907.47 1562.65 230473.89 881.77 763.86 88106.08 1006.69 3960.82 852.31

Figure 4.5.20 Option 08 closeness centrality result Most Centralised Zones 08 230473.89 11 88106.08 13 3960.82

12

13

14

9

10

11

7

8

4

5

6

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Option 09

Option 10

Figure 4.5.21 Option 09 zoning with weights Zone Weighing

Closeness Centrality Values

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

0.76 0.76 0.76 0.76 0.76 0.76 10 0.76 0.76 0.76 0.76 10 0.76 0.76 0.76

793.34 803.68 934.33 879.03 890.61 833.14 48998.8 1562.65 4268.43 881.77 763.86 88106.08 1006.69 3960.82 852.31

Figure 4.5.22 Option 09 closeness centrality result Most Centralised Zones 11 88106.08 06 48998.8 08 4268.436

12

13

14

9

10

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7

8

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5

6

Figure 4.5.23 Option 10 zoning with weights

Figure 4.5.24 Option 10 closeness centrality result

Zone Weighing

Closeness Centrality Values

Most Centralised Zones

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

13 213864.55 11 88106.08 08 4268.43

0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 0.76 10 0.76 10 0.76

793.34 803.68 934.33 879.03 890.61 833.14 907.47 1562.65 4268.43 881.77 763.86 88106.08 1006.69 213864.55 852.31

12

13

14

9

10

11

7

8

4

5

In Option 10, it becomes evident that when the event areas are situated in Zones 11 and 13, as opposed to the other nine options, Zones in proximity to Henriette Pl. (specifically, Zone 13 in this scenario) attain the highest closeness centrality levels. Sequentially, after Zone 13, Zones 11 and 8 ranking as the second and third highest in terms of closeness centrality.

This observation underscores the potential for a gradual increase in the closeness centrality levels towards Henriette Pl., emphasizing the strategic positioning of event areas within the urban layout.

6

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Results of the Experiment

K

J

I F

Retail regions

G

E

A

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

Event regions

H

D

1

B

C

Figure 4.5.25 Design regions

The zones in the site were renumbered from design region A to design region K. From the results of the above experiments, it was concluded that region H and J were used for event regions (Futura Fusion Gatherings). The other regions are retail regions (Emerge Market, Gastronova Nexus).

The options in the event regions are larger modules and the options in the retail regions are smaller combinations of modules. The module options in each region will be used as genotypes for optimisation in the next step experiment.

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Figure 4.5.26 Genotypes - modules in regions

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4.5.3 Seasonal Changes Summer

Gen.23|Ind.6

Gen.30|Ind.7

Gen.25|Ind.3

Gen.40|Ind.7

Gen.44|Ind.5

Gen.47|Ind.3

The configuration of the modules is going to be changed according to the seasonal changes for the outdoor space comfort. A multi objective optimisation is run to achieve comfortable outdoor space and maximum floor area. In summertime the sunlight hours below 8 hours are maximised in the 40% of the site. On the wintertime, maximum sunlight and maximum floor space is aimed.

Gen.32|Ind.9

Figure 4.5.27 Summertime seasonal changes

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Gen.38|Ind.5

Gen.35|Ind.7

1-Max. Floor Area

2-Comfortable Outdoor Space

Gen.49|Ind.6

1-Max. Floor Area

Based on the outcomes of the generational algorithm, best performing phenotypes from the Pareto front are chosen. We select 10 phenotypes optimised for winter conditions and another 10 phenotypes optimised for summertime, which will be presented as options within the VR platform.

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Winter

Gen.28|Ind.8

Gen.28|Ind.8

Gen.30|Ind.5

Gen.41|Ind.2

Gen.33|Ind.8

Gen.36|Ind.0

Gen.38|Ind.7

Gen.49|Ind.9

Figure 4.5.28 Wintertime seasonal changes

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1-Max. Floor Area

2-Max. Sunlight

1-Max. Floor Area

Gen.45|Ind.1

Gen.48|Ind.8

2-Max. Sunlight

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4.5.4 Pedestrian Simulation

Gen 30- Ind.5

Gen 33- Ind.8

Circulation Density

Circulation Density

Max

Visitor Density

Visitor Density

Max

Path Length

Path Length Min.

