Adaptable morphodynamics

ADAPTABLE MORPHODYNAMICS | AA | EMERGENT TECHNOLOGIES AND DESIGN | M.SC DISSERTATION | 2013-2014T MSc CANDIDATES Silvia Daurelio Maria Fernanda Chaparro

ADAPTABLE MORPHODYNAMICS | AA | EMERGENT TECHNOLOGIES AND DESIGN | M.SC DISSERTATION | 2013-2014 MSc CANDIDATES Silvia Daurelio Maria Fernanda Chaparro

ARCHITECTURAL ASSOCIATION SCHOOL OF ARCHITECTURE GRADUATE SCHOOL PROGRAMME PROGRAMME:

Emergent Technologies and Design

TERM:

03

STUDENTS:

Maria Fernanda Chaparro, Silvia Daurelio

SUBMISSION TITLE:

Adaptable Morphodynamics

COURSE TITLE:

Emergent Technologies and Design - Master of Science

COURSE TUTORS:

Michael Weinstock, George Jeronimidis Evan Greenberg, Mehran Gharleghi

SUBMISSION DATE:

19.09.14

DECLARATION:

“I certify that this piece of work is entirely my/our own and that any quotation or paraphrase from the published or unpublished work of others is duly acknowledged.”

SIGNATURE:

Maria Fernanda Chaparro

Silvia Daurelio

EMTECH STAFF Michael Weinstock Director George Jeronimidis

Director

Evan Greenberg Studio Master Mehran Gharleghi Studio Tutor Wolf Mangelsdorf

Visiting Professor

ACKNOWLEDGEMENTS We would like to express our gratitude to Michael Weinstock and George Jeronimidis, whose expertise and sincere guidance enabled us to progress in our personal and professional development, leading us to explore new dimensions of the design. We would like to thank also Evan Greenberg and Mehran Gharleghi for providing us with constant support and inspirations. Finally, we would like to thank our families, friends and all people involved in this phase of our life, for their patience, encouragement and help as well as all our Emtech colleagues.

PERSONAL CONTRIBUTIONS This year in Emtech allowed us to explore new theoretical and experimental fields of architectural design through use of a consistent and scientific method. In particular, during our dissertation we gained new expertise and skills in the field of the parametric design, with particular focus on the computational evolutionary techniques applied to architecture. Our mind was opened to innovative design solutions for complex environmental and social contexts and we learned how to run environmental simulations at both the urban and building scale, in order to get a clear insight into causes and effects of the design process at each stage. Finally, the cooperation and exchange of ideas and expertise within the various teams allowed us to achieve shared goals.

MORPHODYNAMICS Morphodynamics is defined as the study of the three ways of interaction of physical, informational and geometrical processes that influences the changing form, shape and structure of living cells, tissues and organisms (Vijay Chickarmane, 2010).

table of contents ABSTRACT

10

13 13 24 25

4. SELECTED PATCH - Site Analysis - Rooftop villages - Analysis of Existing Urban ventilation - Conclusion

67 74 77 78

2. DOMAIN - High Density Cities - Concept of Public Space - Environmental Problems in dense urban tissues - Case Study

29 33 42 49

5. DESIGN DEVELOPMENT - Overview - Environmental factors - Social & architectural aspects - Connectivity

82 83 85 86

3. METHODS - Process Overview - Computational Techniques - Multi-software Data Transferring - Associative Techniques

57 58 60 62

6. EXPERIMENTS - Strategy’s parameters - Patch scale: Experiment 1 and 2 - Patch scale: Experiments comparison - Limitations - Porosity and Pedestrian Circulation

91 100 116 119 120

1. INTRODUCTION - Hong Kong’s Overview - Design Objectives - Design Strategy

Emergent Technologies and Design | AA |

7. EXPERIMENT 2: BLOCKS AGGREGATION SCALE - Sub-area 1 - Sub-area 2 - Sub-area 3 - Albedo

125 126 131 136 141

DESIGN EVALUATION

143

FURTHER DEVELOPMENTS

145

CONCLUSION

147

APPENDIX BIBLIOGRAPHY

Adaptable Morphodynamics

11

abstract

Adapable Morphodynamics addresses the development of complex high density urban systems over space and time. Building morphologies can be conceived as living organisms that change in form, shape and structure through the interaction of physical, informational and geometrical processes.

This research focuses on density, environmental quality and spatial identity. These studies are extended to present-day Hong Kong and addresses a design system that aims to reinterpret spatial logics, connected with local socio-cultural attributes, into a set of rules and code for an “intelligent densification”.

From the data gathered, two strategies are developed in parallel and as they become more defined, they begin to inform one another until a holistic urban approach is developed. Urban porosity and Urban growth at different scales (neighbourhood, plot and building) become the key design tools to achieve environmental performance, in terms of urban ventilation, housing public programmes, and maximizing pedestrian and bicycle accessibility for all people through a fluid mobility network at ground

and multiple layers of connectivity.

Existing building morphologies are transformed computationally into porous organisms and are used to construct accurate models of growth for regaining the lost demographic pressure.

Multi-objective evolutionary algorithms are employed to generate a complex urban design model. This is characterized by the emergence of public green areas, integration of sociocultural amenities within the existing building morphologies and by generation of a comfortable outdoor microclimate, at different operational scales. The improvement of the well-being of the urban population could be achieved through a spatial approach based on principles of social inclusion, especially in the most deprived areas of the patch, characterized by illegal and informal settlements, known as “rooftop villages or sky-slums”.

The main target, in the long term, will be to develop an “urban intelligence” that takes into account the mutual relation between demographic demand, site constraints and the potentialities and limitations of the architectural targets.

1. introduction 1.1 Hong Kong’s Overview 1.2 Design Objectives 1.3 Design Strategy

1.1 hong kong’s overview

Hong Kong’s intense urbanism is the outcome of a continual fluctuation of people, goods, data and services. The city’s compact footprint and rapid densification has led to the city’s vertical growth. This has defined Hong Kong’s skyline and has directly affected environmental and social conditions that challenge the contemporary urban planning of the city.

The city is part of the special Administrative Region of the People’s Republic of China, located at the mouth of the Pearl River Delta on the coast of southern China. Its strategic

geographical position as a gateway between the East and West has made it an attractive centre for international trade, which has contributed to the rapid economic and population growth.

It was first established as an entrepôt port and naval base, and has positioned itself as an important manufacturing and financial centre. In the 1950s, Hong Kong’s rapid industrialisation was driven by textile exports and other expanded manufacturing industries that resulted in a massive migration of refugees from inland China looking for better opportunities.

Fig.1.1: Architecture of density, Hong Kong Source: “Architecture Of Density” (the Outside Volume Of Hong Kong Inside/outside), Michael Wolf, 2013

Adaptable Morphodynamics

17

1.1 hong kong’s overview Annual Average Min and Max Temperature *

Annual Average Relative Humidity *

40

100 80 60

20

40 20

Sep

Oct

Nov

Dec

Oct

Nov

Dec

Aug

Jul

Jun

May

Apr

Annual Average Precipitation - Rain/Snow * 500

4 (12-19 km/h)

375 (6-11 km/h)

Aug

Jul

Jun

May

mm

Apr

Dec

Nov

Oct

Sep

Aug

Jul

Jun

May

Apr

0

Mar

0

Feb

125

Jan

1

Mar

250

Feb

2

Jan

3

F

Sep

Annual Average Wind Force *

Mar

%

Feb

Dec

Nov

Oct

Sep

Aug

Jul

Jun

May

Apr

Mar

Feb

Jan

ํC

Jan

0

10

* Source: 2013 data - www.weather-and-climate.com Fig.1.2: Hong Kong, weather, humidity, rain fall, wind force Source: http://www.weather-and-climate. com

As the population grew and labour costs remained low, a high demand for housing increased land prices. The Chinese population had dealt with crowded conditions for years, where the average housing space was 3.5m² per person: 4.9m² in small cities and 2,2 m²in big cities. Migrants were living in poor and compact spaces, but it wasn’t until a fire broke out in squatter settlements leaving around 53.000 refugees homeless that the government became more conscious regarding the low housing standards and the surge of the immigrant population in the city.

Following the incident, the government launched

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a public housing programme to introduce the idea of “multi-storey buildings” for the immigrant population, thus commencing a mass public housing project, providing affordable homes for those on low incomes.

The city went on to develop its economic and financial prosperity via a mixed economy of hightechnology products and small industries which are reflected in the financial towers along the coast, juxtaposed with the crafted-base informal economy made up of numerous small household companies. Hong Kong is a city of constant

change, capable of adapting and fulfilling the challenges of becoming a global city.

1.1 hong kong’s overview Population and Water Consumption (1970s-2010s) *

Hong Kong’s Fresh Water use (2011) *

8

Water consumption (mcm/year)

Population (millions)

7

1,000 900 800 700 600 500 400 300 200 100 0

6 5 4 3 2 1 0

1971 1970

1981 1980

Hong Kong population

1991 1990

2001 2000

2011 2010 Year

Hong Kong water comsumption

Hong Kong (2011) Sector

Percentage

Domestic

54.1

Construction/ shipping Government Establishments

1.5

Industry

6.3

Service Trade

25.6

Flushing

8

Total

100

4.5

Average water consumption per person/day in Hong Kong (2012) * Fresh water

43.3%

46.6%

9% 1.1%

Salt water Showering Tap water Washing machines Others

Total = 214.7 litres 90 litres for Flushing

25% more than the global average (=170 litres) * Source: 2014, Liu S., Williams J.,“Different Approaches to water dependency”

Fig.1.3: Hong Kong, water consumption Source: “Different approaches to water dependency”, Liu S. Williams J., 2014

The build out of the city and its tropical climate has triggered several environmental problems, such as urban heat island effect, high levels of pollution and a shortage of water. Temperatures have increased during the last decade in urban and rural areas by 0.6ºC and 0.2ºC respectively; thus high temperatures of around 28ºC to 31ºC, high levels of humidity around 80 per cent, and low wind ventilation at ground level are observed during the summer months. These conditions unmeet the thermal comfort of the outdoor environment, making it difficult to enjoy

any outdoor activity, even walking. Short-term solutions have been applied, such as the use of air conditioning on escalators and the pedestrian secondary layer.

One of the biggest impacts of climate change in Hong Kong is a shortage of water. Due to urbanisation, water resources have been diminished, with 20 per cent of the water supply currently coming from water catchments and 80 per cent of the water being imported from the Dongjiang River. The river is shared with five

other cities in the Pearl River Delta Region under the Dongjiang Basin Water Resources Allocation Plan. The plan has a maximum usable water resources limit and is unlikely to have surplus capacity in the future, due to the warmer climate.

The rapid growth of population means greater water consumption, thus increasing domestic demand.

Adaptable Morphodynamics

19

1.1 hong kong’s overview

Hong Kong’s area of 1,104km² has the world’s highest percentage of urban green space; over 80 per cent is comprised of mountains and wetlands and the other 20 per cent of the territory is left for the development of the urban tissue that hosts a population of 7,184,000 inhabitants. The city is built on steep slopes and is therefore facing one of the major challenges of construction, due to landslides and unsuitable terrain for building. The high demand for land has driven Hong Kong to use the majority of the suitable land for construction, creating a contrast between the constructed and open areas.

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The city’s high density and constant demand for construction has only left a relatively small area to act as public space for the city’s population; the average public space per person in Hong Kong is 2m², while in Western cities, such as London, the average is 8m². The shortage of spaces for social interaction has led Hong Kong inhabitants to re-define what public space is, so that streets, market areas and shopping centres become areas where social activities take place.

Fig.1.4: Topography and High density, Hong Kong Source: http://www.cn.hdscreen.me

1.1 hong kong’s overview

Motorcicle 1%

Motorcicle

Walking

Car

31%

44.7%

40%

36,3%

11%

22%

37%

58%

Taxi

20%

Car

30%

Walking

Walking

0,7%

11%

41%

1,4%

Bus

Metro

13,7%

40.8%

Private Bus

Motorcicle 1%

7.2%

30%

7%

2%

48%

Metro, DRL

45%

Walking

27.7%

1,4%

Bus

Walk - Bike 45%

Metro

13,7%

Rail

40.8%

Private

Comunal Private 7%

11%

17.7%

18%

7%

11%

58%

Taxi

22%

Bus

31%

44.7%

Bus - Tram

1%

Walking

Car

4.9%

Bicycle

Taxi

Private

Car Taxi 7.2%

7%

3%

Public Space

P

Walk - Bike

6%

45%

Forest 40%

Public Transportation 48%

Protected parks

layer’ that connects corporate lobbies, hotels, The high density has had aCommunal significant impact on Public Space 6% Space 7% Private 3% shopping malls and transportation hubs with the the development of the city, in which proximity becomes a necessary condition for sustainability. urban fabric.

A full range of activities, such as residence, shopping, working and leisure, all happen in The wide range of possibilities for transportation, the same place and at the same time; this is such as ferries, trails, trams, buses, and only possible thanks to the complex that allows escalators, encourage the population to use this intense dynamic of interaction to happen. public transportation and opt for pedestrian Hong Kong has proven that a high population journeys. The effectiveness of this model shows density can be viable through the provision of that only 4 per cent of the journeys are made by effective public transportation systems and car, 44 per cent by walking and 52 per cent by infrastructure that allows pedestrian journeys public transportation. through footbridge passages: a ‘secondary .

Protected Parks 44%

P

Public Transportation

44%

48%

Forest 40%

Fig.1.5: Map Green areas and

Protected Parks 44% MethodPublic Space 6% Hong Communal Space 7% of transportation, Kong

Source: LCE Cities, Urban Age Cities Compared, 2011

Adaptable Morphodynamics

21

1.1 hong kong’s overview

Fig.1.6: Topography, secondary layer, podium diagram, Hong Kong Source: “The Making of Hong Kong,from vertical to volumetric”, Barrie Shelton, Justyna Karakiewicz and Thomas Kvan, 2010

The verticality of the city and the intensification of usages bring a concentration of activities and modes of movement across the city; several levels of connectivity that extend to other buildings have created the largest secondary pedestrian layer in the world, with over 800 metres in distance that elevates over 135 metres from the ground floor. It is not only used as a circulation, but also plays an important role as public space where leisure activities take place.

solutions and opportunities for accessibility on different floors of the buildings, and the proposal of three-dimensional connections from where the ground floor extends, like a series of mid escalators, has been suggested to ease the movement of the pedestrian population in steep areas. This continuity of connection would allow the permeability of the buildings and increase the flow of people through commercial and market spaces.

The need to move through congested areas and across challenging topography has led to inventive

Hong Kong’s high-density network model is coherent to the one suggested by Jane Jacob

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in 1961 when she challenged the planning world by suggesting “more and shorter streets to give more choice, convenience and vitality to an area: it would give more route options, and more strategic crossing points and corners; induce more stopping and meeting points; and create more favorable location points for the generation of economic and other activities” (Jacobs, 1961).

1.1 hong kong’s overview Fig.1.7: Footbridge , Connection secondary layer and podium, Central ICF , Hong Kong Source: http://www.wikipedia.com

Adaptable Morphodynamics

23

1.2 DESIGN OBJECTIVES

SITE

CONDITIONS

AMBITIONS

STRATEGY

SHAM SHUI PO YAU TSIM MONG

0 m/s 1.6 - 3.4m/s

1.73 km²

Urban Heat Island Effect

EXISTING MORPHOLOGIES

203.094 inhab.

Population 203.094 inhabitants Density 117.395 inhab/ km

Increase urban airflow

TOWERS -

Low Urban Ventilation

High density Minimize disruption 20%

1.66m²/inhab x 2 Rooftop Villages

Duplicate Public Space m²/inhab

Fig.1.8: Overall design objectives and strategy

The design proposal will be based on improving the local socio-cultural and built environment in the degraded high-density district of Sham Shui Po and Yand Yau Tsim Mong in the city of Hong Kong. General research about the city will be carried out in order to understand the local urban identity and quantify spatial attributes in relation to the existing socio-cultural factors.

Data about the climatic conditions of the city will be collected to focus on specific urban environmental problems, such as high heat island intensity and serious air pollution due to a lack of natural ventilation in the urban clusters.

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The application of an evolutionary urban design strategy will focus on the emergence of urban attractors, which will be able to interconnect with the different parts of this existing urban fabric and enhance its spatial, social and environmental qualities. Urban inclusion will be followed in order to minimise disruption and maximise benefits for inform al and s elf-built settlements.

Optimised building morphologies will provide the existing urban fabric with social and cultural amenities in critical points of interactions.

They will be refined through the integration of greenery, a porosity system including airflow, and a fluid pedestrian circulation at multiple levels. Using greenery solutions to absorb pollutants, mitigating the urban heat island effect through the reduction of humidity levels, and creating global urban air ventilation will be important environmental goals to enrich spatial qualities.

1.3 DESIGN Strategy

STRATEGY

POROSITY STRATEGY TOWERS - PODIUMS

BREAK

Increase urban ventilation

SOCIAL LOGIC

Social inclusion Public spaces Semiprivate spaces

Micro Economy Relocate Housing Urban Wetland

BLOCKS

ROUGHNESS STRATEGY

ENVIROMENTAL LOGIC

EMERGE

CLUSTERS PUBLIC SPACE

CONNECT

This dissertation applies an evolutionary urban strategy through a porosity and roughness system that will affect the existing morphologies of the buildings. Adaptable morphodynamics aims to optimise the existing urban tissue in order to create a symbiotic relationship between the built environment and the site conditions.

Morphodynamics is defined as the study of the three ways of interaction of physical, informational and geometrical processes that influences the changing form, shape and structure of living cells, tissues and organisms (Vijay Chickarmane, 2010).

The improvement of the environmental conditions and social inclusion are the main drivers of the experiments. These factors aim to enhance the qualities of a vibrant high-density tissue and respond to the site’s deficiencies to reduce the ecological footprint and provide better living conditions. The design strategy will attempt to impose minimum disruption in order to maintain the high density of the patch; this will be achieved by the relocation of at least 40 per cent of the population.

Social Provitions Transportation system Secondary layer Rooftop villages

The system takes into consideration multiple fitness values for the optimisation of the buildings, an established criteria to meet the target for solar exposure, ground exposure and volume.

This will generate a set of possible optimum solutions that will affect the site conditions and the possible dynamic of interactions within the patch. The result of the proposal will be the result of a calibration between the experiments of spatial qualities and the impact on urban ventilation.

Adaptable Morphodynamics

25

2. domain 2.1 High Density Cities 2.2 Concept of Public Space 2.3 Envirnmental Problems in dense urban tissues 2.4 Case Study

Fig.2.1: Urban Sprawl: Calgary, Alberta Source: http://wwwfritzmuellerphoto. com

2.1 high Density cities

Fig.2.2: High density, compact footprint, Singapure Source: http://www.planetizen.com/ node/60424

The question of how to approach a high-density city model has always been open for debate, In some cases High Density is referred to as a negative quality of the cities because of their impact on the environment and the damage it causes to land quality. Cities consume and produce disproportionately large amounts of resources and green house emissions; American and Australian cities generally have greater surface area than European and Asian cities.

