Urbanrhiza

Urbanrhiza Groud 01, Group Menmbers: Zhiyue Gan, SN:19090242 Liangchen Zhu, SN:20085531 Ning Zhou, SN:19119612 Tutors: Claudia Pasquero, Filippo Nassetti, Eirini Tsomokou, Emmanouil Zaroukas

Contents

1

Urbanrhiza Introduction

Chapter-00

3

Biosensor & Norilsk Nickel

Chapter-01

8

Bio-intelligence Algorithm

Chapter-02

16

Mycelium Material Prototype

Chapter-03

20

Bio-degradable Architecture

Chapter-04

Chapter-00

- Urbanrhiza Introduction

Smart cities and blue-green cities have been enthusiastically implemented around the world in the post-epidemic era. To seek a new perspective to examine urban issues, designers need to reflect on the original design aesthetics, break away from the original epistemology dominated by anthropocentrism and re-examine the relationship between human and non-human. Humans no longer have the authority to dictate to or discriminate against other species following the non-anthropocentric framework of thought.

Urbanrhiza proposes an urban interface which integrates bio-intelligence and digital algorithms, to develop novel urban morphology. The project embeds waste collection and recycling stations into a distributed urban infrastructure, which is deploying mycelium as the basis for architectural systems. Finally, the goal is to make up for missing links in the city's metabolism, enabling urban circularity, and enhancing urban ecologies.

Artificial intelligence machines, mycelium, and other non-human elements will take on the role of city residents in the future, replacing humans dominance. Humans no longer discriminate against non-human intelligence but coexist with it in a complex symbiotic relationship.

1

Starting point of waste flood: the area that produces the most garbage

Chapter-01

- Urbanrhiza Introduction

The project's research in Norilsk explores how algorithms can interpret urban information through images and intervene in ecological landscapes.

Using the styleGAN algorithm, the dynamic transformation of industrial land and natural landscape topography such as wetlands, hills, and rivers is realized. The algorithm stores a wealth of geographic information and records the process of their changes. By reading and decoding the collected geographic information database, so that the GAN network can analyze and understand various ecological status quo to give further state assessment, value assessment, and development forecast here.

Finally, as an ecological sensor, the biological computer exhibits a sensitive perception of the environment. The collaboration of biological computers and machine learning forms a synthetic landscape. It is highly resilient to changes in the surrounding environment and can effectively respond to the environment. The synthetic landscape system is observing and protecting our ecosystem, monitoring water bodies, pollution, and climate change, becoming an indispensable part of our ecosystem.

3

4

5

AQUA VEGETABLE

AQUA VEGETABLE

PRIMARY PRODUCTIVITY

PRIMARY PRODUCTIVITY

POLLUTANTS

POLLUTANTS

WATER BODY

WATER BODY

AQUA VEGETABLE

AQUA VEGETABLE

PRIMARY PRODUCTIVITY

PRIMARY PRODUCTIVITY

POLLUTANTS

POLLUTANTS

WATER BODY

WATER BODY

AQUA VEGETABLE

AQUA VEGETABLE

PRIMARY PRODUCTIVITY

PRIMARY PRODUCTIVITY

POLLUTANTS

POLLUTANTS

WATER BODY

WATER BODY

AQUA VEGETABLE

AQUA VEGETABLE

PRIMARY PRODUCTIVITY

PRIMARY PRODUCTIVITY

POLLUTANTS

POLLUTANTS

WATER BODY

WATER BODY

6

7

Chapter-03

- Bio-intelligence Algorithm

Mycelium has extremely marvelous path intelligence and can be used as building materials. Using his path intelligence, the urban garbage recycling system can be organically formed, gradually decomposed, a multi-center recycling system, and the recycling system of urban materials can be used.

Mycelium has excellent graphical capabilities for geographic information, ecological information and cross-species biological information. This graphic ability can be explained as the one-to-one correspondence between the recognition and transmission of graphics and matter. This graphic ability is also the prerequisite for mycelium to generate urban digital landscapes from the perspective of graphic processing. Relying on this graphical ability, combined with algorithms that have life similarities, a city senario is finally generated.