Min.

Max

Min.

Path Length

Min.

Max

Path Length

Gen 49- Ind.9

Gen 28- Ind.8

Circulation Density

Circulation Density

Max

Visitor Density

Visitor Density

Max

Path Length Min.

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Min.

Max

Path Length

Figure 4.5.29 Pedestrian simulation results

Path Length Min.

Min.

Max

Path Length

The phenotypes that are selected according to the seasonal changes, are evaluated fort the pedestrian simulation as well.

A pedestrian simulation experiment is conducted to determine how visitors are circulation in different configurations. The results that we get from the pedestrian simulation is given as an instruction to the platform to help participants make choices.

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4.5.5 Expansion Pattern

00

01

02

03

04

05

Following the initial global configuration selection through the VR platform’s voting system, the modules can be expanded in response to growing user demand, increased visitor numbers, and evolving floor area requirements. This expansion or reduction can occur gradually, tailored to specific needs and demands.

Additionally, the configuration and adjustment of module size can be continuously updated based on visitor data, ensuring a responsive and adaptable spatial solution.

Figure 4.5.30 Expansion pattern 156 | META-MORPH

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4.6 VR Platform Development

Login pages

Design scales

Design results

01

02

03

Panelling (Local Scale)

Module Catalogue (Regional Scale)

Urban Strategy (Global Scale)

VR Participatory Design Platform

Upon completing the development of both the module and urban strategy, the resultant design options are input into the VR platform, and the following section addresses the integration of explorations spanning local, modular, regional, and global scales into the VR platform setting. This section provides an in-depth examination of the participatory VR building platform, presenting its technical framework, user interface components, participatory design methodologies, participant categorization, design region classifications, and a comprehensive testing regime that includes module selection, data transmission, and VR device functionality demonstration.

Framework of Platform Participation Methods

Interactive Functions

Figure 4.6.1 The platform development process

This section will introduce the operation logic and technical framework of the participatory VR building platform.

The first part is the overall framework of the application, including the login pages, user interfaces, the design process, etc.

The second part is the operation logic of the participation, including the specific method of participatory design, the type of participants, and the classification of design regions involved in the platform.

The third part is the basic operation test of the application and devices, including the test of the module selection system, the data transmission, and the basic VR interactive device function demonstration.

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4.6.1 The Framework of the Platform

Customisation at 3 Scales

The final design will be determined by the number of selections and votes.

When a round of participatory design is completed, the design will serve as the architectural configuration of the site for a period of time. Over time, when the space no longer meets the needs of the users, they can repeat the previous process to redesign a region or the whole site.

OPTION 2

Figure 4.6.2 The wire-frame of the application

Login Pages

Design Results

OPTION 1

Overall configuration options on site

This diagram shows the overall framework of the participatory virtual building platform application. It includes three main sections.

The first is the login pages, where the participants must select their identity type and the scale at which they want to join the custom design. The platform offers custom designs at three scales, from global scale to local scale.

Secondly, custom design process at the three scales. At each scale, the platform provides the participants with several optimised modular building options. They can make selections based on their spatial needs.

OPTION 3

Module combination in all regions

PANEL OPTIONS

Thirdly, result processing, after the above three levels of custom design, the modular selections made by each user are recorded by the platform with votes count. The platform filters out the option that receives the most votes as the final design result.

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At the Global scale, the platform provides several initial building configurations that cover the entire site. These configurations are experimentally optimised and are the recommended initial configurations.

Participants select their preferred configuration and are recorded as votes by the platform.

Panel selection on modules

RESULTS PROCESSING

If the initial site configuration does not meet the spatial needs of some of the participants, they can continue to engage in custom design at Regional scale. Select the area they need to redesign and reselect the appropriate modules. The platform will provide multiple module options for each design region, ranging in size from small to large, and in different heights and combinations of forms.

Local scale is to customise the panels of each module. This phase will involve the owner or renter of the building (entrepreneurs, performing artists).

They will be able to customise the different panel units according to their operational or performance effect needs.