The ecological footprint of the American city is typically 30 times that of the physical city because of the amount of area that it takes to build up the city, therefore small footprint cities might have more intrinsic potentials to become less resource consuming than more sprawling cities with sparser living and building patterns.

Adaptable Morphodynamics

29

2.1 high Density cities Fig.2.3: Central Hong Kong, Exisiting secondary layer Source: "Cities Without Ground: A Hong Kong Guidebook", Adam Frampton ,Jonathan D Solomon , Clara Wong, 2012

In the specific case of Hong Kong, Hui concludes “Hong Kong’s High rise compact forms bring real benefits to the city by virtue of more compact distribution area and far less energy consumption for travel compared with almost every other city in the world”. (Kenworthy, 2008). However, he also points out some potential disadvantages of high density living: it can create road and micro climate conditions that result in more, not less energy use – for instance, cars consume considerably more fuel in slow moving traffic and homes use more air- conditioning when contained in a city of massive buildings forms that block the natural flow of air. (Hui, 2001) The advantages of the high-density city are the effectiveness of public transportation, which result in more journeys on foot and discourage the car as a method of mobility. A denser urban living contains buildings that host a large mixture of usages allowing homes to be serviced from less extensive infrastructure. By the interaction and dynamism of this usages it also creates a greater concentration of people meaning greater range of social, health, recreational and other services that can be offered in closer proximity.

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Emergent Technologies and Design | AA |

This has a direct impact on lowering the costs of constructing and managing services.

It is the interaction of usages that bring vitality and intensity to a place through multiple scales of connection from local to global. Then it is not only the density that is in control of the dynamics and interactions of a place, but the physical configurations and the way they are connected, that can make a high density city more sustainable. Christopher Alexander, reinforced Jane Jacobs notion of the city as “organized complexity” he states: “The city is not a Tree”, in which he used the ven diagram to illustrate the nature of relationships between urban activities, his argument was: that urban services and facilities are symbiotic and cannot exist in isolation from each other. A connection between different activities means more frequent use for all of them: They interact by virtue of their proximity and the form of spaces that join and lead to them. (Alexander, 1966) Other high-density cities such as London and New York have developed a different form of urbanism; London’s urban sprawl consist in

a low-density living and high-density working areas, this creates different dynamics in which the lack of integration will result in a larger amount of time commuting, while New York has successfully achieved a balanced integration between living and working environments reducing commuting time. On the other hand, Hong Kong is the most integrated global city in terms of connectivity, which allows a complex interaction of usages and activities within the city.

Transport infrastructure is a critical driver of urban form, enabling the centralization of economic functions and the accommodation of a growing population. Without public transport, space-hungry motorways dominate, resulting in more sprawl and congestion. The oldest and most extensive metro, bus and rail systems are in London and New York, creating high levels of accessibility. Hong Kong’s younger metro network extends to approximately and because of its constrained topography has developed a more efficient and affordable public transport.

(Cities, 2011)

2.1 high Density cities

Pilmico

Upper East

London

New York

Residential Density Peak 27.100 pp/km2

Population 8.308 million Area 1,572 km² Density 5,285/km2 Green Public space 38.4% Global City Ranking 2

Car 36,3% MotorcicleCar Taxi 0,7% 7.2% Walking 22% 20% Private Bus 7.2% 37% Car 4.9%

g

%

36,3%

7% 22%

37%

Taxi48% 1%

41%

27.7% 1%

40.8%

1% 31%

2%

30%

Metro, DRL Walking 22%

Metro, DRL

22%

Taxi

11%

1,4% 31%

Bus

13,7%

Taxi

36,3%

37%

Bus Rail

7% 22% 45%

27.7% 1%

40.8%

Private

22%

6%

45%

Forest

40%

Protected parks

Fig.2.4: Residential 40% Density and method of transportation,global cities.

Protected parks

Public Transportation

44%

44%

48%

Forest 40%

3%

Public Space

Forest

Private 3%

17.7%

Bus Rail

7%

Walk - Bike

6%

Communal Space 7%

44.7%

Comunal Private

7%

3%

Public Space

%

Bicycle 2% Walking

18%17.7%

Comunal Private

alk - Bike

44.7%

Bus - Taxi Tram

Metro

18%17.7%

7%

Walking

45%

RailMetro, DRL

41%

1,4%

Bus

48%

27.7% 48%

40.8%

13,7%

20%

Bus/Tram

Metro

58%

Walking

Private Bus 7.2% Car 4.9%

58%

11%

7%

Car Motorcicle Taxi 0,7% 7.2%

11%

Walking

Car

18%

Bus Taxi - Tram

Metro

Private Bus 7.2% 4.9%

Motorcicle

44.7%

Bus

Car Taxi 7.2%

11%

30%

Bicycle Bicycle

Population 7,174 million Area 1,104 km² (18% buildable) Density 6,516 pp/km2 Urban Public space 6% Global City Ranking 5

Car

20%

2%

41% 45%

Hong Kong

Walking

1%

Walking

0,7%

Residential Density Peak 111.100 pp/km2

Population 8.337 million Area 1,213 km² Density 10,725.4/km2 Green Public space 14% Global City Ranking 1 Motorcicle

Motorcicle

West Kwoloon

Residential Density Peak 59.150 pp/km2

Protected Parks 44%

Public Space 6%

Communal Space 7%

Private 3%

Source: LCE Cities, Urban Age Cities Compared,2011.

Forest 40%

Public Transportatio

48

Protected Parks 4

Adaptable Morphodynamics

31

UTILITIES

2.1Manufacturing high Density cities Utilities

INTELECTUAL CAPITAL

CITY GATEWAY

SUSTAINABILITY

INTELECTUAL CAPITAL

CITY GATEWAY

SUSTAINABILITY

Construction Services Others

Innovation City gate Infraestructure Sustainable Businness

Manufacturing Utilities Construction Services Others

Innovation City gate Infraestructure Sustainable Businness

UTILITIES

MOST GLOBAL CITIES 2013

New York London 5.86 Tokyo 5.42 Paris 5.35 4.14 Hong Kong MOST GLOBAL CITIES 2013 Chicago 3.94 New York 6.22 Los Angeles 3.9 London 5.86 Singapore 3.45 Tokyo 5.42 3.44 Sydney Paris 5.35 3.4 Seul 4.14 Hong Kong Chicago 3.94 Los Angeles 3.9 A comparison between the global cities regarding Singapore 3.45 important aspects for living conditions, highlight Hong Kong’s main deficiencies. 3.44 As a contrast Sydney to other global cities, Hong Kong’s public space Seul (in the urban area) is only 6 per 3.4 cent compared

Tourist Int. meetings Passanger Flow Airport Accesss Digital Economy

Disaster risk Thermal comfort Recycle Waste Air Pollution Public Space

Tourist Int. meetings Passanger Flow Airport Accesss Digital Economy

Disaster risk Thermal comfort Recycle Waste Air Pollution Public Space

PUBLIC TRANSPORT

MAJOR CONSTRUCTION

HOUSING

PUBLIC TRANSPORT

MAJOR CONSTRUCTION

HOUSING

6.22

to cities like London and New York with a 38 and 14 per cent respectively, The wealth gap, lack of public space, poor living conditions, long working hours and environmental problems reveal the instability of Hong Kong’s regulations towards the wellness of its population.

The development of Hong Kong as a leading

manufacturing city defined living standards and conditions that have still remained in the urban culture. The city developed in order to meet an economic and industrial target undermining the standards of living conditions of the population.

High density understood as overcrowding, in a city with a shortage of public space, has a great impact on social and mental health, as an example; young population being raised indoor, with no social interaction.

It is important to value the challenges that high density cities brings within, a great complexity

of vertical relations that can generate patterns of living the city; but this can only be achieved through a balance and a structural logic established by the understanding of the context and cultural background.

Fig.2.5: Hong Kong, General aspects performance.Ranking and comparsison global cities.

Source: http://www.citymayors.com/ statistics/global-cities.html.

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2.2 Concept of PUBLIC space

WHAT IS A PUBLIC SPACE? Urban planners have historically defined a “public space” as the collection of publicly owned and managed outdoor spaces, including streets, squares, parks, and similar informal recreational areas, to which every member of the community has free access, regardless of his or her social and economical status.

Accessibility and circulation are not the only elements that characterize a public space, but the functions directly connected to social and cultural implications are relevant factors as well.

In human history, the idea and form of public space arose and developed in relation to needs, values and characteristics of specific times, places and populations’ culture. William H. Whyte, an American sociologist and urbanist, states, “Public spaces as expression of human endeavour and artefacts of the social world are the physical and metaphysical heart of the cities, thus providing channels for movement, nodes of communication and common ground for cultural activities.” (Whyte, 1980).

In general, the term “public space” is directly associated to social and public life, and reflects Western habits of civic activities that take place in squares, parks and similar places, showing the freedom of speech and association that characterizes our society. As a consequence, it is often ignored that in other contexts social and public activities can often occur in a nonpublic space and through different channels of interaction, or even that the same idea of public space can completely mismatches the mainstream view. For example, in China’s old cities open space and nature are broken into smaller pieces and evenly distributed according to a human scale and a horizontal layout, while Western cultures group open space into bigger

pieces, distributing it through important nodes in a vertical oriented city. The enclosing of spaces characterizes the Chinese perception of the space, seen as series of enclosed worlds.

(Nijveldt, 2013) As a consequence, several and various factors, such as people’s lifestyle, modes of social interaction or generation gaps, need to be analyzed to get a clear insight into the nature that shapes public spaces. Not only is it important to put in relation the characteristics of a public space with the individual and collective values that are performed in it, but it is also crucial to define the seasonal and cultural rhythms associated to a specific place. In addition, it seems that the nature of a public space is clearly related to local climate conditions, accessibility and walkability, but it has also a connection with the urban transformations brought by the integration of cities into the global scale.

To conclude, this section will explore the concept of public space from a non- Western perspective, in order to get a clear insight into the contrast that today shapes the Asian cities, divided between a local culture, which is linked to a traditional past, and a globalized emerging financial power. With this in mind, the main questions to be answered are: “What form has the public space in the age of globalization?”, and more important, “How has the meaning of public space changed over time in China and Hong Kong?”

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2.2 Concept of PUBLIC space Fig. 2.6: Compression of the space -Poor Housing, Hong Kong Source: http://photomichaelwolf.com

PUBLIC SPACE AND GLOBALIZATION Capital flows and business expansions have played a significant role in changing and shaping the structure of contemporary cities, activating a process of compression and densification of the living space of inhabitants in the urban space.

Landmark office buildings, shopping malls, hotels and massive transport infrastructures took over large portions of the global cities, depriving city-users of concrete spaces of everyday life, both private and public, and pushing the phenomenon of urban densification without no-control.

This intense and fast urban growth has often generated examples of high density residential districts that are characterized by poor housing and lack of services and facilities, which are the result of a physical vertical compression of the space. Moreover, as a consequence of the massive densification of the cities, significant environmental problems, such as an increase of temperature and pollution or lack of urban ventilation, have been negatively affecting the quality of urban cityscapes and its people’s lives.

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In the East Asian metropolises, such as Hong Kong, Tokyo and Shanghai to name a few, the effect of globalization on the living environment has evolved at a faster pace and has caused extreme transformations in the last two or three decades with respect to that of Western global cities.

THE CONCEPT OF PUBLIC SPACE IN CHINA More than anywhere else, the Chinese public spaces are full of prohibitory signs and not everyone is allowed to enter. China is practically a one-party state with an authoritarian political system where the government exercises a strict control over the population. (Orum, 2009) As a result, the lack of adequate public spaces have driven Chinese people to use the urban space in a creative and intense way by transforming it according to their needs and their idea of public display. It is important to remember that streets have always been the main form of non-designed public space in

Chinese cities, being used for different purposes, including an extension of one’s own private home space. Streets can be seen as lively and chaotic containers for informal activities that have indirectly contributed to creating publicity in the urban space.

Indeed, “disorder” is a word that can define with a positive connotation the authentic essence of the Chinese everyday public space, meant as a creative mess that shapes narrow and crowded spaces. For example, it is crucial to take into consideration the value of traditional street markets in the Chinese culture in order to understand what public space means for Chinese people. Not only do outdoor markets add colour and energy to the street scene, but they also reflect the identity of local communities and their way of living socially. The purpose of street markets is not merely commercial, but also to provide the urban environment with diversity and thus encourage a social interaction, which has been repressed in other places.

2.2 Concept of PUBLIC space Fig. 2.7: Informal seating arrangements Source: http://photomichaelwolf.com

Fig. 2.8: Informal seating arrangements Source: http://photomichaelwolf.com

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2.2 Concept of PUBLIC space Fig 2.9: Alternative public space in Central Hong Kong, HSBC Bank’s square - Philippine immigrants enjoying their day-off Source: http://www.asianurbanepicenters. com

THE CASE OF HONG KONG In Hong Kong the form of the urban space has been quickly modified by the desire to achieve an international reputation and a cosmopolitan character similar to those of Western global cities, such as New York or London. A force of timespace compression has been activated in Hong Kong’s urban landscape, giving two version of the same city, respectively defined by a global capital accumulation and a local compression that collapse to accommodate urban densities.

As a result, this process has created a new social structure that is defined by striking social contradictions between international business people and a huge population of low-income people.

In addition, monumental vertical buildings have become an emblematic aspect of the economic success of Hong Kong, but they occupy a great portion of the available land and have gradually consumed the local identity of the place. As a consequence, this dual spatial and temporal

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compression has taken over the existing public space to make room for housing, and it has produced hyper-densities areas in which old communities are relegated to sandwiched and jam-packed spaces. (Huang, 2004) The lack of adequate public recreational areas encouraged the city-users to take over existing urban sites and transform them into self-made urban spaces for a series of social activities.

Pieces of cities are injected with new functions and redefined as an alternative public domain.

Especially during the weekend, empty streets and deserted plazas of private multinational companies in Hong Kong Island have over time become informal gathering places for lowincome workers, fulfilling the collective desire of public space in the contemporary city.

A significant example is the HSBC Bank, occupied by Philippine immigrant enjoying their day-off. The structured urban layout of the

financial district is attacked by a spontaneous and disordered self-expression of the public sphere, which provides the space with new programmatic usages and significance. Most of the social activities that are forbidden or reputed “undesirable” in the few official public spaces happen in this empty square on Sundays.

Here people meet and spend their spare time by sitting on straw mats, playing card games, hawking goods from home, and even getting haircuts and manicures. Lisa Law, an Australian researcher in Urban Studies, states in her article Defying Disappearance: Cosmopolitan Public Spaces in Hong Kong, that “Central is a ‘multicoded’ landscape where shoppers, tourists, office workers and migrant groups are ‘reading’ and ‘writing’ different languages in the built environment”.( 2) This means that not only is the concept of public space in Hong Kong linked to people’s cultural background, but it also changes according to the social differences. ____________________________ (2) Lisa Law, Defying Disappearance: Cosmopolitan Public Spaces in Hong Kong, Carfax Publishing, 2002, Urban Studies, Vol.39, No.9, pp.1625-1645

2.2 Concept of PUBLIC space

STREET MARKETS AND SHOPPING MALLS In Hong Kong the increased homogeneity of the urban space brought by the global culture has gradually diminished the authentic way of living the public space by the city-users. Some critics claim that Hong Kong’s citizens lost their interest in public space because of their hasty lifestyles and under the influence of the traditional Chinese culture, which did not allow people to gather publicly. On the other hand, others assert that before the British colonization, Hong Kongers had already associated the idea of public space to social interaction. For example, traditional markets (hui), ancestral temples (pinyin) and open areas in villages were all reputed important places for the day-to-day social life.

In fact, commercial streets and street markets have always been a significant form of public space for the local Hong Kongers, an example of their unique way of interacting socially and culturally. Today, most of these places have been slowly replaced by shopping malls, considered

an optimal solution to regenerate degraded parts of the city and develop the tourism industry at an international level.

Bearing this in mind, the question is: what is the new form of public space in Hong Kong?

The adoption of westernized customs and the deterioration of outdoor environmental conditions, due to the massive urban densification, caused the decline of the traditional public space and increased the demand for air conditioned indoor spaces, such as shopping malls. The diffusion of commercial centres in the city since the 1980s marked the beginning of the decline of the traditional and collective concept of public space. In the late nineties, the amount of public space per each Hong Kong’s inhabitant was only 1.5 square meter, and in some of the most densely populated district of the city, such as Mongkok, each resident has only 0.5 square meter of public space.

Fig 2.10: Apliu Street market, Sham Shui Po, Hong Kong Source: http://manfredgruber.net

Fig 2.11: Apliu Street market, Sham Shui Po, Hong Kong Source: http://hk-magazine.com

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2.2 Concept of PUBLIC space Fig.2.12: Yan On Building in Mong Kok (1965), Hong Kong - It is one of the earliest examples of shopping mall, a single corridor that create a public pedestrian thoroughfare.

Source: http://theprotocity.com

Although malls allow free access to users and house daily social activities, such as shopping and eating, they actually act as pseudo-public spaces because of their privatization and the restricted freedom to conduct a variety of activities. A curious aspect of this diffuse phenomenon is that the malls of Hong Kong are not simply spaces to go shopping, but they represent a point of public meeting and leisure walking for the community. Their internal layout of corridors and plazas, the thermal comfort and the wide range of facilities available emulate shape, characteristics and functions of the outer urban spaces that the real city cannot offer to its inhabitants. These buildings concentrate so many functions onto a small piece of land and differ from the North American counterparts, which are self-contained on the outskirts of the cities. Most of them are connected through public transport systems, enabling the user to walk indoors all the time.

In contrast, some people may argue that the government has provided the community with sufficient public space. There are a number of sizable recreational parks in Hong Kong, 38

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including Kowloon Park, Victoria Park, Hong Kong Park and the Hong Kong Zoological and Botanical Gardens. Despite the theoretical publicity of these place, in practise a wide range of social activities, such as bringing animals to the parks, riding bicycles, roller-skating, flying kites, bringing food to eat, running, walking on grass and lying on benches are prohibited. (Lo Ka Man, 2013)

2.2 Concept of PUBLIC space Fig.2.13: Kwun Tong Promenade, Hong Kong- Public space can encourage social interaction Source: http://www.hkpsi.org

A SUCCESSFUL MODEL OF PUBLIC SPACE IN HONG KONG As stated above, cultural, environmental and physical factors have a great influence on the perception that people have of public space. It is crucial to bear in mind that values of communities change and what that can be considered a successful example of urban space for a culture may not fit well in another place. For instance, Western cultures may like to be exposed to the sunlight in open spaces, but is this true in the East Asian context? Overall in Hong Kong, people, especially young women, may prefer to keep their skin white and spend their spare time in air-conditioned shopping malls, characterized by thermal comfort and cleaner air. These reasons make it easier to understand why the majority of the existing outdoor public spaces in the city are not able to attract local people.

As a consequence, the design of a public space should take into consideration what are the needs of the community and what external factors play a crucial role in distinguishing that specific context. Now, it can be deduced that

in Hong Kong an attractive and well-designed open public space should provide its users with comfortable temperatures, shaded areas and various range of activities for different age groups. It is necessary to think about how people would use a space that can fully belong to Hong Kong’s context.