8

5 mm

Growth Speed: 107 Digital Threshold: 2.89

Growth Speed: 115 Digital Threshold: 2.97

Growth Speed: 121 Digital Threshold: 3.02

Growth Speed: 127 Digital Threshold: 3.14

Growth Speed: 134 Digital Threshold: 3.17

Growth Speed: 141 Digital Threshold: 3.21

Growth Speed: 146 Digital Threshold: 3.26

Growth Speed: 152 Digital Threshold: 3.34

Growth Speed: 156 Digital Threshold: 3.39

Growth Speed: 160 Digital Threshold: 3.42

Growth Speed: 162 Digital Threshold: 3.64

Growth Speed: 167 Digital Threshold: 3.78

Growth Speed: 169 Digital Threshold: 3.95

Growth Speed: 172 Digital Threshold: 3.98

Growth Speed: 175 Digital Threshold: 4.56

Growth Speed: 184 Digital Threshold: 4.76

Growth Speed: 190 Digital Threshold: 5.19

Growth Speed: 190 Digital Threshold: 5.64

Growth Speed: 190 Digital Threshold: 5.94

Growth Speed: 190 Digital Threshold: 6.32

9

1km Buildings Centers Waste Collection and Tranfer Center

1km Buildings Centers Waste Collection and Tranfer Center

5km Buildings Centers Waste Collection and Tranfer Center

1km Buildings Centers Waste Collection and Tranfer Center

Mycelium Network 1 cm

CycleGAN Algorithm

Urban Network

1 km

Existing Road System

Random Distribution of Building Points

Urban Network

1 km

System Reorganization - Step 1

System Reorganization - Step 2

Mycelium Network

1 km

13

-- Rules of Cellular Automata

-Death by isolation: Each live cell with one or fewer live neighbours will die in the next generation.

-Death by overcrowding: Each live cell with four or more live neighbours will die in the next generation.

-Births:

-Survival:

Each dead cell adjacent to exactly three live neighbours will become live in the next generation.

Each live cell with either two or three live neighbours will remain alive for the next generation.

14

Chapter-03

-Mycelium Material Prototype

Mycelium can degrade urban waste and implement local waste treatment, thereby compensating for the missing links in the original urban ecosystem. The designer’s task is to reintroduce non-humans to the urban ecosystem via a multi-level structure and allow non-humans to take over the city’s waste treatment system.

With three components as the smallest construction unit, they can be freely combined to form highly flexible construction forms. This method achieves both the consumption of urban recyclable waste and the reduction of urban construction waste.

16

Raw Material

Raw Material

Day 1

Day 5

Day 10

lignocellulosic composites Pleurotus ostreatus

150 mm

1 cm

lignocellulosic composites Plastic waste Pleurotus ostreatus

lignocellulosic composites Coconut shell Paper waste Pleurotus ostreatus

120 mm 17

18

Component 1 Aggregation Stage 1

Component 2 Aggregation Stage 2

Component 3

Aggregation Stage 3

19

Chapter-04

- Bio-degradable Architecture

Based on the automata algorithm, the building itself forms a great deal of space typology. As a waste disposal site, the building has grown over a certain period to provide more activities for humans and non-human organisms and adapt to the function through different spatial attributes.

The narrow, vertical space is used by human as a fix and repair space, and the wider and horizontal space is used as human living space.

Urbanrhiza proposes a new urban morphology design experiment with dynamic fluctuations. In this scenario, the person’s dominant position in the decision-making process of urban design is temporarily removed, and artificial intelligence with non-human mycelium as the agent takes its place.

Cities dominated by bio and artificial intelligence will be able to reintegrate the end products of urban metabolism into the city’s new urban metabolism, thereby compensating for the urban material cycle’s missing links. Under this new order, the orientation of human perception of the world is domesticated by the environment, and open ecological aesthetics replace anthropocentrism. The interaction between human, non-human, materiality, artificial intelligence machines and modern cities has been re-established, and the ecological resilience of the city has been enhanced.

20

21

22

Raw Material

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