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4.6.2 Design Options Input

4.6.3 Participation Methods

Global Op�on 1

Op�on 2

Op�on 3

Op�on 4

Op�on 5

Selected op�on Regional

A

B

C

D

E

F

G

H

I

J

Regions

1 2 3 4 ...

1 2 3 4 ...

1 2 3 4 ...

1 2 3 4 ...

1 2 3 4 ...

1 2 3 4 ...

1 2 3 4 ...

1 2 3 4 ...

1 2 3 4 ...

1 2 3 4 ...

Op�ons

2

3

2

4

2

1

1

3

4

5

Selected results

Local Op�ons

Figure 4.6.3 Options from experiments to platform

In the three levels of customisation described above, the designer's task is to provide the platform with options at each scale. In this project, these options are derived from a series of experiments shown in the previous sections.

The three levels are: Global scale, the overall configurations on the site; these options are from the urban-scale experiments in site development.

Regional scale, the modular combinations in all regions; these options are from experiments with various combinations in module development.

Local scale, the selections of modular panel components; these options are from robotic fabrication experiments in module development. In the future the project will continue to investigate construction materials and architectural features to provide more options for panel assemblies.

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Figure 4.6.4 Voting system

For the three scales above, participants selected the options as the design outcome that met their expectations. After customisation by a large number of participants, there are a certain number of selectors for each design option at each level. In this way, the platform will record this data as a number of votes, and ultimately the option that receives the most votes will serve as the final site configuration. Significantly, all options have been optimised by design experiments, meaning that they are the well-performing options that fit the function of the building. What the participants have to do is to choose a configuration based on their needs in terms of space size, shape, etc. After the results of each stage of the design have been determined by the voting statistics, the design can be moved to the next level of customisation. For example, before adding the regional scale, the platform should already have a completed global scale solution. The same applies from regional to local scale.

This process ensures that every tenant and user of the building has the right to express their needs, increasing democratisation and participation in the design process.

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4.6.4 Interactive Functions in VR

F

Module selec�on

K

J

I

G

H

Pla cin gm

E B

Retail Regions Emerge Market Gastronova Nexus

C

B

e ng mod Edi�

A

A

e od

D

Me nu

Event Regions Futura Fusion Gatherings

Figure 4.6.5 Design regions

Users(Customers)

Gastronova Nexus

Entrepreneurs

Users(Customers)

Entrepreneurs

Futura Fusion Gatherings Users(Customers)

Performance Ar�sts

City Hall

Modules

Global scale

C

Dest r o y mo de

Emerge Market

Regional scale Local scale

Figure 4.6.6 Participant identity and contribution

Each type of participant can be personalised for different functions, different areas and participate in different levels of selections. The types of participants in this platform are Users (Consumers), Entrepreneurs, Performance Artists and City Hall. The building functions are Emerge Market (retail), Gastronova Nexus (food) and Futura Fusion Gatherings (event). The design scales are Global, Regional and Local.

For Emerge Market and Gastronova Nexus, users and entrepreneurs can participate in the customisation.

In this case, users can participate in the selection of the Global and Regional scales. The entrepreneurs can continue with the Local scale, i.e. customise the panels according to the function. Users and performance artists can participate in the customisation of the Futura Fusion Gatherings space. Again, users can participate in the first two levels of customisation, while artists can join all three scales.

The city hall only provide advice at the urban scale and are not involved in module customisation and panel selection. Therefore, they can only participate in the Global scale selection on the platform.

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Remove selected

Figure 4.6.7 Basic functions of the module selection system

There are three types of module-specific operations: Placing Mode, Editing Mode, and Destroy Mode.

Placing Mode allows the participant to pick the desired module option from the menu (e.g. A,B,C). Editing Mode is to remove the current module and replace it with another. Destoy Mode, on the other hand, only removes the current module.

This platform mainly works with the Editing mode.

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Module to be edited

e

e

cem

Pla

Par�cipant with VR Devices

d Select an

nc sta i d nt

Design region

dule

move mo

Figure 4.6.9 Placed module in VR

Figure 4.6.8 Editing mode in VR application

Placed

Selecting

Editing

Use the headset to target the module to be edited, open the menu to select Editing Mode, press the right trigger to confirm. Open the menu to select another module, use the headset to control the module position, place it in the design region and press the right trigger key to confirm.