To conclude, it can be supposed that in the congested and hyper-dense Hong Kong a network of pocket, vibrant and equally distributed open spaces could probably enhance the global quality of the urban environment, rather than localized big public spaces.

A successful model of new public space in Hong Kong is represented by the Kwun Tong Promenade, situated at the Eastern part of the Kowloon Peninsula. It opened in 2010 on an industrial stretch of waterfront facing the runway of the old Kai Tak Airport, and is 200 metres long, but the plan is to continue expanding it. Water vapour is released from vents inside the boardwalk of the multi-purpose plaza, offering visitors a refreshing way to cool down, especially in summertime. This space is defined by a mixture of green and water and it contains a series of new recreational facilities that stimulate people to spend time outdoors.

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2.2 Concept of PUBLIC space

HONG KONG STANDARDS FOR PROVISION OF OPEN SPACES In the urban areas, including the Metro Area and the New Towns, the standard for provision of open space is a minimum of 2m2 per person, apportioned as follows: (a) a minimum of 1m2 per person for District Open Space (b) a minimum of 1m2 per person for Local Open Space

Local Open space Local open spaces are smaller sites (where possible at least 500m2 in the urban areas) which are more passive in nature and provide sittingout areas and children's playgrounds to serve the neighbourhood population. For local open space serving a larger neighbourhood, some active recreation facilities may be provided. (3)

District Open space District open spaces are medium-size sites (where possible at least 1 ha) which provide facilities for core activities and for passive recreation to meet the needs of a district population.

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Source: http://photomichaelwolf.com

Fig. 2.15: Hong Kong Flora -People’s imaginative way of integrating nature with the city Source: http://photomichaelwolf.com

____________________________ (3) http://www.hkpsi.org/eng/publicspace

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Fig. 2.14: Hong Kong Flora Maximazation of private space by creating a natural environment on the facades of houses

2.2 Concept of PUBLIC space Fig. 2.16: Diagrams, Typology of spaces

Open Space

Public Space

Semi-public Space

Semi-private Space

Private Space

DEFINITIONS OPEN SPACE

SEMI-PUBLIC SPACE

SEMI-PRIVATE SPACE

Meaning any land with the minimum of building structure which has been reserved for either passive or active recreation and provides major or minor recreational facilities, which may be of local or district significance, which is for the use and enjoyment of the general public. This includes parks and gardens, playground/playing fields, promenades, pavilions, sitting out areas, pedestrian areas and bathing beaches. (3)

The term "semi-public space" refers to places that appear to be public spaces but they are in fact privatized spaces. Despite a lot of social interactions and even public life are going on in these pseudo-public space, they are not truly public spaces as they do not always fulfil one fundamental spirit of public space, that the entry be free for everyone. (3)

It is defined as a space that is access controlled and accessible to residents and associated people only. These spaces are not really private since they’re shared, but because they’re usually inaccessible to outsiders, they’re not really public either.

PUBLIC SPACE

PRIVATE SPACE

It can be defined as an area where everyone, regardless of his or her background, can enter without pre-requisite, such as an entry fee.

Typical examples include public squares, parks, streets, public libraries, street markets, and country parks, etc. (3)

It is defined as a space which is owned by particular groups or individuals but not the community, and is meant for private use. The entry of certain people can theoretically be restricted by their owners. (4)

____________________________ (3) http://www.hkpsi.org/eng/publicspace (4) http://waua.wordpress.com/tag/semi-private-space

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2.3 Environmental problems in dense urban tissues

Podium Building Morphologies Urban Wind Environment affected by:

Large Podium structures:

Summer:

- buildings Site Coverage

- Lower permeability

- buildings Layout and Orientation

- Air flow impeded at pedestrian level

- buildings Heights

- Air volume minimized at pedestrian level

wall effect

- a decrease in wind speed of 1.0 to 0.3 m/s = an increase in T= 1.9 ํC

55 m

20 m

55 m 20 m

15 m

Stagnant air

Urban street canyons

15 m

Wind profile

50 m

15 m

60 m

Urban Canopy Layer H average Buildings

H Podium layer

Fig.2.17: Environmental conditions. Urban ventilation

The built environment is not just the collection of buildings; it is also the physical result of various economic, social and environmental processes, which are strongly related to the standards and needs of society. Cities are integrated systems that facilitate the delivery of a wide range of services and activities. Synergies among these elements generate stress in the built environment. (Santamouris, 2001).

Indeed, not only has the rapid development of cities increased enormously the population’s density, but it has brought about a lot of negative effects on the global environmental quality, 42

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such as heat stress, worsening of air quality and acoustic pollution, to name a few. It seems clear that the relationship between climate change and the urban system is extremely important to understand causes, effects and solutions for the main environmental issues that negatively affect the quality of life in our cities.

The urban environment has been modified by the process of urbanization and industrialization, causing an increase in the number of buildings at the expenses of open spaces and greenery.

As a consequence, today the majority of high density cities are characterized by a change in

the heat balance with respect to the surrounding non-urbanized areas, called “Urban Heat Island Effect”.

Definition of UHI Effect

Causes of UHI Phenomenon

"warm island" among the "cool sea" represented by the lower temperature of the non-urbanized surroundings” (Perez Arrau C., 2011) Definition UHIinEffect Mean UHII ByofTPU hot seasons ( June - September, 2001-2009).

Urban Heat blocked by Causes of UHI Phenomenon buildings

“It isUHII defined in temperature of any2001-2009) man-made area, resulting in a well-defined, distinct Mean

by TPUasinthe hot rise seasons (June-September,

- Urban canyons: narrow arrangement of buildings

2.3 Environmental problems in dense urban tissues - Urban canyons: narrow arrangement of buildings “It is defined as the rise in temperature of any man-made area, resulting in a well-defined, distinct

"warm island" among the "cool sea" represented by the lower temperature of the non-urbanized High: 7.5 T > 28 ํC - Wind speed = 11 km/h (Perez Arrau C., 2011) surroundings” Medium: 3.67 Low: 1.35 T < 28 ํC - Wind speed = 33.6 km/h

Mean UHII by TPU in hot seasons (June-September, 2001-2009)

New Territories

High: 7.5 T > 28 C ํ - Wind speed = 11 km/h Medium: 3.67 Low: 1.35 T < 28 C ํ - Wind speed = 33.6 km/h

- Decrease of vegetated areas and low wind velocity x

low wind strong wind New Territories

Kowloon Hong Kong Island Lantau Island Kowloon Island HongLamma Kong Island Lantau Island

Mean Urban Heat Island Index (UHII) for Tertiary Planning Units in Hong Kong (2012)

x

Urban Heat blocked by buildings

33 ํC

30 areas ํC evaporation - Decrease of vegetated and low wind velocity low wind strong wind

33 ํC

evaporation

30 ํC

Rural area

Urban area

- Buildings material with low reflectivity daytime

night time Rural area

Urban area

- Buildings material with low reflectivity daytime incident radation is absorbed

night time

Lamma Island

Fig.2.18: Mean UHII By TPU in hot seasons ( June - September, 2001-2009)

incident radation is absorbed

Mean Urban Heat Island Index (UHII) for Tertiary Planning Units in Hong Kong (2012)

Source: Mean Urban Island Index (UHII) for Tertiary Planning Units in Hong kong, 2012

Fig.2.19: Causes of UHI Phenomenon

URBAN HEAT ISLAND EFFECT (UHI) sides by very tall buildings, usually skyscrapers.

The height and the narrow arrangement of buildings creates a “wall effect” that blocks the urban air flow, especially at the street level, and they also reduce the sky view factor.

and roads, lower the amount of water sources and limits the dispersion of the heat through the process of evapotranspiration. As a result, there is an increase of air temperature on the buildings’ surfaces and in the atmosphere.

CAUSES:

- Building materials, such as concrete, bricks, asphalt, etc., have non-reflective and water resistant properties. They absorb and store a great quantity of incident radiation during the day, and slowly release it as heat at night.

- “Urban street canyons”, defined as places where a narrow street is surrounded on both

- Decrease of vegetation areas and high surface covers, such as parking areas, buildings plots

- Human activities also release large quantities of waste heat in the air due to air-conditioning and refrigeration systems, vehicular traffic, industrial processes, etc. A direct consequence of this phenomenon is also the production of air pollutants and dust that create the well-known “Dust dome effect”, keeping the heat in the lower layers of the atmosphere.

According to Sue Grimmond, a world leading expert on urban climates at Kings College London, the “Urban Heat Island Effect (UHI)” is a phenomenon whereby temperatures tend to be warmer in urban than surrounding rural areas, particularly when it is calm, clear and at night.

On average in cities temperatures are one to three degrees centigrade warmer, but on occasions may be as much as 10 C warmer.

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2.3 Environmental problems in dense urban tissues Case Study: main solutions

Negative Effects of UHI Phenomenon

(1) SHANGHAI and SINGAPORE - Impact on Human comfort

Uncomfortable Warm Environment

- Spread of diseases

- Skyrise Greenery Incentive Scheme Evaporation

Evaporation Cooling effect

Green Facades

Green-roofs

- Mortality

Dust Dome Effect

- Air pollution

(2) STUTTGART, GERMANY

Increase Use of Air-conditioning

- High Electricity Consumption - Increase Greenhouse Effect

- Green Aeration corridors Natural wind patterns Air-flow exchange

Data for UHI in Hong Kong (2012)

T cooling effect

from Location 1

Increase of Temperature

to Location 2

urban margins

between 2 and 6 �C /every km

city centre

(3) MELBOURNE

urban green areas

between 2 to 3.2 �C

hottest urban spots

- Urban Wetlands

urban channels

between 2.3 to 3.5 �C

hottest urban spots

Better Air quality

Water in the urban environment

Evaporation

Evapotranspiration reduction of daily heat stress

IMPACTS: - Health and welfare of inhabitants can be seriously compromised by the thermal discomfort due to high temperatures, causing physiological disruption and diseases, such as heat syncope and heat stroke, which in some cases can be fatal.

- Increased Energy Consumption for cooling (i.e. refrigeration and air-conditioning) indoor spaces intensifies the emission of greenhouse gases and other pollutants, such as sulphur dioxide and carbon monoxide, into the atmosphere, and 44

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consequently it leads to higher levels of air pollution. Moreover, an increase in the energy demand could raise the prices for inhabitants and governments.

- Water quality can be compromised by storm water, heated by the high temperatures of urban surfaces. This heated storm water may become runoff and drain into storm sewers, increasing water temperatures and modifying aquatic ecosystems fatally.

Fig.2.20: Effects UHI Phenomenon Source: http://www.ncbi.nlm.nih.gov/ pubmed/23007798.

2.3 Environmental problems in dense urban tissues Fig.2.21: Greenery rooftop, Nanyang, Technological University.

Source: http://greencompanyeffect.com Fig.2.22: Vertical greenery rooftop, La Caixa Forum, Madrid.

Source: http://upload.wikimedia.org Fig.2.23: Urban Wetland, Stormwater-wetland, Perth.

Source: http://www.aila.org.au

UHI EFFECT: â&#x20AC;&#x153;COOLING STRATEGIESâ&#x20AC;?

Strategies for mitigating the UHI Effect are related to specific local factors, such as topography, climate conditions, geography, but they also depend on land-use patterns in the urban landscape. In general, the main solutions adopted to reduce the UHI Effect in high density cities concern: - the Increase of vegetation cover, in the form of open green areas, green roofs and green walls, which can give benefits in absorbing humidity, decreasing air temperatures through evapotranspiration, and reducing the energy used to cool buildings.

- the Increase of urban surfaces reflectivity which reduces the absorption of solar radiation - the Integration with Urban Wetlands which can give benefits in terms of cooling and regulating urban microclimates through evaporation from water surfaces and moist soil.

- the Improvement of Urban Air Flow which reduces temperatures and stops the formation

of stagnant air between buildings arrangement.

DEFINITIONS - Green roofs are planted roofs whose vegetation keeps the temperature of surfaces cooler and provides a space for urban agriculture and outdoor community gardens.

- Urban Wetlands are defined as pieces of land, permanently or seasonally saturated with water, which are characterized by hydric soil and specific vegetation, such as aquatic plants. They can exist naturally or be constructed artificially as a water management tool in urban areas.

- Vertical Greening consists of self-sufficient vertical gardens joined to the buildings envelope or interior walls. These elements can shade sides of buildings that get direct sunlight.

- Cool Surfaces, which include cool roofs and pavements, are characterized by highly reflective materials (i.e. high albedo) and light colours/white paint. These reflective surfaces can reduce heat gain, whereas materials of high thermal conductivity, such as concrete and bricks, absorb and store a great amount of solar radiation during the day and then release it in form of heat at night.

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2.3 Environmental problems in dense urban tissues

UHI EFFECT IN HONG KONG The densely populated urban area of Hong Kong provides a typical example of the UHI effect, which shows an increase of temperature from urban areas to rural surroundings between 2 and 6 Celsius degree every kilometre. In addition, there is a difference of temperature from 2 to 3.2 Celsius degree between urban green areas and the hottest urban spots. It is clear that in Hong Kong the city centre is significantly warmer than its urban margins, mainly due to the impact of the massive urbanization.

The Department of Land Surveying and GeoInformatics of The Hong Kong Polytechnic University reported that the temperatures in the inner urban areas of Hong Kong are expected to rise by two to three Celsius degree in 30 years’ time. This means that during summer days the average temperature in urban districts will increase from currently 35 Celsius degrees to 38 Celsius degrees in 2039. This latest study, carried on by Professor Janet Nichol, was based on satellite images for mapping the distribution of air temperature over Hong Kong, and estimating the impact of the urbanization over time by quantifying the plot ratio. As a result, the mean temperature is predicted to rise by 3.7 to 6.8 Celsius degree by 2100, taking into account a constant urbanization rate. This means that UHI magnitude is estimated at 0.08 Celsius degrees per decade. (University, 2012).

shape of the built environment enormously influence the characteristics of urban air flow, such as wind speed, pressure and patterns.

Considering Hong Kong as case study, it has been demonstrated that building morphologies and narrow street arrangement significantly affect the local air ventilation, and several studies have been carried on the city’s urban tissue using computational fluid dynamics analyses (CFD). The Hong Kong Environmental Protection Department recently reported that the mean wind speeds recorded in the city over the last 10 years have decreased by 40%.

BUILDING MORPHOLOGIES In Hong Kong’s urban area the decrease of the overall urban airflow is mainly caused by the presence of tall and overly large highrise buildings, characterized by compactness, uniform height and typical podium structures with large ground coverage. This low permeability of the urban tissue impedes proper air circulation and worsens its quality.

Although the height of buildings is a critical factor in blocking urban ventilation, many researchers reported that airflow is more sensitive to the density, and that high percentages of site coverage have more impact than buildings height on the pedestrian wind environment.

LACK OF URBAN VENTILATION

URBAN STREET CANYONS

The Urban heat Island (UHI) phenomenon is strictly related to city ventilation, because lowlevels of airflow produce stagnant air in outdoor urban spaces, increasing temperatures and causing thermal discomfort. Air ventilation is a crucial factor to ensure good air quality in the urban fabric because it allows pollution to disperse and temperatures to fall), especially in highly dense subtropical cities. Many researchers agree that spatial distribution and

Some experts claim that even though Hong Kong, as a coastal city, has a considerable wind potential in the urban atmosphere boundary layer, the alignment of tall and compact buildings and their aggregation in clusters create a “wall effect”, blocking the natural ventilation and worsening the outdoor thermal comfort. Taking into account the Physiologically Equivalent Temperature (PET) thermal comfort as a standard, wind speed decreasing from 1.0 to 0.3

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m/s is equal to 1.9 ºC air temperature increase in the subtropical summer. An outdoor thermal comfort under typical summer conditions requires 1.6 m/s wind speed.(Chao Yuan, 2013) Moreover, it has been shown that in Hong Kong the streets design (i.e. geometry, orientation and configuration) can reduce significantly the effectiveness of the urban air flow because of the formation of urban street canyons that trap stagnant air at pedestrian level. An urban street canyon can be considered as the space formed between two typically parallel rows of buildings separated by a narrow street. (Shishegar, 2013) The geometry of a street canyon is expressed by its “aspect ratio” which is the ratio of the Height of the building (H) to the Width of the street (W).

A canyon can be defined as: Uniform

with

Aspect ratio= 1

Shallow

with

Aspect ratio < 0,5

Deep

with

Aspect ratio= 2

An additional classification depends on the ratio between Length of canyon (L= road distance between two main intersections) and Height of the building (H), subdividing the canyon in: Short Medium Long

with L/H=3 with L/H=5 with L/H=7

2.3 Environmental problems in dense urban tissues

PROPOSED VENTILATION STRATEGIES FOR HONG KONG Currently, there are no adopted solutions for improving urban ventilation in the urban area of Hong Kong, but the government has introduced several ventilation parameters in the official urban design guidelines. Moreover, many researchers from the Chinese University of Hong Kong have carried on studies about how to enhance urban ventilation in the city, providing a series of possible solutions listed below.

1) Increasing the overall Permeability of the urban tissue, especially at ground level, is important in order to create breezeways and air paths. This could be possible by: - linking open spaces - creating open spaces at road junctions - maintaining low-rise buildings along prevailing wind direction routes - widening minor roads connected to major roads 2) Increasing Buildings Permeability, especially at pedestrian level, could be possible through a system of voids and openings in the buildings (4) .The combination of a porosity system with appropriate wing walls helps create a difference of pressure across buildings facades, and thus it facilitates indoor airflow through openings. In the case of very deep urban street canyons or very tall buildings, a mid-level permeability is crucial to improve air ventilation performance at mid-floors.

arrangement, improving air circulation at higher levels. In addition, it also contributes to increase the sky view factor.

5) Street Grid Orientation should be designed by arranging main streets along prevailing wind directions.

6) Buildings Disposition and Orientation should be parallel to the prevailing wind direction in order to avoid obstructions. Furthermore, the planning layout should provide buildings with adequate gaps and open spaces.

7) Building Height is an important factor that affects wind speed. Creating a Gradation of Height profiles toward the windâ&#x20AC;&#x2122;s direction helps to improve ventilation. When it is not possible to create a height gradient, varying the buildings height helps to divert winds to the lower level.

8) Surfaces Roughness creates an aerodynamic effect at rooftop level that helps increase the overall wind speed.

9) Increasing the amount of greenery could help improving the effect of air stagnation.

3) Reducing the Site Coverage Ratio could help enhance the pedestrian-level natural ventilation performance. It has been demonstrated that splitting the volume of podiums into several parts helps air to circulate better at street level.

4) Creating Setbacks by stepping back buildings height in rows widens the narrow blocks ____________________________ (4) Wing walls can be defined as vertical solid panels placed alongside of openings and perpendicular to the wall on the windward side of the building.