This test verifies the proper functioning of the module selection system, based on which more complex modules can be introduced.

LEFT STICK Movement Circular menu selection LEFT TRIGGER - Cancel

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Figure 4.6.10 Synced module in Rhino and Grasshopper

This test verifies the feasibility of syncing data from a VR application (Unity) to Grasshopper via C# scripts.

This step allows the platform to send all the information of the built model to Rhino and Grasshopper to be recorded in order to facilitate the statistics of the results. After the design solution is completed, the model information will be sent by Grasshopper to the robotic fabrication.

HEADSET Viewing Aiming Selecting Placing

RIGHT STICK - Rotation BUTTON B - Menu Module Selection Menu

RIGHT TRIGGER - Confirm

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05

THE DESIGN PROPOSAL 5.1 Options for Platform 5.2 Final VR Application

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Upon concluding the research related to the design development phase, this chapter provides an insight into the entire process of inputting design options into the participatory design platform, across diverse design scales, incorporating a voting system and engagement of different stakeholders. And with processing all the design options, based on the platform framework and devices described above, the participatory design platform works as a VR interactive application.

This chapter shows the full operational flow and design results of the application.

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5.1 Options for Platform 5.1.1 Options for Global Scale

GLOBAL

S1

S2

S4

S5

S3

Figure 5.1.2 Site configurations for summer

W1

W2

W4

W5

W3

Figure 5.1.1 Global scale options

At the Global scale, the design options are the overall configurations on site. These options are from urban scale experiments in site development.

Figure 5.1.3 Site configurations for winter

The urban scale experiments provide 10 optimised site configuration results that have been validated by multi-objective optimisation and other simulations, all with good performance. Five of these configurations are used for summer and five for winter. These configurations will be used as the initial recommended combinations for the site.

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5.1.2 Options for Regional Scale

REGIONAL

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

Figure 5.1.4 Regional scale options

At the Regional scale, options are from various experiments with combining and extending in module development. For each subdivided design region, the platform screened the amount of reconfigured and expanded modules based on the area scales. When participants are not satisfied with the recommended initial configuration at the Global scale, they can select the appropriate region and replace modules to expand or shrink their space according to their needs.

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Figure 5.1.5 Regional scale options

These module options are available in different combinations of forms and x,y,z axis extensions. The modular options offered by the platform may vary slightly in different functional regions. For example, the options for the event regions tend to be larger in scale, while the modules for the retail regions are relatively smaller and more flexible to create more forms of indoor and outdoor spaces.

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5.1.3 Options for Local Scale

Bar - private space

Opaque Panels

LOCAL

Pop-up store - semi-public space

30% Transparency panels

Event hall - public space Figure 5.1.6 Local scale options

60% Transparency panels

At the Local scale, options are building panel components with different functions. These options are from robotic fabrication experiments in module development. Standardised production allows for a wide range of panels of the same size to be assembled on the same structural skeletons. In future research, the project will continue to be delved deeper into materials, fabrication processes, and architectural functions to provide more panel options. In this way, participants will have the opportunity to customise more wall assemblies to suit their spatial needs.

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Figure 5.1.7 Panels with different transparency for different uses

At the current stage, the platform offers the option of panels with different levels of transparency. For example, completely opaque panels should be used in private spaces; panels with 30% transparency should be used in semi-public spaces; and panels with 60% transparency should be used in public open spaces, etc.

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Figure 5.1.8 The wire-frame of 3 levels design on platform

All of the above options are input into the VR building platform according to the appropriate scale, forming a complete custom design process for all three scales.

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5.2.1 Login Pages

5.2 Final VR Application

All Regions Global scale Regional scale

Retail Regions Global scale Regional scale Local scale

Event Regions Global scale Regional scale Local scale

Global scale

Figure 5.2.1 The start screen

Figure 5.2.2 Identity selection menu

RIGHT CONTROLLER Aiming at UI

LEFT CONTROLLER Aiming at UI LEFT STICK Circular menu selection LEFT TRIGGER - Confirm

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The start scene of the VR building platform, using the controller to click buttons to start or exit the application.

As mentioned above, different types of participants can be added to different functions or different levels of customisation of the design.

Therefore, the first step after getting started participants will go to the identity selection page.

BUTTON B - Menu RIGHT TRIGGER - Confirm

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5.2.2 Design Scales

Figure 5.2.3 Global scale design scene

Figure 5.2.4 Regional scale design scene

Participants need to select the scale they want to participate in the design, use the right controller B button to call out the menu, use the left stick to select the appropriate design scale and press the right trigger button to confirm. It is recommended to start with the Global scale.

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Figure 5.2.5 Local scale design scene

Figure 5.2.6 Back to the previous scene

Selecting a specific scale will jump to the corresponding design scenario. If the back button is selected, it will return to the previous page of the identity selection scenario.

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5.2.3 Design Process - Global Scale

Return and make other selections

Accept and confirm the configuration

GLOBAL

Figure 5.2.7 Selecting global scale

Switch summer or winter Select configuration on site Figure 5.2.8 Global scale options menu

Global scale options cover the entire site (all zones)

Figure 5.2.9 Global scale design work-flow

Global scale options cover the entire site (all regions)

At global scale, participants will make the selection on site. Select the configuration from the menu and check it on site in VR glasses. Click switch button on menu to change the category to the other season.

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Figure 5.2.10 Global scale option in VR

Click confirm if accept this initial configuration or click back to make another selection. And the modules in each region can be edited at next scale. If participants are not satisfied with an region of the initial configuration, they can select that region for further customisation.

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5.2.4 Design Process - Regional Scale

Regional

Figure 5.2.13 VR headset operation

Figure 5.2.11 Selecting regional scale Figure 5.2.14 Select the region to be edited

Figure 5.2.15 Aim at the module to be edited

Figure 5.2.16 Select another module from the menu

Figure 5.2.17 Place the new module in the region

Figure 5.2.12 Regional scale design work-flow

If the initial recommended configuration doesn’t meet participants’ requirement, they will have the opportunity to change the modules to expand or shrink their spaces in any region at Regional scale.

First, they need to choose the specific region and move to the regional scale design scenario with right controller.

Second, aim and select the existing module via headset and make a selection from the modules menu to change it.

If a satisfactory module is obtained, confirm and finish the current design scale.

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RIGHT CONTROLLER Aim at existing regions

RIGHT GRIP Select region to be edited

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5.2.5 Design Process - Local Scale

Local

Figure 5.2.18 Selecting local scale

Figure 5.2.20 Aim at the module to be edited

Figure 5.2.21 Select panel from the menu

Figure 5.2.22 Panels with 0 transparency

Figure 5.2.23 Panels with 60% transparency

Figure 5.2.19 Local scale design work-flow

After defining your building modules, the owners or the tenants can continue to the local scale which is the panels selection.

First, select the specific module from the previous design scenario or the modules menu with right controller to move to the Local scale design scene.

And choose the available panel for this module according to the function or their demands.

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5.2.5 Design Process - Design Results

Figure 5.2.25 Syncing data between Unity and Grasshopper

Figure 5.2.24 Sync design result from VR application to Grasshopper

After customising the selections for each region, all the users’ options and the number of votes for each option on the platform will be recorded in Grasshopper via the data transformation with C# scripts.

For instance, there are 4 options with votes in the editing region (figure 5.2.25, figure 5.2.26). And option 4 has the most votes, so it will be the final design result for that region. The same process will happen for all 11 regions.

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12

18

15

22

Figure 5.2.26 Example selections with votes count in region

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Figure 5.2.27 Final selection examples on platform

Figure 5.2.28 Final design result synced in Rhino

Figure 5.2.29 Send models of design result to robotic fabrication

The final design result as a digital model will be sent from the VR application to the Rhino and Grasshopper in order to be fabricated by robots.

With the changing season, trends or demands, participants can reuse the above process to make a new configuration according to their new spatial requirements. This system ensures adaptability in the face of changing retail industry.

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6.1 Conclusion

06

Evaluations and Revisions/ Future Development 6.1 Conclusion 6.2 Future Development

In the pursuit of creating ‘Meta-Morph,’ a project dedicated to enhancing the flexibility and adaptability of retail spaces, our overarching goal was to address the issues these spaces currently face. However, our vision extended beyond the boundaries of retail, encompassing the integration of event spaces and culinary experiences, transforming the entire site into a vibrant cultural hub. Our research canvas was the iconic Oxford Street, a renowned shopping district on the global stage.