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2.3 Environmental problems in dense urban tissues Fig.2.24: Vertical cross sections showing the velocity contour and streamlines for horizontal and vertical setbacks Source: â&#x20AC;&#x153;A modeling investigation of the impact of street and building configurations on personal air pollutant exposure in isolated deep urban canyonsâ&#x20AC;?, Wai-Yin Ng, Chin Kwan Chau, 2013

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2.4 Case study

Fig.2.25: Vertical Horizon, Hong Kong Source: http://www.rjl-art.com/index.php.

During the last century, high-density cities around the world have shaped a skyline based on high-rise buildings driven by one main goal: to accommodate a large amount of population.

In Asia, some examples of public housing proposals reveal the lack of cultural, spatial and environmental considerations in the design proposal. These multi-storey buildings bring further effects to the urban fabric, affecting environmental conditions and disrupting any dynamic between the population and the built out of the city.

Recently more awareness regarding these conditions has influenced some architectural offices to have a different approach towards the high density skyscraper model, in which they consider the inclusion of open areas at several levels; these spaces are considered communal and semi-private for social interaction, in order to balance the lack of open areas in the urban fabric. These proposals face further challenges such as the mobility of the population to use the open spaces provided, and also a clear relation of interaction between the private and the public.

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2.4 Case study

Fig.2.26: Case study 1- Proposal for a high rise mixed-use tower, MahaNakhon Tower, Bangkok, Thailand (by OMA, 2012)

Fig.2.27: Case study 2Residential Developments, The Interlace, Singapore (by OMA, 2013)

Source: http://phamngochuong.com.vn

Source: http://arch2o.com/wp-content

HIGH DENSITY BUILDING BLOCKS Highlight: high density, private space, semipublic space, greenery, flexibility, mixed use MahaNakhon Tower by OMA, Bangkok - Thailand, 2012

The Interlace by OMA and Ole Scheeren, Singapore, 2013

Sky village by MVRDV, Copenhagen â&#x20AC;&#x201C; Denmark, 2008

Mixed-use development with apartments, retail, five-star Ian Schrager hotel and public gardens a tall tower of 77 stories that seeks to communicate intimately with Bangkok from the ground up: its series of components comprise MahaNakhon Square, a landscaped outdoor public plaza intended as a new public destination within the city; MahaNakhon Terraces, 10,000 square meters of gardens and terraces spread over multiple levels for restaurants, cafes and a 24 hour marketplace.

This complex of 31 apartment blocks, each 6 stories tall, is based on the idea of horizontally interconnected volumes, forming a less isolated residential environment. An integrated network of private and communal spaces, such as terraced gardens and courtyards, arise from the stepped morphologies on multiple levels, allowing light and air to penetrate into and through the surrounding environment.

This 116 meter tall tower is mixed use and it includes apartments, a hotel, retail, offices, and a public park and plaza. The building is composed of an aggregation of pixelated units that allows flexibility in function and integrates greenery built through a series of terraced sky gardens.

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2.4 Case study Fig.2.28: Case study 3- Proposal for a high rise mixed-use tower, Sky Village, Rødovre, Denmark (by MVRDV, 2008) Source: http://www.mvrdv.nl

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2.4 Case study Fig.2.29: Case study 4- Proposal for a high rise mixed-use tower, Sky Village, Rødovre, Denmark (by MVRDV, 2008) Source: http://www.mvrdv.nl

PEDESTRIAN CONNECTIVITY Highlight: greenery, public space, elevated pedestrian connectivity High Line Park by James Corner Field Operations, Diller Scofidio+ Renfro, New York - USA, 2006 This project is focussed on the redevelopment of a disused railroad in New York, which is constituted by a 1.45 mile-long elevated steel structure. Its transformation into a public elevated park aimed to offer an alluring break from the chaotic city 52

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streets for users, who can enjoy the viewing area and lounge on the open lawn and seating steps. Indeed, this public space is conceived as multifunctional, offering a variety of cultural attractions and community programming as well as informal recreation, thanks to the integration with vegetation. The system of walkways, which structure this hanging urban park enhances the pedestrian connectivity across the district, offering unexpected views of the Hudson River and the surrounding cityscape.

2.4 Case study Fig.2.30: Case study 5- Proposal for a high rise mixed-use tower, Sky Village, Rødovre, Denmark (by MVRDV, 2008) Source: http://www.mvrdv.nl

VERTICAL GREENERY Highlight: vertical park, permeability, public space, multi-functionality MFO Park by Burckhardt + Partner and Raderschall, Zurich - Switzerland, 2002 The MFO Park, measuring 100 meters long, 34 meters wide and 18 meters high, is the largest pergola in the world. The design of this multilevel “park house” covers an area of 96,875 ft² and it is constituted by a double-walled construction, made of metallic trellis and open on 3 sides. The

whole structure is permeable and transparent, and it is covered with plants and traversed by walkways. Loggias and small silent gardens are located on different levels. This public space accommodates a variety of activities, such as open-air movies, concerts and theatres, or simply offers users the opportunity for gathering and informal recreation.

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3. methods 3.1 Process Overview 3.2 Computational Techniques 3.3 Multi-software Data Transferring 3.4 Associative Techniques

SITE ANALYSIS

CFD

DESIGN LOGIC and PARAMETERS

EXISTING CONDITIONS

GENETIC

RESEARCH CASE STUDY ENVIRONMENTAL - Low Wind Speed - High Temperature

SOCIAL

- Land Use - Buildings Morphologies

AIRFLOW STRATEGIES

SPATIAL QUALITY

(Height, Rooftop villages)

CRITICAL AREAS

Fig.3.1: Overall Diagram, Methods

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DESIGN AMBITIONS

Patch scale

P

Blocks Aggregations scale

Block

PRIMITIVE INPUT

COM

GIC

ERS

e

3.1 PROCESS OVERVIEW CFD ANALYSIS

GENETIC ALGORITHM

SOLAR ANALYSIS Patch scale

MATERIALITY PEDESTRIAN ANALYSIS

ations

Blocks Aggregations scale

VE

COMPUTATIONAL OUTPUT

ARCHITECTURAL QUALITY

This chapter illustrates the different methods that will be employed in the various phases of the process to describe the logic system on which the thesis is based. Research, analysis, design procedures and evaluation modes will be driven by principles of sustainability for a highdensity city model and digital tools and noncomputational approaches will focus especially on buildingsâ&#x20AC;&#x2122; morphological aspects, in terms of environmental and architectural quality at different scales. The interdependence of analytic and design methods will be used to calibrate the parameters for the several experiments and to understand success and limitations of the entire process.

The computational design of cities is a scientific and innovative way of approaching contemporary urban systems. This is coupled with transformations and growth in high density scenarios. This approach requires a simultaneous processing of large quantity of data, successively translated into precise design solutions. In each stage, the thesis adopts the combination of spatial logics, environmental responsiveness and social and cultural factors to inform a challenging urban system, with the aim to extract parameters for a design strategy that can achieve an overall urban quality.

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3.2 COMPUTATIONAL TECHNIQUES

Fig.3.2: Genetic Algorithm Definition, GH for Rhinoceros v5

GENETIC ALGORITHM The development of evolutionary algorithms starts with an understanding of the two different but coupled processes that lead to the morphogenesis, variation and distribution of all living forms. Every living form is generated by two strongly joined processes, throughout differentiated time spans: the rapid process of embryological development, and the long slow process of the evolution of diverse species of forms over multiple generations” (Michael Weinstock, 2010).

Genetic Algorithms (GA) are adaptive heuristic evolutionary ideas of natural selection and genetics. The basic concept of GA is to simulate evolutionary processes that occur in nature, specifically those that follow the principles of survival of the fittest. As such they represent

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an intelligent exploitation of a random search for finding solutions to an optimization problem that takes advantage of evolutionary principles; different possible solutions to the problem are iteratively subjected to “replication”, “mutation” and “selection” processes. (Wilfred Ndifon, 2011). The entire process usually starts with the initiation of a random population of candidate forms, from which those that best match the desired criteria, the “fittest” individuals, are selected. Genetic algorithms combine both growth and evolution over multiple generations.

(Michael Weinstock, 2010).

The application of GA to architectural forms aims to explore innovative context-sensitive design solutions and develop a logical and thoughtprovoking way of reimagining contemporary

architecture, building a bridge between scientific and sociological paradigms. In this light, during the thesis the urban system has been developed through an evolutionary computational design process that employed Grasshopper (GH) for Rhino within Octopus’s evolutionary solver as main generative platform.This form generative method has been structured on a multi-objective optimization, which has led to a multiple set of different design solutions. With respect to single objective GA, the adopted approach allowed evaluating many morphological options simultaneously and according to a series of different fitness criteria, taking in consideration both environmental and cultural factor for the design strategy.

3.2 COMPUTATIONAL TECHNIQUES

V

V

GE

GE

SE

SE

GE

G1.01

G1.02

G1.03

G1.04

G1.05

G5.01

G5.02

G5.03

G5.04

G5.05

G8.01

G8.02

G1.06

G1.07

G1.08

G1.09

G1.10

G5.06

G5.07

G5.08

G5.09

G5.10

G8..06

G8.07

V

V

Fig.3.3: Numeric Domain

Fig.3.4: Ranking criteria

GE

SE

GE

REMAPPING PARAMETERS

DIFFERENTIAL WEIGHTING

The parameters used in the system will be characterized by different numeric domains and thus to compare these values it will be necessary to remap them into standard domain ranges.

A variety of techniques will be employed to transform this data into similar numeric values.

This is an important step that allows evaluating and comparing the results of the generative process.

Differential weighting criteria will be used when the parameters cannot be computed together.

Due to the lack of computational connection between the GA and the computational fluid dynamics (CFD) evaluation, it will be necessary to identify which parameters have higher priority.

It is important to be aware that even though the two of the main goals of the thesis are improving urban airflow and minimizing disruption both ambitions could become contradictory because maximizing the built volume could result in a decrease in wind speed. Therefore, a differential weighting of fitness criteria is a key factor for the selection of specific morphologies generated in the design process. The adopted weighting technique will be based on a comparison between evolutionary computational outputs and results of the CFD analysis, in order to establish

SE

GE

G11.01

G11.02

G11.03

G11.04

G11.05

G14.01

G14.02

G14.03

G14.04

G14.05

G11.06

G11.07

G11.08

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G11.10

G14.06

G14.07

G14.08

G14.09

G14.10

G19.01

G19.02

G19.06

G19.07

as selective criterion, the best optimum value between maximum volume and maximum wind performance. This could provide a control over the outcomes of the entire design process.

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3.3 MULTI-SOFTWARE DATA TRANSFERRING Although the GA is able to optimize existing buildings morphologies, according to the fitness criteria of maximum volume, minimum summer solar exposure and minimum ground exposure, there is a disconnection between the generative process and other parameters. As a consequence, analyses on specific environmental conditions, such as wind performance and spatial layouts, such as pedestrian connectivity, required the use of specific simulation software, due to the inability of the GA to provide direct design solutions for these conditions. For example, the CFD evaluated the performance of the experiments for wind ventilation, while the pedestrian circulation at the ground level has been analyzed with Depth map.

SOLAR RADIATION ANALYSIS A solar radiation analysis of the emergent open spaces has been used to verify the quality of the outdoor environmental conditions. Incident solar radiation is measured as the energy received on surfaces during a selected period of time.

The calculation of this parameter is based on hourly readings during the hottest period in Hong Kong, estimated to be between June and September. According to the analyses, we evaluated the characteristics of the microclimate of the emergent open spaces and translated the values of solar radiation into temperatures. This allowed functions to be assigned to different spaces in relation to the human thermal comfort.

Ladybug plug-in for GH has been used to run this analysis.

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Fig.3.5: Multi-Software Data Transferring

Fig.3.6: Ladybug for GH, Solar Radiation Analysis Source: https://aec-apps.com

GRASSHOPPER

VASARI CFD

LADYBUG

SPATIAL QUALITY

3.3 MULTI-SOFTWARE DATA TRANSFERRING COMPUTATIONAL FLUID DYNAMIC ANALYIS Computational fluid dynamics is used for solving and analyzing problems related to fluid flows.

It uses numbers and algorithms to compute the results (Chao Yuan, 2011). One of the ambitions of the experiments is to maximize urban ventilation and increase airflow at the different height levels in the patch. In this light, CFD becomes an important tool for flow simulation because it allows extracting numeric and visual data about wind speed in relation to the morphology of buildings. Vasari CFD analytic software has been employed to evaluate the computational evolutionary outputs that perform better for the urban ventilation. The interdependence and exchange of information between the wind simulation and computational design tools has been crucial to the entire design process, due to the issue that the genetic algorithm does not provide Rhino and Grasshopper with a simultaneous feedback analysis for the wind optimization.

Fig.3.7: Example of CFD Analysis (Streamlines) Source: http://wildeanalysis.co.uk

DEPTH MAP

Fig.3.8: Pedestrian Analysis

UCL Depth map is an Open Source application to perform visibility analysis of architectural and urban systems. It takes input in the form of a plan of the system, and is able to construct a map of ‘visually integrated’ locations within it. (1) The Agent analysis tools in the 2D view window (Map window) are used to generate aggregate models of agents’ movement in space. These aggregate models are governed by global parameters as well as parameters defining the behaviour of individual agents. The global parameters determine the duration of analysis, when, where and how many agents are released into the system (Alasdair Turner, 2012).

Source: clementcreusot.com

This analytic tool was used to evaluate the pedestrian circulation at the ground level in the existing and optimized urban patch, to evaluate the effect of the porosity strategy and the level of fluid circulation achieved with respect to the original condition. ___________________________ (1) http://www.spacesyntax.net/software/ucl-depthmap/

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3.4 ASSOCIATIVE TECHNIQUES Evolutionary strategies have been applied to existing morphologies to explore multiple solutions for specific and context-sensitive architectural forms within their effects on the areas nearby. However, another noncomputational parameter, such as materiality related to the environmental and architectural quality of the space, can be considered as a significant factor in the computational process for creating a responsive urban tissue.

Fig.3.9: Behaviour of materials with High and Low Albedo

100%

100% 80%

HIGH ALBEDO

10%

LOW ALBEDO

Incoming Incident Radiation Outgoing Reflective Radiation

SURFACES MATERIALITY The main driver of the experiments is to provide a comfortable outdoor environment in a highdensity city, negatively affected by the Urban Heat Island effect and low ventilation. The optimized morphologies could contribute to reduce outdoor and indoor high temperatures and absorb humidity and pollutants through the materiality of their envelope. For example, vegetation covers could lead to the reduction of excess moisture and air pollution, while material surfaces with a high albedo coefficient would be capable of reflecting the incident solar radiation.

Albedo is a measure of the amount of light that is reflected from a surface without being absorbed.

From the solar radiation analysis, it can be deduced which materials could be applied to the envelope of buildings in order to reduce high temperatures in the hottest months through their reflective properties.

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Fig.3.10: Materials Reflectance Spettra Source: http://www.astro.washington.edu

ALBEDO

no light reflected

all light reflected

4. Selected patch 4.1 Site Analysis 4.2 Rooftop villages 4.3 Analysis of Existing Urban ventilation 4.4 Conclusion

Fig 4.1: Shamp Shui Po district Source: http://photo.sf.co.ua/id75?lang=ru

4.1 Site Analysis Density Density Density

GeneralData Data General

Location Location Location

ShuiPoPoDistrict District Sham ShamShui SelectedPatch Patch Selected Yau Tsim Mong District Yau Tsim Mong District

LandArea Area - -Land General 1,73km² km² Data 1,73

km² km²

Kowloon Peninsula Kowloon Peninsula Sham Shui Po District Selected Patch Yau Tsim Mong District

- Land Area TotalPopulation Population - -Total 1,73 km² 203.094inhabitants inhabitants 203.094

km²

Kowloon Peninsula HongKong KongIsland Island Hong

NN Hong Kong Island

N

BuildingTypologies Typologiesininthe thePatch Patch Building

HighDensity Densityand andPoorest PoorestArea Area High windflow flow wind

High Density and >T Poorest Area >T

walleffect effect wall wind flow wall effect

xx >T

x

NarrowStreet StreetArrangements Arrangements - - Narrow FormationofofUrban Urbanstreet streetcanyons canyonsthat thatblock block - -Formation urbanair airflow flow urban - Narrow Street Arrangements - Formation of Urban street canyons that block urban air flow

Blocks Tower in the Towers andBlocks Blockswith withPodium Podium Blocks Tower Towers Building Typologies Patchand Blocks Tower

Towers and Blocks with Podium

- Total Population PopulationDensity Density - -Population 203.094 inhabitants 117.395inhab/ inhab/km² km² 117.395 - Population Density 117.395 km²Public Lackinhab/ Open PublicSpaces Spaces Lack ofofOpen

IllegalHousing Housing--Rooftop RooftopVillages Villages Illegal

Lack of Open Public Spaces

Illegal Housing - Rooftop Villages

2020mm

20 m

Podiumstructures structureshouse houseservices servicesand and - - Podium commercialactivities activities commercial - Podium structures house services and commercial activities

Temporaryand andinformal informalrooftop rooftopstructures structures - -Temporary Concrete,bricks, bricks,wood, wood,flimsy flimsymaterial material - -Concrete, Dwellings’area= area=from from99toto28 28sq. sq.

- -Dwellings’ - Temporary and informal rooftop structures - Concrete, bricks, wood, flimsy material - Dwellings’ area= from 9 to 28 sq.

Fig 4.2: Patch's general aspects, architectural and environmental conditions

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4.1 Site Analysis

The experiments will be carried out in an area of 1.7 kilometres between two of the most vulnerable districts of Hong Kong: Sham Shui Po and Yau Tsim Mong. The first is characterised by an industrial and commercial background and the other is considered a shopping and business centre. With a population of 203,094 inhabitants and a density of 117,395 inhabitants per square kilometre, the area has one of the highest peaks of density and urban heat island effect intensity.

The urbanisation of the Kowloon Peninsula is clearly evident in the physical fabric of Sham Shui Po. During the 1980s, large tracts of land were reclaimed for the construction of highways, railways and housing developments. The centre of Sham Shui Po shifted inland, defining differences between the old Hong Kong and the new enterprising waterfront characterised by new large-scale developments.

The path landscape is one of the most controversial aspects of the city: a height gradient throughout the patch, where the east coast is filled by important high-rise financial and housing towers as part of the infrastructural 68

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renewal of the Kowloon Peninsula. On the west coast, the area is filled by old shop houses that vary between seven and 10 storeys high; these buildings host a mix of purposes and include offices, shopping centres, street markets, a secondary pedestrian network, housing, and rooftop villages, creating vibrant patterns of interaction between the two districts. (Fig.4.2)

Fig.4.3: High-rise buildings Shophouses, Sham Shui Po district, Hong Kong Source: Building and Environment,Chao Yuan, Edward Ng, 2011

4.1 Site Analysis

Cruciform Tower FAR: n. DU:

7.3 768

Population 3.072 Area 27.741 m2 Floors 32

Tower Podium FAR: n. DU:

6.82 234

Population 2.106 Area 11.200 m2 Floors 21

Tower FAR: n. DU:

11,7 504

Population 1.512 Area 7.284 m2 Floors 42

Block FAR: n. DU:

The area is affected by several environmental conditions such as a lack of urban ventilation and being an urban micro-climate. In the redundant towers on the coastal block, the patchâ&#x20AC;&#x2122;s urban ventilation has seen wind speed drop over the last decade. Measures of the urban scale have shown high concentrations of NO2 and rising temperatures at the ground level. Inner conditions in the buildings are not recorded, but overcrowding suggests that indoor temperatures are 2ÂşC more than the urban area.