Throughout the development of the module, the synergy between digital and physical data transition played a pivotal role, and the incorporation of 3D printing in the fabrication process yielded invaluable insights.

These insights unveiled both the limitations and challenges inherent in the realm of fabrication and digital calibration, enriching our understanding of these critical aspects.

Furthermore, a central aspect of our project was the creation of a VR application, guided by the principles of participatory design. This application not only enriches the user experience but also highlights the democratization of space ownership, fostering a sense of inclusivity and engagement.

In summation, ‘Meta-Morph’ encapsulates a broad spectrum of topics and scales, from overarching urban strategies to intricate joinery systems, from the tangible physical realm to the boundless possibilities of digital extension. The project represents a holistic endeavour aimed at reimagining and revitalizing retail spaces, with the ambition of not only meeting but also exceeding the evolving needs and expectations of the modern world. As the retail landscape continues to transform, ‘Meta-Morph’ stands as a testament to innovation, adaptability, and the enduring spirit of progress in the field of architecture and design.

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6.2 Future Development Robotic 3D Printing

Robotic Assembly

Based the robotic 3d printing research on this project, the fill optimisation of printing can be a focus for further development. This will be directly related to the final load-bearing behaviour of the module and the material usage.

In addition to the research on the fabrication of the components of the module, the research on the assembly of the module is another important further research.

In addition, materials research is an important part of more in-depth research. With the development of 3D printing technology, novel technologies and materials, including metal 3d printing and composite fibre, can be considered as further research directions for this project.

Figure 6.2.1 Fill optimization

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Figure 6.2.2 Material research

Based on the previously researched joints between structures, the joints between structures and panels will be important. Furthermore, the use of the normal direction of the geometry as a basis for the robotic tool path can be developed even further.30

Figure 6.2.3 Joinery system

Figure 6.2.4 Robotic tool path

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Data Transfer System The VR platform research part of this project verifies the one-way transfer of model data from the VR application (Unity) to Grasshopper. Using C# code and the receiver of the Grasshopper plugin, the project enables the transfer of object number and coordinate information. However, Grasshopper only serves to record design selections in the platform in this way.

In the future research, not only the data transfer from Unity to Grasshopper, but also from Grasshopper back to Unity should continue to be experimented with, eventually forming a bi-directional transmission. Based on this loop, participants can continue to analyse, simulate and optimise the digital model with sending the customised design solution in the VR application to Grasshopper. Subsequently, optimised results or analysis feedback can be sent back to the VR app to be viewed by the participant. This gives people the opportunity to understand the building information in more detail so that they can make judgements that are more appropriate with their demands.

Ultimately, the complete design will be generated by Grasshopper and deconstructed into productionready digital models. These models will be sent to the robotic fabrication system to complete standardised production. The aim of the data transfer system design is to automate the entire process from participant customisation to construction.

Interaction VR Headset

Space

Sc en e

Or de rs

Controller

Model information

Models

Data

Site

VR Application

Computation

Unity

Grasshopper

Fabrication

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VR Building System - Main Menu

APPENDIX

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Selecting placing mode

Selecting editing mode

Selecting destroy mode

Close the menu

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Global scale options menu

Regional scale options menu

5 options for summer and 5 options for winter

Option 1

4 options for example region D

Option 2

Option 3

Option 1

Option 2

Option 3

D

Option 4

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Option 5

Change season

Option 4

Back to main menu

Example design region D

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Local scale options menu

3 options panels with different transparency

Option 1

Back to main menu

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Option 2

Option 3

E:\UNI\001\ENVIRONMENT\Assets\Scripts\UDPContinousBoxes.cs 1 1 using UnityEngine; 2 using System.Collections; 3 using System.Collections.Generic; 4 using System; 5 using System.Text; 6 using System.Net; 7 using System.Net.Sockets; 8 using System.Threading; 9 10 public class UDPContinousBoxes : MonoBehaviour 11 { private string IP; 12 public int port; 13 public bool mouseOverBox = true; 14 GameObject lastHitBox; 15 public GameObject test1; 16 IPEndPoint remoteEndPoint; 17 UdpClient client; 18 19 //store old cube positions 20 public List<Vector3> oldPos; 21 22 // store valuees 23 public GameObject obj = null; 24 25 // Use this for initialization 26 void Start() 27 { 28 Send IP (AASchool WiFi) 29 IP = "10.15.1.34"; 30 Send port port = 001; 31 32 remoteEndPoint = new IPEndPoint(IPAddress.Parse(IP), port); 33 client = new UdpClient(); 34 35 // populating stored values 36 obj = GameObject.Find("OriginalParent"); 37 if (obj) 38 { 39 Initialise(); 40 } 41 // status 42 print("Sending to " + IP + " : " + port); 43 } 44 45 46 47 48 49 50 51 52 53

C# script for sending data

GH component for receiving data

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E:\UNI\001\ENVIRONMENT\Assets\Scripts\UDPContinousBoxes.cs // Update is called once per frame 54 void Update() 55 { 56 57 if (obj == null) 58 { 59 //Debug.Log("obj is null"); 60 obj = GameObject.Find("OriginalParent"); 61 if (obj) 62 { 63 Debug.Log("intialising"); 64 Initialise(); 65 } 66 else return; 67 } 68 69 70 Transform parentTransform = obj.transform; 71 if (parentTransform.childCount != oldPos.Count) // 3 cubes and 2 positions 72 saved { 73 Debug.Log("Re saving old positions"); 74 Initialise(); 75 } 76 77 bool atLeastOneFound = false; 78 string msg = ""; 79 for (int i = 0; i < parentTransform.childCount; i++) 80 { 81 Transform childTransform = parentTransform.GetChild(i); 82 Vector3 position = childTransform.position; 83 84 //Debug.Log("Child " + i + " position: " + position); 85 if (position != oldPos[i]) 86 atLeastOneFound = true; 87 88 string childName = childTransform.gameObject.name; 89 90 //msg += "#" + position; 91 msg += "#" + childName; 92 93 oldPos[i] = position; 94 95 } 96 if (atLeastOneFound) 97 { 98 Debug.Log("Position Sent!"); 99 Debug.Log(msg); 100 sendString(msg); 101 } 102 } 103 104 105

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2

E:\UNI\001\ENVIRONMENT\Assets\Scripts\UDPContinousBoxes.cs void Initialise() 106 { 107 Transform parentTransform = obj.transform; 108 oldPos = new List<Vector3>(); 109 110 // storing the original cube positions 111 for (int i = 0; i < parentTransform.childCount; i++) 112 { 113 Transform childTransform = obj.transform.GetChild(i); 114 115 if (i == parentTransform.childCount - 1) 116 oldPos.Add(new Vector3(-10f, -10f, -10f)); 117 else 118 oldPos.Add(childTransform.position); 119 } 120 } 121 122 // a funtion to send data via UDP 123 private void sendString(string message) 124 { 125 try 126 { // encode string to UTF8-coded bytes 127 byte[] data = Encoding.UTF8.GetBytes(message); 128 129 // send the data 130 client.Send(data, data.Length, remoteEndPoint); 131 132 } 133 catch (Exception err) 134 { 135 print(err.ToString()); 136 } 137 } 138 139 } 140

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BIBLIOGRAPHY 1. “[Draft] Oxford Street by Year Story - Mobile.” Flourish. Accessed September 18, 2023. https://public.flourish.studio/story/1644855/.

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14. How much does a shop renovation cost in 2023? | Checkatrade. Accessed September 18, 2023. https://www.checkatrade.com/blog/cost-guides/shop-renovation-cost/.

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23. Ghisleni, Camilla. “Social Sustainability: Participatory Design in Collective Space Creation.” ArchDaily, August 1, 2023. https://www.archdaily.com/1004448/social-sustainability-participatory-design-in-collective-space-creation?ad_ source=search&amp;ad_medium=search_result_all.

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Emergent Technologies and Design 2022-2023 Architectural Association School of Architecture MSc Dissertation Selin Ozasik (MSc), Liuxin Zhao (MSc), Tuotuo Chen (MSc)