Sham Shui Po is one of the poorest districts of the city, portrayed as a decaying neighbourhood of claustrophobic apartments, where the shortage of public space is exposed on the bustling overcrowded streets. The area is a lively commercial centre where various scales of marketing take place; wholesale, retail and informal markets are steps away from each other.

Apparent economic prosperity with new capital investment in shopping centres exists alongside the miserable living conditions of the residents.

(Fig. 4.3)

3,5 448

Population 1792 Area 9.492 m2 Floors 14

Fig.4.4: Buildings morphologies, Sham Shui Po and Yau Tsim Mong districts, Hong Kong Source: LCE Cities, Urban Age Cities Compared, 2011

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4.1 Site Analysis

2 2

3

1

1

2 4

3

1

1

2 3

2 3

2 4 1

3

1

4

Figure 2. The growth of Sham Shui Po.

Fig.4.5: Growth of Sham Shui Po (1902 - 2005) Source:

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scheme was executed by private developers, mainly contractors, using Continuityland and changereclain the urban transformation of old mation and building projects (Smith, 1995). Two streets, Nathan Roaddistricts, andPuileng Boundary Woo, Ka Man Hui, 2010 Street, played a critical role for the layout of Sham Shui Po. Nathan Road was the ď&#x192;&#x17E;rst major road built in Kowloon, while Boundary Street was merely a line of high bamboo Emergent Technologiesfences. and Design | AA | The regulating line for the orthogonal layout of Sham Shui Po was set by bisecting the angle formed between Nathan Road and Boundary Street (Figure 2).

4.1 Site Analysis

Business/Factories Business/Factories

Leisure/Retail Leisure/Retail

Social Provisions Social Provisions

Green Areas Green Areas

Residential Residential

70 % 70 % + Retail + Retail at Gr at /Gr1st/ 1st floorfloor

30 % 30 % OnlyOnly Housing Housing

Fig.4.6: Existing Patch, Land use

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4.1 Site Analysis

Rooftop Villages Location

Average n. floors = 7-8

Fig.4.7: Existing Patch, Rooftop villages

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Area m² Surface 31.468 m²

4.1 Site Analysis

Sham Shui Po

Tai Kok Tsui

Retail - Electronics- Poorest

Sham Shui Po Tai Kok Tsui Kwun Tong

Kwun Tong

Mix - Industrial

Population 365.540 280.548 587,423

A high percentage of the patch’s population consists of marginalised groups with low economic status from Mainland China and Southeast Asia; some of them are part of the public housing programme that comprehends 40 per cent of the total housing of the area. The principal aim of public housing was for all of the levels of the buildings to be designed strictly for residential usage; however, from the outset they have been altered at ground- and top-floor levels to supply the need for other activities.

The existing morphologies are the product of manmade alterations in which small markets— narrow passages, informal settlements and social activities—take place.

Area 9.480 km² 6.550 km² 11.050 km²

39.000/km² 43.000/km²

Industrial

Density

48% 33% 55,000/km²

The interventions to the existing buildings are the consequence of a set of allowances from the early years of the Hong Kong Government. As the population grew during the 1960s, investment in infrastructure was largely concentrated on the creation of adequate housing stock, but there was a deficiency in services such as schools and churches; as a result, the Government allowed the establishment of informal structures on top of buildings that could host educational and physical activities. With the shortage and high cost of land, other usages started to emerge.

These are the roots of a major social problem: rooftop villages. (Fig.4.6)

Rooftop Villages

27%

Fig.4.8: Three districts Data comparison Source: "Portraits from Above: Hong Kong’s Informal Rooftop Communities", Stefan Canham,Rufina Wu ,2009

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4.2 Rooftop villages Fig.4.9: Rooftop Villlages general aspects, Frontal Section.

Source: "Portraits from Above: Hong Kong’s Informal Rooftop Communities", Stefan Canham,Rufina Wu ,2009

WHAT

-“poor housing” - illegal but “tolerated” by the government - temporary and informal rooftop structures - concrete, bricks, wood, metal sheets, flimsy material - dwellings’ area= from 9 to 28 sq. m.

WHERE

- Sham Shui Po, Kwun Tong, Tai Kok Tsui districts - old urban areas of the districts - old (30-40 years) dilapidated tenement buildings

WHO

- migrants from Mainland China and Southeast Asia - marginalized groups with low economic status Rooftop Dwellers 3,982 2006

WHY unbuilt land 75% built 25%

74

10s of thousands now

- shortage of land in Hong Kong for hilly topography - extremely high housing prices Average home price 14.9-times gross

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the annual median household income 2014

4.2 Rooftop villages Fig.4.10: Rooftop Villlages, Sham Shui Po district, Hong Kong Source: http://pantip.com

Rooftop structures are temporary structures built without the formal approval of the government.

People who either intend to live in them, or sell or rent them for profit, build them. They are supposedly “illegal” and disapproved of by the authorities, but they are also “tolerated” and “recognized” by the government. (Wu, Portraits from above - Hong Kong's Informal Rooftop Communities, 2009) The area has 48 per cent of the existing rooftop villages. They have served the critical function of providing accommodation for low-income,

marginalised communities. According to the most recent census of 2006, there were 1,554 households, accommodating 3,962 rooftop dwellers. Health and safety conditions inside the informal settlements are very poor; the phenomenon of cage houses is also part of the problem, where living areas are reduced to 1m² per person.

dwellers have been offered relocation in nearby cities through the public housing programme.

Ironically, the offers have been rejected due to the desire for proximity to the urban fabric that Hong Kong offers.

The Government has unofficial yet specific regulations towards rooftop villages in terms of relocating the inhabitants or demolishing the structures; nevertheless, some of the Adaptable Morphodynamics

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4.2 Rooftop villages Fig.4.11: Urban agriculture, Sky farms in Hong Kong Source: http://green-living-hk. blogspot.co.uk

Situation Agricultural Products 2.3 % local

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97.7% imported

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New Phenomenon Urba Agricultural Network Informal Rooftopgarderns

Vertical Eco-system: promote micro-economies rediscover local identiy use of public space

4.3 Analysis of Existing Urban ventilation

0 m/s

5 m/s

Fig.4.12: Patch, Analysis Urban Ventilation. Several levels.

Wind Direction EAST 5

0 m/s

Ground Floor

50 metres

100 metres

150 metres

The high rate of urbanisation and compact footprint in Hong Kong has had a significant impact on ground-level ventilation. One of the main challenges of the experiments carried out during the thesis has been how to optimise the urban porousness at ground level to ensure adequate natural ventilation in the urban area.

High-rise building blocks and deep-street canyons are one of the main urban characteristics of the patch. In one of the studied districts, Yau Tsim Mong, air flow was measured and compared with previous site analysis in order to understand the effect of air flow on temperature; it was observed that in the last decade the mean

wind speed at 20 metres above the ground level has decreased by about 40 per cent, from 2.5m/s to 1.5m/s (Chao Yuan, 2011). In summer, a decrease in wind speed from 1.0m/s to 0.3m/s is equal to a 1.9ยบC temperature increase, meaning that in our patch, temperatures have risen by 2.7ยบC. The increase of temperatures in the patch suggests that in order to achieve an outdoor thermal comfort under typical summer temperatures, we will require between 1.6m/s and 2.28m/s to decrease temperatures and provide more pleasant open-air conditions.

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4.4 CONCLUSION

The existing patch presents several architectural and environmental conditions that define the area’s potentialities and deficiencies. The patch tells the history of the city and how several interventions have affected the build environment. It is important to understand the existing urban structure and how it has played a key role in the historic transformation of the patch; the structure of the old neighbourhood’s fabric exposes its cultural identity and the importance of its activities for economic growth, while the renewal waterfront displays a preeminent hub for global trade.

A clear understanding of the site analysis will allow us to define the effect of the specific patch morphologies and how they have affected the existing urban conditions. The analysis can then guide us to address the possible solutions to improve environmental conditions and how this could be achieved through strategies applied to the existing buildings. The exploration of parameters that can change the buildings’ morphologies—such as setting back buildings, separating long buildings, stepping the podium, and opening the permeability of towers and podiums—will define how the strategies can be applied to the improvement of the air flow of the urban fabric.

The analysis of the patch suggests an intervention based on minimising the disruption in order to avoid the displacement of communities and to keep the patch’s cultural identity. A key factor of social inclusion will shape the emergent public space and will define the dynamics of interaction between the markets and other activities at podium levels.

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5. design development 5.1 Overview 5.2 Environmental Factors 5.3 Social & Architectural Aspects 5.4 Connectivity

5.1 overview

The urban design proposal for the redevelopment of a high-density district of Hong Kong considers the extreme local climate conditions and the insufficient provision of public services and open spaces as an indication to employ as a main driver the creation of a balanced distribution of social provisions and green areas within a comfortable microclimate in the residential urban tissue. The secondary ambition is to facilitate pedestrian movement throughout the site at multiple horizontal and vertical levels.

The overall design target is to address the transformation of the high-density urban fabric towards a responsive urban system, able to accommodate densification without neglecting its spatial and environmental quality.

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5.2 environmental factors Fig.5.1(a,b): High and low Porosity polystyrene designed for 3D cell culture Source: http://reinnervate.com

Fig.5.2: Urban Porosity, Ansan, South Korea (by BIG Architects, 2008) Source: http://www.designboom.com

Pore (from Greek poros) means “a minute opening”. Porosity or “the state of being porous” in the context of organic chemistry and the study of plants and animals indicates the existence of small openings. In biology and in medicine porosity is defined as: “the attribute of an organic body to have a large number of small openings and passages that allow matter to pass through”. The forms, sizes and distribution of pores are arbitrary. (Kotsopoulos, 2007) The concept of porosity, imported from biology and organic chemistry, has been already applied to the urban and architectural context to achieve openness, permeability and transparency of forms. For example, porosity was re-interpreted from Steve Holl’s studio in several architectural

projects, in order to be used in a new tectonic/ urban context, to guide the production of a sponge-like building morphology. (Kotsopoulos, 2007) A series of design operations can transform building morphology into a “porous machine”, able to alter the temperatures, light quality, humidity within a building. Porosity can define many features of an architectural space, marking physical boundaries between no-built up and formal built spaces.

In our thesis, the ambition to adopt a design strategy capable of combining environmental and architectural qualities using the idea of porosity was particularly interesting. We

employed this concept as the main design tool for the optimization of existing morphologies for the urban airflow and with positive outcomes at the architectural scale as well. Porosity was conceived as a system integrated mainly with the structural but also with the skin and window layouts of existing buildings. It required subtraction of smaller masses from a larger volume to achieve “breathable architectures”.

Indeed, the design process, based on both computational rules and conceptual frameworks, intended to transform the existing morphologies by means of a system of vertical cavities to ensure the penetration of light and the circulation of air.

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5.2 environmental factors Fig.5.3: Diagram, Porosity geometrical operations for Simmons Hall, Cambridge, MA, USA (by Steven Holl, 2002) Source: Design concepts in architecture: the porosity paradigm, Sotirios D. Kotsopoulos, CEUR Workshop Proceedings, 2007.

Fig.5.4: Porosity Block, Simmons Hall, Cambridge, MA, USA, (by Steven Holl,2002) Source: http://en.wikipedia.org

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5.3 social and architectural aspects Fig.5.5: Library-Parks, Medellin,Columbia (by G. Mazzanti, 2007) Source: http://terraurban.wordpress.com

The purpose is to propose a high-density and interconnected locality in Hong Kong, which embraces existing conditions and social values as essential design inputs, for stimulating economic, cultural and social growth. The choice of this area, located in the north-western part of the Kowloon Peninsula, was made with the intent to operate in a critical scenario, characterized by striking social contradictions and serious environmental problems. Indeed, the district has developed with no control over time and currently is mainly defined by lack of open spaces, and a hyper-dense, poor quality housing that accommodates low-income people.

The phenomenon of the rooftop villages, as discussed earlier, is widely spread throughout the patch, and the project aims to recover these poorest sectors through an approach of urban inclusion instead of disruption. We believe that improving the general quality of the urban environment could bring about positive effects on marginalized areas by establishing

a sense of acceptance, integration and dignity among people. The metamorphosis of Medellin, in Colombia, is a significant example of how architecture and design can empower the poor communities, previously approached by lower quality interventions.

The urban proposal provides diversification of functions inside building typologies and the permeability of the building morphologies at ground and top floor levels creates an easy access to emergent public open spaces by means of facilitating fluid pedestrian circulation.

The Growth strategy generates additive volume, distributed within the different building typologies and housing new mixed-use programmes avoids extreme zoning and segregation of land-uses.

Furthermore, it also allows the recovery of part of the lost demographic density, which occurs from the subtraction of urban volume for the creation of open spaces within the buildings.

The formation of a collection of open spaces,

public, semi-public and semi-private, aims to preserve the local identity of the district, promote the small local business linked to the Chinese tradition of open street markets, and also shape a cultural and social environment for different types and ages of users. In fact, the wide range of sizes of open spaces, from small to large, could embrace the two main opposing social behaviours demonstrated by Chinese people; a reserved attitude, linked to a traditional sense of privacy, and a contemporary need for public display, due to the transformation to a globalized society. In this light, a distributed network of pocket open spaces could satisfy the need to live more parochially, whereas larger and multipurpose areas could accommodate a variety of activities that require a greater number of users.

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5.4 connectivity DEFINE OPEN SPACE

CREATE MULTILAYER OF CONNECTIVITY

CRITERIA

CLUSTERS

Short walk Urban Attractors

Surface area

DEFINE Type of Connection

5 - 15 minutes range (0.25 km = 5 minutes)

(Large areas of Public space)

Floating Population

0.75 km 0.50 km 0.25 km

300 m2 - 200 m2 500 m2 - 300 m2 500 m2 >

Fig.5.6Diagram, Connectivityâ&#x20AC;&#x2122;s Strategy

(400 - 1200 pp h)

LOW FLOW MEDIUM FLOW HIGH FLOW

Public Transportation Secondary layer Rooftop Villages Services Green areas

As a result of the porosity strategy a series of emergent open spaces are distributed throughout the patch. The emergence of clusters that connect larger areas of public space aims to integrate the public spaces to the existing layers of connectivity in the city. The clusters are connected under two criteria: large areas of open public space and closeness to urban attractors.

We identified blocks with a larger surface area of open space in order to evaluate how close they were to urban attractors, such as: - Public Transportation system (MTR): to provide a direct accessibility from other districts of the city - Existing secondary pedestrian layer: to extend the existing pedestrian network and connect it to the emergent open spaces

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-Rooftop Villages: to generate social inclusion by generating new dynamics of interaction between poor housing and its surroundings -Services and social provisions: to strengthen the linkage with areas where there are public services -Existing Green Areas: to create an extended and integrated network of public spaces Three areas are identified in the patch for the development of clusters, and are located between three and five minute walk from the two main public transportation nodes of the patch: Sham Shui Po and Olympic Tube Station.

Each cluster will have several levels of connectivity according to the floating population A hierarchy of flows will define the amount of connected blocks and the mutual relation at building, block and cluster scale. High Flow will

be designed for an estimated index of 800 to 1200 pp./h, Active Flow for 400 to 800 pp./h, and finally Low Flow for 400 pp./h.

6. experiments 6.1 Strategyâ&#x20AC;&#x2122;s Parameters 6.2 Patch scale: Experiment 1 and 2 6.3 Patch scale: Experiments comparison 6.4 Limitations 6.5 Porosity and Pedestrian Circulation

6.1 strategy’s parameters n. floors = 1-10 H = 3-30 m

n. floors = 11-20 H = 33-60 m

n. floors = 21-30 H = 63-90 m

n. floors > 30 H > 90 m

Fig.6.1: Selected Patch, Classification of Existing Buildings by height

URBAN BUILDING TYPOLOGIES Previous studies on the current situation on the selected patch (Chapter 4) showed that the area has a high population density, characterised by high-rise buildings with a business and residential function on the southern coast boundary, and by medium- and low-rise buildings, mainly residential, in the northern part. In particular, as previously discussed, the phenomenon of illegal informal settlements on the rooftop surfaces of existing buildings, known as ‘rooftop villages or sky slums’, is widely diffused in this northern area of the patch.

Following this analysis, the overall strategy was based on the combination of environmental performance, in terms of maximised urban wind ventilation and minimised solar exposure in the

hottest month, and architectural ambitions, in terms of high-density building morphologies, integrated with open spaces and socialprovisions.

Existing buildings were considered as geometrical primitive input for optimisation of the patch, and they were classified according to their typology, height and destination. Four ranges of height were established: -Low rise Building Blocks with an Height= 3-30 m (1-10 floors) -Medium rise Building Blocks with an Height= 33-60 m (11-20 floors)

-High rise Building Blocks with an Height= 63-90 m (21-30 floors) -High rise Towers with an Height> 90 m (>30 floors) Rooftop villages and existing social provisions were directly excluded from the strategy to avoid negatively affecting the density in critical nodes, and so as not to reduce the current amount of facilities and services for inhabitants through disruptive intervention. Nevertheless, the general strategy aimed to indirectly regenerate them, thanks to the environmental and social benefits that they can deduce from the improvement of their surroundings.

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6.1 strategyâ&#x20AC;&#x2122;s parameters Fig.6.2: Wind Strategies Exploration- Selected four blocks

WIND STRATEGIES EXPLORATION

STRATEGY 1

STRATEGY 2

An exploration of different wind strategies was conducted in order to understand how to improve air flow at the several height levels in the urban patch, and also how to acquire knowledge about possible parameters, such as porosity and roughness of the surfaces, to apply to existing building morphologies. The effect of porosity on the urban ventilation was tested at different height levels, and additional parameters for redirecting air flow to specific points were studied. The test was run on four existing blocks, considering a porosity parallel to the prevailing east wind and a variation of the wind vector of Âą30 degrees. The aim was to understand how to maximise air flow by using breezeways and pedestrian permeability all over the district.

Porosity at ground level is applied, considering a set of vectors breaking the podium along the prevailing wind direction and within a range of a 30 degree angle. In case 1, the dimension of voids has an inlet equal to the outlet (6 metres), while in case 2 inlet and outlet are 6 and 9 metres respectively. In both cases, the amount of porosity is set to a value between 30 and 50 per cent. It is clear from the CFD analysis that the increased wind permeability in the podium layer is very useful for leading air flow to deep street canyons.

It has been observed that there is more ventilation on the top-floor levels of the patch; consequently, it can be deduced that porosity applied to top floors could be used to bring benefits to lower levels. Thus, in cases 1 and 2, porosity is applied to the buildings at topfloor levels from 9 to 70 metres. The permeability can vary between 10 and 15 per cent in both cases. In addition, although in case 1 there is no inclination applied along the y axis, in case 2 an inclination between 0 and 15 degree angles is considered in order to redirect the air flow from the top-floor level to the ground-floor level. As shown, permeability at the top-floor levels could redirect wind from above to the pedestrian level.

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6.1 strategyâ&#x20AC;&#x2122;s parameters Fig.6.3: Wind Strategies Exploration- Four Strategies

STRATEGY 3

STRATEGY 4

Variations on the width of the urban canyons and buildingsâ&#x20AC;&#x2122; setbacks allow air flow to be driven from the urban canopy layer to the ground level. Therefore, different types of setbacks are applied to the existing buildings in order to increase the width of the existing streets. In case 1, an inclined setback is set in relation to the street width (y = x1), while in case 2 we can find a stepped setback with a depth of 3 metres on the middle levels (y = 3 metres), and a depth of 6 metres on the top-floor levels (y = 6 metres). Both cases have a range of permeability arranged from 10 to 15 per cent.

Roughness on the rooftop surfaces can create a variation of heights in the urban canopy layer in order to break the continuous height of buildings, which blocks wind at higher levels, and can also be used to direct air flow towards the patch.

This strategy is applied to lower buildings with a height between 21 and 30 floors. Their rooftop surfaces are split into a grid and each cell is extruded vertically from 3 to 6 metres. The percentage of porosity is set between 10 and 15 per cent.

STRATEGY CONCLUSION From the CFD analysis of the different strategies, it is observed that any porosity could improve urban ventilation, but only the redirection of air flow from the upper floors could have a significant effect on the pedestrian level. Due to the vertical profile of the mean wind velocity,

that decreases air flow performance at the lower levels, permeability at the podium level does not appear to improve the urban ventilation, even with 50 per cent of porosity.

Furthermore, the air flow above the urban canopy layer may not easily enter into the deep street canyons to benefit the wind environment at the pedestrian level. Thus, the wind velocity ratio at the ground floor is mostly dependent on the wind permeability of the upper levels and podium layer. The roughness did not increase urban ventilation, but it was effective at redirecting the air flow of the urban canopy layer. To conclude, some of these strategies can guide the settings of the parameters applied to the algorithm: porosity at ground and top-floor levels, and roughness strategy on the rooftop surfaces.

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6.1 strategyâ&#x20AC;&#x2122;s parameters URBAN VENTILATION - LEVEL 0

1.Porosity Ground 30% Inlet 6m Outlet 6m

2. Porosity Ground 30%Inlet 6m Outlet 18m

3. Porosity Ground 50%Inlet 6m Outlet 6m

0 m/s

5 m/s

6. Porosity at Top Floors 10% 7. Porosity at Top Floors 10% 8. Stepped Set Backs Inlet 6m Inlet 6m Outlet 6m Outlet 6m Angle 10, connections Angle 10 Wind Direction EAST

5 AA | EmTech 0 m/s | 2013-14 | Dissertation

4. Porosity Ground 50%Inlet 6m Outlet 18m

5. Porosity at Top Floors 10% Inlet 6m Outlet 6m

9. Inclined Street Canyons

10.Rugosity 5 m/s

5 m/s

0 m/s

0 m/s

Adaptable Morphogenesis

Fig.6.4: Wind Strategies Exploration- CFD Analysis Ground floor

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URBAN VENTILATION - AVERAGE HEIGHT 20M

1.Porosity Ground 30% Inlet 6m Outlet 6m

2. Porosity Ground 30%Inlet 6m Outlet 18m

3. Porosity Ground 50%Inlet 6m Outlet 6m

0 m/s

5 m/s

6. Porosity at Top Floors 10% 7. Porosity at Top Floors 10% 8. Stepped Set Backs Inlet 6m Inlet 6m Outlet 6m Outlet 6m Angle 10, connections Angle 10 Wind Direction EAST

5 AA | EmTech 0 m/s | 2013-14 | Dissertation

4. Porosity Ground 50%Inlet 6m Outlet 18m

5. Porosity at Top Floors 10% Inlet 6m Outlet 6m

9. Inclined Street Canyons

10.Rugosity 5 m/s

5 m/s

0 m/s

0 m/s

Adaptable Morphogenesis

Fig.6.5: Wind Strategies Exploration- CFD Analysis 20 m Height

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95

URBAN VENTILATION - 40M

1.Porosity Ground 30% Inlet 6m Outlet 6m

2. Porosity Ground 30%Inlet 6m Outlet 18m

3. Porosity Ground 50%Inlet 6m Outlet 6m

0 m/s

5 m/s

6. Porosity at Top Floors 10% 7. Porosity at Top Floors 10% 8. Stepped Set Backs Inlet 6m Inlet 6m Outlet 6m Outlet 6m Angle 10, connections Angle 10 Wind Direction EAST

5 AA | EmTech 0 m/s | 2013-14 | Dissertation

4. Porosity Ground 50%Inlet 6m Outlet 18m

5. Porosity at Top Floors 10% Inlet 6m Outlet 6m

9. Inclined Street Canyons

10.Rugosity 5 m/s

5 m/s

0 m/s

0 m/s

Adaptable Morphogenesis

Fig.6.6: Wind Strategies Exploration- CFD Analysis 40 m Height

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6.1 strategy’s parameters Fig.6.7: Strategy - Subtraction and Addition of Volume

POROSITY AND GROWTH STRATEGIES As result of the exploration of urban ventilation strategies, porosity and roughness strategies were chosen as drivers to enhance air flow in the patch. First of all, the creation of a subtractive porous system applied to the existing buildings, transformed them into wind permeable organisms, and provided them with open spaces on multiple levels, as a result of the subtracted volume. Second of all, not only did the application of an additive growth strategy on existing buildings rooftop levels aim to increase wind velocity through surfaces roughness, but this mass addition brought about the emergence of new and various functions.

Two experiments were run at the patch scale by using evolutionary computational tools. The analysis of the main environmental problems and social conditions in the patch identified critical areas of intervention. As a consequence,

a porosity gradient was applied to the whole patch in order to diversify the permeability of the urban tissue at specific points. High porosity was applied to the patch’s boundaries because of the presence of high-rise buildings, blocking the wind on the southern coastal side, and the lack of open spaces on the northern side.

However, medium and low porosity were defined in zones with high residential population density in order to minimise the amount of built volume to remove.

Finally, the growth strategy was applied to specific building types characterised by moderate ranges of height, such as 3–30 metres and 33–60 metres. No volume was added to taller buildings in order to avoid an increase of height worsening the general urban ventilation performance. In the selected buildings, the height of the additive volume was increased by one floor unit in comparison to Experiment 1.

In both experiments, the porosity gradient was applied at different levels of height, such as ground-floor, podium and top-floor levels, for each building type. It is clear from the table above that the percentage of high porosity was slightly increased in Experiment 2 with respect to Experiment 1, whereas the proportion of medium and low porosity stayed equal.

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6.1 strategy’s parameters

HEIGHT LEVEL

HEIGHT LEVEL

Fig.6.8: Map of the Porosity Gradient applied to the existing patch

EXPERIMENT 1

HIGH POROSITY

MEDIUM POROSITY

LOW POROSITY

Top Floors Level

75%

65%

50%

Podium Level

50%

50%

50%

Ground Floor Level

50%

50%

50%

EXPERIMENT 2

HIGH POROSITY

MEDIUM POROSITY

LOW POROSITY

Top Floors Level

85%

65%

50%

Podium Level

50%

50%

50%

Ground Floor Level

50%

50%

50%

CLUSTER

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Tab.6.1: Experiment 1 and 2Porosity Gradient’s percentage by area and height level

6.1 strategyâ&#x20AC;&#x2122;s parameters

high

medium

low

Porosity

Fig.6.9: Porosity Gradientâ&#x20AC;&#x2122;s experiment 1

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6.2 patch scale: experiment 1 and 2

Tab.6.2: Experiment 1 and 2- Grid Subdivision by level

GRID SUBDIVISION (u,v)

HIGH POROSITY BUILDINGS HEIGHT

GROUND LEVEL

H= 3 - 30 m

N/A

N/A

2x4

2x3

3x2

H= 33 - 60 m

2x3

2x2

2x4

2x3

3x2

H= 63 - 90 m

5x6

5x5

5x5

5x4

N/A

H > 90 m

5x6

5x5

5x5

5x4

N/A

Exp.1

Exp.2

Exp.1

Exp.2

Exp.1 - Exp.2

PODIUM H= 3 -12 m CLUSTER

TOP FLOORS LEVEL

GROWTH

2x3 Exp.1 - Exp.2

2x1 Exp.2

2x1

GENERAL COMPUTATIONAL SETUP In each experiment, a multi-objective evolutionary algorithm was applied to existing morphologies, considered as primitive geometries. The body of each building is structured on a regular grid of cells and the size of cells varies according to three levels of height, defined as groundfloor level (± 0.00 m), top-floor level (+9.00 m) and rooftop level (+ Hmax building). The grid subdivisions are bigger at the ground-floor level and rooftop level in order to maximise the air flow and increase the surface areas of open spaces and emergent functions. On the contrary, the top-floor level is characterised by smaller cells, which tend to be more adequate for residential units, as well as communal and semi-private open spaces.

Therefore, in both experiments the body plan for each building typology consists of specific number of cells per each of the three height levels. Moreover, as shown in the table above, in Experiment 1 the building morphologies 100 Emergent Technologies and Design | AA |

were first modified on a smaller gridded plan, whereas in Experiment 2 the number of cells’ subdivisions was generally decreased over the entire patch—particularly in specific points, where buildings aggregate in clusters nearby public transportation nodes. The phenotype is determined by two variables (genes) applied to each of the cells of the body plan. The differential intensity of the modifying genes’ effect on the body plan is regulated by homeobox genes. The variables for each cell are: (a) Height of vertical extrusion in multiples of 3 metres (equal to the standard height of one storey). (b) Location of cells, vertically extruded up to the Hmax of existing buildings.

The vertical extrusion in multiples of 3 metres can only be modified within a certain range, which is dissimilar for each building typology

and depends on the height of a specific building.

For instance, the extrusion of cells is between 0 and 9 metres at ground floor level, between 9 metres and Hmax of the building at top-floor level, and finally between 3 and 12 metres at rooftop level.

The percentage of the cells totally extruded up to the maximum height of the building is fixed.

Indeed, this factor contributes to regulation of the percentage of porosity in the urban tissue.

On the other hand, the location of all cells varies randomly.

Finally, the fitness criteria influencing the generation of phenotypes are maximisation of building volume, minimization of building envelope’s solar exposure in July (hottest month), and maximisation of the shadow on the ground.

6.2 patch scale: experiment 1 and 2

Fig.6.10: Experiment 1 and 2Porosity Strategy

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6.2 patch scale: experiment 1 and 2

Fig.6.11: Experiment 1 and 2Growth Strategy

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6.2 patch scale: experiment 1 and 2

Fig.6.12: Experiment 1 and 2Fitness Criteria

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6.2 patch scale: experiment 1 and 2

1) ENVIRONMENTAL

- Enhance Urban Ventilation

-

Rougosity on rooftop surfaces to Increase Wind’s Velocity

In

GENERAL COMPUTATIONAL FLUID DYNAMIC SETUP Computational fluid dynamic will be used throughout the experiments in order to analyse the impact of the different morphologies on urban ventilation. In this study, we will take into account the characteristics of the dense urban morphologies and the site’s prevailing winds.

The urban fabric will be tested at different scales, such as patch, cluster and block scale, in order to achieve more accurate results.

Dynamic analysis at podium level where drag is more significant (3–9 metres), at a height of 30 metres, at the urban canopy layer (50 metres), and finally at the top of high-rise buildings (100– 150 metres). Specific criteria will be used to analyse and compare different results.

For the analysis, it is relevant to consider that the air moving on the Earth’s surface is slowed down by frictional forces. These forces have a decreasing effect on air flow as the height above the ground increases, resulting in mean wind speed increasing with height, up to a point where the effects of surface drag become insignificant. Therefore, the entire patch and some specific sub-areas will be analysed using a three-dimensional (3D) Computational Fluid

DATA

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WIND INPUT -Direction: East -Speed: 3 m/s - Grid Resolution: Patch

O

6.2 patch scale: experiment 1 and 2

Tab.6.3: Experiment 1 Genetic Algorithm Parameters

No. GENERATIONS= 10 No. INDIVIDUALS/GEN.= 10

EXPERIMENT 1

PARAMETERS

GEN.0-3

GEN.4-6

GEN.7-9

Elitism

50%

50%

75%

Mutation Rate

25%

50%

75%

Mutation Probability

25%

50%

50%

Crossover

50%

75%

50%

EXPERIMENT 1 SETTINGS

RESULTS: VOLUME AND OPEN SPACE

No. GENERATIONS= 20

EXPERIMENT 2

1 shows that the initial volume For the entire patch in Experiment 1, ten No. Experiment INDIVIDUALS/GEN.= 10 was around 32 per cent of the original generations of ten individuals each were run removed in Grasshopper using the evolutionary solver total volume. The volume added through the PARAMETERS GEN.0-6 such growth GEN.7-12 GEN.13-19 which is about strategy is 1.117.395m続, Octopus. The evolutionary parameters, as Mutation Probability, Mutation Rate, Elitism 20 per cent of the initial volume subtracted. As per cent of the total and Crossover, were changed every three a result, Elitism 20% 50%approximately 26 75% original volume was lost, exceeding the initial generations. target 75% by 6 per cent.

50% 25% Mutation Rate In addition, as a result of the porosity strategy, RANKING a series 25% 50% of open spaces were 25% created by the Mutation Probability Three individuals with the highest value of volume subtraction of volume. The dense pixilation of brought 75% about the creation were selected over ten generations;50%they were the morphologies 50% Crossover later tested for wind performance. It was clear of open spaces characterised by small surface from the Fluid Dynamic analysis that all three areas and with an influence at the local scale selected individuals performed similarly with of the building. The data show that the ratio regard to urban ventilation. As a consequence, of public open space per inhabitant has been the patch with the highest value of volume was increased by 47 per cent with respect to the existing value. chosen as final among others.

Adaptable Morphodynamics 105

6.2 patch scale: experiment 1 and 2 Primitive Input

EXISTING PATCH

EVOLUTIONARY OUTPUT Ops Atot ex= 236.844 m² Vtot ex= 17.234.980 m³

GOALS

Fig.6.13: Existing patch and Experiment 1- Results comparison

Experiment 1

Ops Atot Exp1= 399.050 m² Vtot Exp1= 12.849.396 m³

- Double Existing Public space (Ratio ex = 1.66 m²/inhab.)

Ratio 1-Ops = 3.15 m²/inhab.

- Reallocate min 40% of V removed

V1 growth= 1.117.395 m³ (= 20.30% of V2 removed )

- V disruption <= 20% of Vtot ex

V1 disruption= 4.385.584 m³ (= 25.5% of Vtot ex) V1 removed= 5.502.979 m³

RESULTS

RESULTS: URBAN VENTILATION A CFD analysis was carried out to identify whether the parameters set up in the algorithm have improved the existing urban ventilation.

The patch has been analysed at ground floor level, as well as 50, 100 and 150 metres, without considering the context. It is pertinent to highlight that the resolution of the CFD analysis at patch scale is not accurate, and thus it can be observed that the wind performance of the modified morphologies has changed slightly.

However, this analysis can provide an overall understanding about how the morphologies could alter air flow in different areas of the patch.

As is evident from the wind analysis of the existing patch, the ground level lacks complete air flow (0m/s) and Experiment 1 shows no improvement with regard to wind ventilation at a pedestrian level, regarding the 50 per cent of 106 Emergent Technologies and Design | AA |

porosity applied. These 3D CFD simulations analysed different horizontal sections of the patch, up to the total height of the buildings, in order to understand the impact of the urban ventilation from the bottom upwards.

It can be seen that, in this case, the vertical profile of buildings significantly reduces air flow performance at lower levels. At 50 metres, at point A, the roughness strategy was applied in order to relocate the volume removed by the porosity strategy. Here, it is observed that there is a decrease in the amount of air flow, due to the increase of the building’s height. On the contrary, at point B, it is obvious that wind speed increased from 0m/s to 2m/s in some areas, thanks to the high porosity applied to the existing buildings. This increase of wind velocity positively affected the west urban ventilation of

the patch.

As a result of the roughness strategy, we can see a decrease of air flow at point C, at 100 metres, and consequently its effect on the low and medium porosity area. At point D, it is observed that no air flow has been improved; therefore, wind speed has been reduced from 3m/s to 0m/s.

6.2 patch scale: experiment 1 and 2 Fig.6.14: Comparison of CDF analyses between Existing patch and Experiment 1

(a)

EXISTING PATCH EXISTING PATCH

URBAN VENTILAT URBAN

URBAN VENTILATION URBAN VENTILATION ANALYSIS OPTIMIZATION ANALYSIS OPTIMIZATION

(c) EXISTING PATCH EXPERIMENT EXPERIMENT 1 1 EXISTING PATCH EXPERIMENT EXPERIMENT 2 2EXPERIMENT 1EXPERIMENT 1

C

(a) Ground Floor level (b) 50 m Height (c) 100 m Height (d) 150 m Height

D

(b)

GROUND FLOOR GROUND FLOOR

(d)

A

m/s Wind Direction m/s Wind EASTDirection Direction 0 Wind 5 0 EAST

EAST

0| m/s AA | EmTech 5 |AA 2013-14 | EmTech | Dissertation 2013-14 | Dissertation

At 150 metres, air flow has been increased at point E where a high level of porosity was applied to the high-rise buildings to reduce their wall effect. This improvement can only be seen at this top level. By comparing these results with those of the existing patch, it emerges that the wind performance varies according to the different modifications of the building morphologies, bringing about improvements in some specific areas. Indeed, in Experiment 1 it is still evident that the towers located on the southern side of the patch do not allow the ventilation to pass through the patch, and for this reason these morphologies need to be reconsidered in the next stage.

Furthermore, a wind analysis was carried out at a detailed scale in order to obtain a visual higher resolution of the results, and to get a

5

m/s 0 5

0 m/s

5 m/s

0 m/s

5 m/s

0 m/s

0 m/s

5 m/s 5 m/s

5

0 m/s

5 m/s

B

50 metres m/s Wind Wind Direction EASTDirection EAST 0

50 metres

AA | EmTech | AA 2013-14 | Dissertation | EmTech | 2013-14 Adaptable | Dissertation Morphodynamics Adaptable Morphodynamics

clear understanding of how the urban ventilation is affected by existing and modifiedmorphologies.

Six blocks, composed of low-rise buildings and located in Sham Shui Po district, were compared at different levels: ground, 10 metres, 30 metres and 50 metres.

Overall, wind ventilation has been improved at several levels; for example, at 30 metres porosity, no positive effect on air flow was observed, whereas other adjacent areas accounted a wind speed of between 3m/s and 4m/s. By identifying these differences of wind speed, it could be possible to define different functions in the emergent spaces, based on outdoor thermal comfort.

Adaptable Morphodynamics 107

6.2 patch scale: experiment 1 and 2

Fig.6.15: Existing Patch

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6.2 patch scale: experiment 1 and 2

high

medium

low

Porosity

Fig.6.16: Patch - Experiment 1 Output

Adaptable Morphodynamics 109

6.2 patch scale: experiment 1 and 2

Tab.6.4: Experiment 2 Genetic Algorithm Parameters

No. GENERATIONS= 20 No. INDIVIDUALS/GEN.= 10

EXPERIMENT 2

PARAMETERS

GEN.0-6

GEN.7-12

GEN.13-19

Elitism

20%

50%

75%

Mutation Rate

50%

75%

25%

Mutation Probability

25%

50%

25%

Crossover

50%

50%

75%

EXPERIMENT 2 SETTINGS In Experiment 2, for the entire patch, 20 generations of 10 individuals each were run in Grasshopper using Octopus’s evolutionary engine. The evolutionary parameters, such as Mutation Probability, Mutation Rate, Elitism and Crossover, were changed every seven generations.

RANKING Three evaluation criteria—minimum solar exposure in July, maximum value, and minimum volume—were used to rank all individuals and choose the three fittest individuals for each of the three parameters. The urban ventilation performance of the three selected patches was tested by using Vasari, a Computational Fluid Dynamic analytic tool. The wind analysis showed that the fittest individual for minimum solar exposure is the most optimised for the wind.

Thus, this individual was chosen and reputed the best option, both for the air flow maximisation and its intermediate value of volume between the two extremes.

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6.2 patch scale: experiment 1 and 2 EXPERIMENT 2- EVALUATION SELECTED PATCHES MAXIMUM VOLUME

MINIMUM SOLAR EXPOSURE

MINIMUM VOLUME

- V2 = 13.807.608 m続

V2 = 13.592.894 m続

- V2 = 13.413.157 m続

50 mtrs

0 m/s 0 m/s

5 m/s 5 m/s

Wind Direction EAST

Wind Direction EAST m/s 5 5 0 m/s 0

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150 mtrs Adaptable Morphodynamics

Fig.6.17: Experiment 2 CDF analysis of the three selected individuals

Adaptable Morphodynamics 111

6.2 patch scale: experiment 1 and 2 Primitive Input

EXISTING PATCH

EVOLUTIONARY OUTPUT Ops Atot ex= 236.844 m² Vtot ex= 17.234.980 m³

GOALS

Tab.6.5: Existing patch and Experiment 2- Results comparison

Experiment 2

Ops Atot Exp2= 393.810 m² Vtot Exp2= 13.627.673 m³

- Double Existing Public space (Ratio ex = 1.66 m²/inhab.)

Ratio 2-Ops = 3.10 m²/inhab.

- Reallocate min 40% of V removed

V2 growth= 1.823.430 m³ (= 33.6 % of V2 removed )

- V disruption <= 20% of Vtot ex

V2 disruption= 3.607.308 m³ (= 21% of Vtot ex) V2 removed= 5.430.738 m³

RESULTS: VOLUME AND OPEN SPACE The quantitative results show that in Experiment 2 the initial volume removed was roughly 5.4 million cubic metres, about 30 per cent of the existing total volume. It was possible to regain one third of the initial volume removed through the growth strategy. This allowed us to maintain our aim of only losing around 20 per cent of the original total volume.

Furthermore, decreasing the grid subdivisions in Experiment 2 led to obtaining a series of open spaces with a variety of dimensions.

Larger gridded plans were specially applied to morphologies aggregated in clusters in order to achieve open public spaces with larger surface areas in specific points of interest. As can be seen from the data, the porosity strategy made

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RESULTS

6.2 patch scale: experiment 1 and 2

EXISTING PATCH

Fig.6.19: Comparison of CDF analyses between Existing patch and Experiment 2

(a)

URBAN VENTILATION ANALYSIS OPTIMIZATION

EXISTING PATCH EXPERIMENT EXISTING 1 PATCH

URBAN VENTILATION ANALYSIS OPTIMIZATION URBAN VENTILATION ANALYSIS OPTIMIZATION

(c) 1 EXPERIMENT EXPERIMENT 2 1EXPERIMENTEXISTING PATCH

EXPERIMENT 2EXPERIMENT 2EXPERIMENT 1

(a) Ground Floor level (b) 50 m Height (c) 100 m Height (d) 150 m Height

GROUND FLOOR

(b)

(d)

GROUND FLOOR

100 metres

50 metres

150 metres

F

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0 m/s

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G

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5

0

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RESULTS: URBAN VENTILATION A CFD analysis was carried out to evaluate the performance of the revised computational parameters in Experiment 2. Roughness was incremented by 3 metres for each typology, while porosity was increased by 10 per cent in the high porosity area, bringing about a general improvement in urban ventilation. The patch was analysed at the ground floor, 50 metres, 100 metres and 150 metres. CFD analysis at the patch scale allowed us to observe moderate changes, as a consequence of the strategy’s application.

Similar to Experiment 1, Experiment 2 sees no improvement in the urban ventilation at the ground floor with respect to the existing situation.

One of the main reasons for this result remains the Earth’s friction that reduces the input wind speed at ground level.

At 50 metres, an overall decrease of air flow onthe boundaries of the patch is shown, while the roughness strategy increases the building‘s height in order to direct air flow. In this CFD resolution, the roughness effect is more evident than that of the porosity strategy. In the low and medium porosity areas, we can see a better performance of the porosity strategy, at points F and G, with wind speed increased by 2m/s.

At 100 metres, there is an improvement in comparison to the last experiment, due to the increase of the porosity in the top floors of the towers, which previously blocked the wind. The high permeability of the high-rise buildings showed a significant improvement in the urban ventilation, allowing air flow to pass through the patch.

URBAN

At 150 metres, an overall optimisation of the urban ventilation was achieved thanks to the permeability of high-rise morphologies, and it can also be seen that the increase of air flow on the top layer of the patch redirected wind flow to the lower levels. .

Adaptable Morphodynamics 113

6.2 patch scale: experiment 1 and 2

Fig.6.20: Existing Patch

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6.2 patch scale: experiment 1 and 2

high

medium

low

Porosity

Fig.6.21: Patch - Experiment 2 Output

Adaptable Morphodynamics 115

6.3 EXPERIMENTS COMPARISON Tab.6.6: Experiments results comparison

Primitive Input

Experiment 1

Experiment 2

EVOLUTIONARY OUTPUT

EXISTING PATCH Ops Atot ex= 236.844 m² Vtot ex= 17.234.980 m³

GOALS

Ops Atot Exp1= 399.050 m² Vtot Exp1= 12.849.396 m³

Ops Atot Exp2= 393.810 m² Vtot Exp2= 13.627.673 m³

- Double Existing Public space (Ratio ex = 1.66 m²/inhab.)

Ratio 1-Ops = 3.15 m²/inhab.

Ratio 2-Ops = 3.10 m²/inhab.

- Reallocate min 40% of V removed

V1 growth= 1.117.395 m³ (= 20.30% of V2 removed )

V2 growth= 1.823.430 m³ (= 33.6 % of V2 removed )

- V disruption <= 20% of Vtot ex

V1 disruption= 4.385.584 m³ (= 25.5% of Vtot ex) V1 removed= 5.502.979 m³

V2 disruption= 3.607.308 m³ (= 21% of Vtot ex) V2 removed= 5.430.738 m³

VOLUME & OPEN SPACE

URBAN VENTILATION

Overall, the initial architectural target to minimise disruption at 20 per cent in the urban fabric has been achieved. Although the volume removed in Experiment 1 and 2 is almost equal, the outcome of Experiment 2 is better in terms of maintaining high density in the urban tissue.

Indeed, the volume added through the growth strategy in Experiment 2 is almost 11 per cent of the initial original volume, whereas Experiment 1 shows a growth around 6 per cent. Additionally, even though the total surface area of open public space is slightly smaller in Experiment 2, generally in both cases the ratio of open public space per inhabitant is doubled in comparison to the existing situation. Ultimately, another important point is that the range of sizes of open spaces is more varied in Experiment 2 than Experiment 1, thanks to the smaller degree of pixilation of buildings and the application of larger gridded plans to morphologies, nearby public transportation nodes.

The evolutionary outputs have been analysed with a CFD simulator on the patch scale without considering the surrounding context. Thus, the complexity of the existing topography of Hong Kong was not included; as a consequence, these simulations did not consider the drag effect. The comparison of the results between the existing patch and both experiments showed how the different strategies and their parameters positively or negatively affect urban ventilation.

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It was difficult to observe any improvements in air flow at the ground-floor level, and for this reason it would be important to further consider the air flow efficiency of the porosity strategy at this level, as well as whether this permeability should only have social and architectural input criteria. However, the high porosity applied at multiple levels has shown a positive impact on urban ventilation, due to its capability of transferring air flow from the top levels to the

RESULTS

lower levels. Finally, the most relevant result is that the porosity strategy applied to the highrise morphologies could allow a cross ventilation between the eastern and western parts of the urban patch.

6.3 EXPERIMENTS COMPARISON EXISTING PATCH

(a)

URBAN VENTILATION ANALYSIS OPTIMIZATION

EXPERIMENT 1

EXPERIMENT 2

GROUND FLOOR

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5 m/s

5 m/s

(b)

Wind Direction EAST

EAST 5 Wind Direction 0

m/s AA 5 | EmTech |02013-14 | Dissertation

50 metres

Adaptable Morphodynamics

Fig.6.23: Comparison of CDF analyses between Existing patch, Experiment 1 and 2 (a) Ground Floor level (b) 50 m Height

Adaptable Morphodynamics 117

6.3 EXPERIMENTS COMPARISON (c)

EXISTING PATCH

URBAN VENTILATION ANALYSIS OPTIMIZATION

EXPERIMENT 1

EXPERIMENT 2

100 metres

0 m/s

m/s

0 m/s

5 m/s

5 m/s

(d)

Wind Direction EAST

5 Wind Direction 0 EAST

AA5 | EmTech0 m/s | 2013-14 | Dissertation Fig.6.24: Comparison of CDF analyses between Existing patch, Experiment 1 and 2 (a) 100 m Height (b) 150 m Height

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150 metres

Adaptable Morphodynamics

6.4 LIMITATIONS

Fig.6.25: View from the seafront

FLUID DYNAMIC ANALYSIS

COMPUTATIONAL TOOLS The computational algorithm defined in Grasshopper and associated with the Octopusâ&#x20AC;&#x2122;s evolutionary engine had some restrictions in terms of the number of primitive geometries that it was possible to import and the degree of complexity of the genotype and phenotype.

Thus, it was not feasible to run the experiments by connecting the entire patch at once. It has been necessary to divide it into six parts, each composed of 20 or 30 blocks, in order to finalise the overall result.

As a consequence, the six areas were each developed individually according to specific communal criteria of the general evolutionary strategy. After ranking all generations, the individuals selected for each area were aggregated to compose the final morphological output of the whole patch.

To conclude, the difficulty of connecting a great number of geometries to the algorithm could lead to less accurate results on a global scale, due to the fact that the interdependence of each patchâ&#x20AC;&#x2122;s part is not taken into account for the optimisation. Furthermore, the timescale could represent an additional restriction for further developments with a higher level of complexity, considering that each of the current experiments was run over one week and an additional few days were necessary to extract numeric data and evaluate the results.

There is no straight connection between the Computational Fluid Dynamic analysis and the computational tools, so it was not possible to directly optimise the building morphologies for the wind by using multi-objective criteria for the evolutionary algorithm. This is the reason for exploring several ventilation strategies in order to extract geometrical parameters that could be easily integrated into the GH definition to indirectly achieve an acceptable wind performance.

Moreover, the CFD analysis did not provide accurate results because of the low resolution on an urban scale. As a consequence, we run several analyses to test the wind performance at different scales because results are more precise at the block and building scale. Overall, the wind analysis mainly worked as a visualisation tool for the performance of the urban ventilation through the use of the porosity strategy.

Adaptable Morphodynamics 119

6.5 POROSITY AND PEDESTRIAN CIRCULATION ANALYSIS PEDESTRIAN FLOW - GROUND LEVEL

EXISTING

EXISTING

shown from the comparison AAAs | EmTech | 2013-14 | Dissertationbetween the pedestrian network at the ground floor of the

existing and modified patches, it can be seen how the pedestrian circulation is affected by the percentage of permeability. Indeed, it is expected that an increase in the amount of the floating population, due to the emergence of new open spaces. For this reason, it is evident from both experiments how more porosity at the ground floor level improves mobility around the urban tissue through fluid, accessible and interconnected pedestrian paths. This factor could have a great importance in encouraging inhabitants to use alternative and sustainable means of transport for short journeys.

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EXPERIMENT

EXPERIMENT1

Adaptable Morphodynamics

Fig.6.26: Depth map AnalysisPedestrian flow at ground level, Existing and Experiment 1

6.5 POROSITY AND PEDESTRIAN CIRCULATION ANALYSIS PEDESTRIAN FLOW - GROUND LEVEL

EXISTING

EXISTING

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EXPERIMENT

EXPERIMENT 2

Adaptable Morphodynamics

Fig.6.27: Depth map AnalysisPedestrian flow at ground level, Existing and Experiment 2

Adaptable Morphodynamics 121

7. EXPERIMENT 2: BLOCKS AGGREGATION 7.1 Sub-area 1 7.2 Sub-area 2 7.3 Sub-area 3 7.4 Conclusion

7. EXPERIMENT 2: BLOCKS AGGREGATION Scale PRIMITIVE INPUT

EVOLUTIONARY OUTPUT

SUB-AREA 1

SUB-AREA 2

SUB-AREA 3

Fig.7.1: Exisiting and Experiment 2 Sub-areas, Location in patch

Three different sub-areas, located in significant points of interest, were extracted from the urban fabric with the intent to explore the architectural and environmental qualities of the emergent morphologies at block and building scale. The aim was to analyse three diverse scenarios in terms of typology, density and environmental performance.

Adaptable Morphodynamics 125

7.1 SUB-AREA 1

Fig.7.2: Sub-area1, Existing conditions, solar exposure analysis

Existing Conditions

Evolutionary Computational Output

Solar Exposure

Sub-area 1 is situated on the north-eastern part of the patch and it has a mix of high-density low- and medium-rise buildings. This zone is characterised by a lack of open spaces and inadequate housing. Indeed, an increased number of illegal informal settlements, known as rooftop villages, can be found. Moreover, a medium flow public transportation node, the Sham Shui Po underground station, is located nearby.

As result of the application of a porosity gradient (from low to high), the sub-area was provided with new open spaces with respect to the existing condition. Public, semi-public and semiprivate open spaces were classified according to specific dimensions in order to define their function and scale of influence. In particular, larger portions of open public spaces next to the public transportation node could bring about benefits to the existing poor housing by stimulating social regeneration and inclusionâ&#x20AC;&#x201D; locally and in all neighbourhoods.

A solar analysis was run on the buildings on a smaller scale to get a clear insight into the local micro-climate of the emergent voids over the hottest season, from June to September.

It can be seen that open spaces, which are more enclosed, become shaded, whereas the rooftop surfaces of tallest buildings are the most exposed to the sun.

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7.1 SUB-AREA 1

Fig.7.3: Sub-area1, Existing conditions, solar exposure analysis

Morphologies - Emergent Functions Existing and new functions could be accommodated in the volume added to the buildings, and in the voids left by the volume removed. The growth strategy applied to the rooftop surfaces of low- and medium-rise buildings could be translated into a series of new morphologies, able to house new programmes, such as micro-economy and social provisions.

For example, as illustrated in the diagram below, a sky farm can be defined when the growth in medium- or high-rise building blocks has a high percentage of no built-up areas. These building typologies could be more adequate than lower buildings for farming activities, because, as

shown from the solar radiation analysis, their rooftop surfaces are more exposed to the sun.

In addition, the porosity at the ground level can generate space for temporary or permanent open street markets, directly connected with the micro-economy located above.

Public and semi-public activities that require both indoor and outdoor spaces, such as cultural and social provisions, can be housed on the top of low-rise buildings when the percentage of grown volume and open space is nearly equal. These buildings are shaded by their surroundings, and this factor positively contributes to the

thermal comfort of open spaces. In addition, their reduced height allows public services and facilities located on the top to be easily accessible to users.Finally, medium and small voids, placed on the middle levels of buildings, could accommodate semi-public communal areas with facilities and semi-private skygardens, whereas larger areas of open space could be dedicated to public activities, such as exhibition and social gathering, or to vertical gardens for informal and passive recreation.

Adaptable Morphodynamics 127

7.1 SUB-AREA 1

Fig.7.4: Sub-area 1, Multilayers of connectivity, flow profiles

Multi-layers of Connectivity This cluster connects eight blocks through a series of vertical and horizontal footpaths. This network has a circulation and leisure character and it connects the emergent public spaces in the cluster at all levels. The linkage between large areas of public spaces within the is comprised of high flow connections, while a lower level of connectivity is used on the building scale .

The cluster provides direct accessibility to the MTR tube station, which is characterised by an increase in the amount of floating population.

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For this reason, we proposed a series of connections that vary according to each function and the level of populationâ&#x20AC;&#x2122;s flow per hour.

7.1 SUB-AREA 1

Section Existing Patch

A

1

B

2

C

3

D

0 m/s

5 m/s

Section Experiment 2 Minimum Solar Exposure

Experiment 2 Minimum Solar Exposure

Wind Direction EAST 5

0 m/s

Fig.7.5: Sub-area1, CFD Analysis, Sections: Existing and Experiment 2

Computational Fluid Dynamic A 3D CFD simulation was carried out to analyse the effect of the strategies on urban ventilation.

We analysed four urban sections in order to quantify the effects of the parameters on different buildingsâ&#x20AC;&#x2122; morphologies. The high presence of rooftop villages and social services negatively affected the wind ventilation, because these buildings were not included in the porosity and roughness strategies. In addition, it can be observed that the increased buildingsâ&#x20AC;&#x2122; height at points A, B, C and D caused a reduction in air flow at the canopy layer due to the roughness

strategy. However, at points 1, 2, and 3, an increase in the amount of air flow can be seen at the block scale as a result of the porosity strategy.

Micro-climate & Architectural Quality of Open Spaces The resulting morphologies have been analysed further in order to identify the quality of open spaces and define the potential activities that these spaces could house, according to their

thermal comfort, size and the number of users.

Thus, areas characterised by a wind speed greater than 3m/s, could be suitable for water collection and vegetation cover to mitigate the Urban Heat Island effect. On the other hand, open spaces with a value of air flow between 0 and 3m/s could be considered zones for leisure and recreational activities.

Adaptable Morphodynamics 129

7.1 SUB-AREA 1

Wood Albedo 0.1

5

Wind Speed 0 m/s

0.35

0

Grass Albedo 0.16

Wood Albedo 0.1

Grass Albedo 0.16

Water Albedo 0.29

CULTURAL 0 - 1 m/s (Light air)

GREENERY 2- 2.5 m/s (Light brezze)

RECREATION 0 - 1 m/s (light air)

GREENERY 3 - 4 m/s (Moderate Breeze)

WETLAND 3 - 5 m/s (Moderate brezze)

Public Space Street Gallery

Comunal Space Semi Private Space

Sports Events

Comunal space Vegetation

Low vegetation Water Collection

Albedo

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Fig.7.6: Architectural approach to the emergent open space

7.2 SUB-AREA 2

Fig.7.7: Subarea 2, Existing conditions, solar exposure analysis

Existing Conditions

Evolutionary Computational Output

Solar Exposure

Sub-area 2 is located in the north-western part of the patch and is characterised by a combination of high-density low- and medium-rise buildings.

Although this area has poor housing, for instance rooftop villages and no public spaces, it has a school as a main social feature.

Sub-area 2 showed a massive increase in the number of public and semi-private open spaces, completely lacking in the existing urban tissue.

Furthermore, the total surface area of semipublic space rose considerably from 2.817 m² to 18.865 m². This was possible thanks to the application of a high porosity gradient to different blocks.

The solar radiation analysis for sub-area 2 showed results similar to those of sub-area 1, due to the presence of buildings with the same ranges of height. While the enclosed open spaces are shaded, the square, where the school is located, is highly exposed to the sun.

Adaptable Morphodynamics 131

7.2 SUB-AREA 2

Fig.7.8: Sub-area 2, Existing conditions, solar exposure analysis

Morphologies - Emergent Functions The increased volume could accommodate new housing, allowing reallocation of part of the initial residential volume removed through the porosity strategy. For instance, this could happen when the percentage of built volume is significantly greater than that one of open areas. Moreover, other public or semi-public programmes that necessitate larger outdoor spaces, such as sportive centres or open green areas, could also be located on the rooftop level of low- and medium-rise building blocks because they are more shaded. Finally, communal areas and semi132 Emergent Technologies and Design | AA |

private terraces, for exclusive use of residents, could be placed on the top floors of buildings.

7.2 SUB-AREA 2

Fig.7.9: Sub-area 2, Multilayers of connectivity, flow profiles

Multi-layers of Connectivity This area has a low flow level of connectivity, thus blocks are not linked to each other. Only buildings that belong to the same block connect to one another, providing internal access to several types of open spaces, located on multiple levels. This vertical and horizontal circulation generates a dynamic pedestrian network that connects the communal and public spaces in each block.

Adaptable Morphodynamics 133

7.2 SUB-AREA 2

Section Existing Patch A 1

B

2

C

3

0 m/s

5 m/s

Section Experiment 2 Minimum Solar Exposure

Experiment 2 Minimum Solar Exposure

Wind Direction EAST 5

0 m/s

Fig.7.10: Sub-area 2, CFD Analysis, Sections: Existing and Experiment 2

Computational Fluid Dynamic

Micro-climate & Architectural Quality of Open Spaces

The height profile of the existing area has only increased in some buildings due to the growth strategy. As shown from the image above, this can be noticed at specific points, such as A, B, C and D, whereas a greater number of open spaces can be found at points 1,2 and 3. In this area, it is observed how the variation in building height is balanced with the porosity, which opens up the buildings at the top-floor levels.

This allows air flow to be redirected from the urban canopy to the pedestrian level, improving the outdoor environmental conditions.

In sub-area 2, open spaces characterised by a value of air flow from 0m/s to 1m/s could be considered as areas for leisure activities, while wind speeds higher than 3m/s could define wetlands zones, composed by ponds for the collection of rainwater and greenery. These elements could create urban biodiversity and a natural environment within the cityscape. Finally, enclosed areas, characterised by a moderate air flow between 0m/s and 1m/s, could host commercial activities or other functions, such as street markets and open-air galleries.

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7.2 SUB-AREA 2

Wood Albedo 0.1

5

Wind Speed 0 m/s

0.35

0

Albedo

Grass Albedo 0.16

Concrete Albedo 0.35

Water Albedo 0.29

RECREATION 1- 2 m/s (Light brezze)

GREENERY 2- 2.5 m/s (Light brezze)

MARKETS 0- 1 m/s (Light air)

WETLAND 3 - 5 m/s (Moderate brezze)

Seating Vegetation

Comunal Space Semi Private Space

Public Space Enclosed space Gathering

Low vegetation Water Collection

Fig.7.11: Architectural approach to the emergent open space

Adaptable Morphodynamics 135

7.3 SUB-AREA 3

Fig.7.12: Sub-area 3, Existing conditions, solar exposure analysis

Existing Conditions

Evolutionary Computational Output

Solar Exposure

Sub-area 3 is located on the southern part of the patch, next to a high-flow tube station, Prince Edward. The zone is mainly constituted by highdensity high-rise building blocks and towers, characterised by low permeability and a mixeduse (residential and commercial) programme.

In sub-area 3, high porosity has been applied to the existing morphologies in order to facilitate the air flow through the patch, previously blocked by the â&#x20AC;&#x2DC;wall effectâ&#x20AC;&#x2122; of the towers. Subarea 3 showed a substantial rise in the number of semi-private open spaces and an increase of around 40 per cent of the original amount of public and semi-public open spaces.

As can be seen from the solar radiation analysis below, the enclosed open spaces in high-rise building blocks and towers are characterised by an average value of solar exposure. These spaces tend to be less shaded because of the higher permeability of buildings and the less compact nature of the urban fabric.

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7.3 SUB-AREA 3

Fig.7.13: Sub-area 3, Existing conditions, solar exposure analysis

Morphologies - Emergent Functions No growth is applied to the towers to avoid increasing their height further, which would be a problem for the passage of wind. The emergence of voids underneath the towers functions to allow air flow through the urban fabric. Enclosed open spaces, such as public gardens with facilities or multipurpose plazas, are public at lower levels because they are easily accessible by users, whereas semi-public open spaces are located on top floors.

The open spaces, which are more exposed to sun and wind, are not publicly accessible; however, their integration with greenery, in the form of green roofs, has environmental purposes, such as absorbing humidity and pollution to decrease temperature. On the other hand, the podium structures are broken through a porous system that creates public crosswalks and urban infill, such as small and medium-sized plazas underneath.

Finally, larger areas of public open spaces emerged because of the aggregation of several high-rise building blocks into a cluster, nearby public transportation node. These spaces could allow for the accommodation of an increased number of users.

Adaptable Morphodynamics 137

7.3 SUB-AREA 3

Fig.7.14: Sub-area 3, Multilayers of connectivity, flow profiles

Multi-layers of Connectivity This area has a high-flow level of connectivity and it is formed by the aggregation of seven blocks into a cluster. Different building morphologies are interconnected internally between different blocks and to the existing secondary layer. Large areas of open space in the cluster are connected to other public spaces, located at lower levels of the high-rise buildings. This creates a system of public spaces that gives additional value to the outdoor pedestrian network. Finally, the mutual use of high, active and low-flow links, according to specific areas, is extremely important to 138 Emergent Technologies and Design | AA |

accommodate an estimated population of over 20,000 inhabitants.

7.3 SUB-AREA 3

Section Existing Patch

A

1

2

3

B

4

0 m/s

5 m/s

Section Experiment 2 Minimum Solar Exposure

Experiment 2 Minimum Solar Exposure

Wind Direction EAST 5

0 m/s

Fig.7.15: Sub-area 3, CFD Analysis, Sections: Existing and Experiment 2

Computational Fluid Dynamic Sub-area 3 is characterised by high-rise buildings,high and medium-rise building blocks, and some social provisions. The existing towers, located in the west, block the wind coming from the coast, generating a sort of wall effect. By applying the previous strategies, we predicted to be able to increase urban ventilation through the patch at several height levels. It is noticeable that the general profile of buildings considerably changed in the area. Indeed, the highest porosity of towers at the top-floor levels increased air flow from 0m/s to 3m/s, allowing the air flow to pass through the buildings and

reach other parts of the patch. Although the increase in building height caused a decrease in wind speed, observed only at points A and B, the emergence of open spaces at points 1, 2, 3 and 4 had considerably redirected air flow to other areas at the urban canopy layer. As a consequence, this last factor could reduce high temperatures during the summer in order to provide citizens with a comfortable outdoor environment.

Micro-climate & Architectural Quality of Open Spaces

As a result of the applied strategies, the highrise morphologies show a variety of open spaces, which differ for architectural quality and dimensions. In this specific case, the emergence of public activities will be possible only when wind speed is lower than 1m/s and the spaces are semi-enclosed.

However, areas in which wind speed exceeds the value of 3m/s could be used strictly for water collection; at this height, only low vegetation could be employed to regulate the patchâ&#x20AC;&#x2122;s micro-climate.

Adaptable Morphodynamics 139

7.3 SUBAREA 3

Water Wood Albedo Albedo0.29 0.1

Grass Albedo 0.16

Grass Albedo 0.16

WoodWood AlbedoAlbedo 0.1 0.1

Grass Grass Albedo 0.16 Albedo 0.16

Water Concrete Albedo0.35 0.29 Albedo

COMUNAL AREA WETLAND CULTURAL GREENERY 1.1 - 2.3 m/s 30 - 51 m/s 2- 2.5 m/s (Light air) (Moderate (Light air) brezze) (Light brezze)

LEISURE RECREATION 1 - 3 0m/s - 1 m/s (Gentle (light brezze) air)

PUBLIC SPACE GREENERY 0 - 1 m/s 3 - 4 m/s (Calm) (Moderate Breeze)

COMUNAL WETLANDSPACE 1.13 -- 52.3m/sm/s (Light brezze)brezze) (Moderate

Seating Vegetation

PublicSports Space Events Seating

PUblic Space Comunal space Seating Vegetation Vegetation

Comunal Space Low vegetation Seating Water Collection Vegetation

5

Wind Speed 0 m/s

0.35

0

Low Publicvegetation Space Comunal Space Street Gallery Water Collection Semi Private Space

Albedo

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Fig.7.16: Architectural approach to the emergent open space

7.4 Albedo

ALBEDO Our approach on the emergent open spaces is to propose a configuration of surfaces with high albedo levels that could affect the microclimate created by the urban heat island effect. Several materials with high reflective properties will be integrated into the open spaces to improve environmental conditions by reducing the absorption of the solar energy. The materiality of the surfaces could also define the character of the spaces. The albedo value ranges from 0 to 1. The value of 0 refers to a blackbody, a theoretical media that absorbs 100% of the incident radiation. Albedo ranging from 0.1â&#x20AC;&#x201C;0.2

refers to dark-colored surfaces, such as rough soil, while the values around 0.4â&#x20AC;&#x201C;0.5 represent smooth, light-colored soil surfaces. The albedo of snow cover, especially the fresh, deep snow, can reach as high as 0.9. The value of 1 refers to an ideal reflector surface (an absolute white surface) in which all the energy falling on the surface is reflected (Matthews, 1984).

the proposal includes water collection and low vegetation on the emergent open spaces. In areas where no reflectivity is required, rough surfaces could be used due to their low albedo values.

The Surface roughness defines the type of reflection. Shiny, smooth surfaces, like a body of water, plant leaves or wet soil surfaces have a high performance on reflectivity and therefore Adaptable Morphodynamics 141

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design evaluation

The overall strategy met the initial aim to minimize disruption to around 20% and it almost achieved the relocation target of 40%. The results of the most recent experiment showed that the Growth strategy recovered 33.6% of the Volume removed but the increase in the number of floor reduced the urban ventilation performance with respect to the previous experiment.

The global optimization of the buildingsâ&#x20AC;&#x2122; morphologies shows an increase in urban ventilation only at the top floor levelsâ&#x20AC;&#x2122; of the patch. Some areas, such as in subarea 1, showed no improvement due to the existence of the rooftop villages. In other areas, where the porosity strategy was applied on the high rise towers there was a significant increase in airflow throughout the patch. The CFD analysis demonstrated the overall performance of the airflow but the result tends to vary in accuracy due to the scale and resolution. However, as shown by the experimental results, any porosity will increase air flow but only changes that allow the entrance of airflow from the top levels towards the ground floor can make a relevant improvement on the overall the patch.

As a result, the ratio of open space per inhabitant has been doubled thanks to the porosity strategy for the maximization of the airflow. Although the differentiation in size and functions of the emergent and distributed open spaces brings about diversity in the patch, their location on multiple levels could require a higher complexity of vertical connections to allow a fluid pedestrian mobility.

Adaptable Morphodynamics 143

144 Emergent Technologies and Design | AA |

further development

A further analysis of the local urban microclimate at the building scale could establish better relations between the location of functions, human thermal comfort and quality of the emergent public spaces. The evolutionary genetic algorithm could be refined in order to apply a killing strategy for open spaces and volumetric mass that do not satisfy requirements of size, daylight and thermal comfort.

In addition, building morphologies could be explored over a larger number of generations and seasonal intervals of time, in order to achieve a greater morphological diversity and classify spaces according to their adaptability to different climate conditions, uses and accessibility.

Finally, a thermal analysis on the existing buildingsâ&#x20AC;&#x2122; envelope could be run to get an understanding of the properties of the materials and their reaction to the indoor and outdoor microclimates. Materials with a high solar reflectance (high albedo index) could be adopted for the major urban surfaces such as rooftops, streets, sidewalks, so as to evaluate their cooling energy effect by directly decreasing the heat gain through a buildingâ&#x20AC;&#x2122;s envelope and by lowering the overall urban air.

Adaptable Morphodynamics 145

146 Emergent Technologies and Design | AA |

CONCLUSION

Adaptable Morphodynamics has presented an urban system that enables environmental and spatial qualities through the metamorphosis of urban forms. The siteâ&#x20AC;&#x2122;s climate conditions and social context in Hong Kong played a key role in informing the entire design process in each phase. This lead exploration into new ways of enhancing the existing urban space in relation to urban ventilation and architectural logics. The resulting diversity of new functions and urban microclimates in the emergent open spaces dematerialized the homogeneity of the original patch, by generating a contemporary cityscape able to adapt to the demands of a demographic population density.

Adaptable Morphodynamics 147

APPENDIX

1. hong kong’s water supply

Environmental Problems - Water Supply Dongjiang Fresh Water Resources: Imported vs Local Supply (1965 - 2012)

Hong Kong’s Water Resources (2012) *

18%

( mcm) 100

59%

23%

Imported water (Dongjiang) Local catchment Seawater

90 80 70 60 50

local water supply

imported water

Hong Kong’s Future Water Resources (2020) *

40 30 20

4%

10 1965 1966 1967 19 6 8 1969 1 97 0 1971 1 97 2 1 97 3 1 9 74 1 97 5 1 9 76 1 97 7 1 97 8 1 97 9 19 8 0 1 9 81 1982 1983 19 8 4 1985 1986 1987 1988 1989 19 9 0 1 9 91 1 9 92 1 9 93 1994 1995 1996 1 9 97 1998 1999 20 0 0 20 01 20 02 20 0 3 20 0 4 20 0 5 20 0 6 20 07 20 0 8 20 0 9 2010 2011 2012 year

0

22%

18%

56%

Local catchment Dongjiang Seawater Desalination

* Source: 2014, Liu S., Williams J.,“Different Approaches to water dependency”

AA | EmTech | 2013 -14 | Dissertation

Adaptable Morphogenesis

4. sham shui po district- public transports

4. sham shui po district- markets and retails

5. connectivity: network hierarchy - urban/regional

5. cluster exploration

CLUSTERS - PUBLIC SPACE

Tower

Podium

Rooftop Village

Services

Others

CHARACTER - SOCIAL - RECREATIONAL Public Space Clusters

Vertical Connections

Horizontal Connections Area Public Space Cluster Closest attractor

AA | EmTech | 2013-14 | Dissertation

28.965 m² 4 Blocks Metro - 8 minutes walk

Adaptable Morphodynamics

6. genetic algorithm- Early explorations

POROSITY STRATEGY - BODY PLAN

AA | EmTech | 2013-14 | Dissertation

Adaptable Morphogenesis

6. genetic algorithm- Early explorations

POROSITY STRATEGY - VOLUME REMOVED

AA | EmTech | 2013-14 | Dissertation

Adaptable Morphogenesis

6. EXPERIMENT 1: morphologies

6. EXPERIMENT 1: morphologies

6. EXPERIMENT 1: morphologies

6. EXPERIMENT 1: morphologies

6. EXPERIMENT 1: patch scan- open spaces at podium level

PATCH SCAN PODIUM- CLUSTERS Emerged Open Space Podium

0.75 km 0.50 km 0.25 km

Area - 7.930 m2 No. Blocks - 13 MTR Sham Shui Po Station

0.43 km

Area - 6.528 m2 No. Blocks - 12 Secondary Layer

0.42 km

Area - 4.359 m2 No. Blocks - 4 MTR Prince Edward Station

0.28 km

Area - 14.512 m2 No. Blocks - 4 Secondary Layer Area - 11.578 m2 No. Blocks - 11 Secondary Layer

Emerged Public Space Urban Attractors Public Transpotation Secondary layer Rooftop Villages Services Green areas

0.33 km

0.38 km

AA | EmTech | 2013-14 | Dissertation

Adaptable Morphodynamics

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.1

FITNESS CRITERIA

VOLUME V

SUN EXPOSURE SE

GROUND EXPOSURE GE

GENERATION 1

INDIVIDUAL V SE GE

G1.01 1577613.187 0.732241 116080.2618

G1.02 1576095.248 0.733382 115797.1699

G1.03 1555077.767 0.733533 115850.3429

G1.04 1571432.637 0.733725 115974.9662

G1.05 1583340.938 0.733352 115979.7052

G1.06 1571945.167 0.732431 115910.8733

G1.07 1593134.14 0.732872 116009.8199

G1.08 -1592475.507 0.732745 116006.5702

G1.09 1587929.199 0.733943 116100.3274

G1.10 1585187.897 0.732844 115940.8118

GENERATION 2

INDIVIDUAL V SE GE

G2.01 1591963.008 0.732636 115991.1447

G2.02 1571832.325 0.733575 115974.6432

G203 1593514.842 0.733725 115987.7386

G2.04 1583567.48 0.732572 116005.3533

G2.05 1572959.405 0.733662 116031.6816

G2.06 1590079.009 0.73307 115931.9457

G2.07 1592922.306 0.732745 116024.6786

G2.08 1588452.957 0.73369 116114.5658

G2.09 1586166.012 0.734307 116065.1071

G2.10 1582757.53 0.733535 115983.9445

GENERATION 3

INDIVIDUAL V SE GE

G3.01 1593112.329 0.7337 115993.612

G3.02 1589585.419 0.733984 116114.6083

G3.03 1575497.139 0.733243 116048.9524

G3.04 1598923.448 0.732824 116060.6384

G3.05 1584704.232 0.734168 116074.914

G3.06 1588625.165 0.733755 116113.1754

G3.07 1592727.155 0.733279 116001.9519

G3.08 1589719.046 0.732403 115944.9358

G3.09 1592453.029 0.733673 116126.2862

G3.10 1590387.556 0.733145 115932.8251

GENERATION 4

INDIVIDUAL V SE GE

G4.01 1597168.199 0.732707 116019.1243

G4.02 1594999.132 0.732903 116040.2795

G4.03 1585267.517 0.734372 116083.1623

G4.04 1594016.581 0.733624 116147.5931

G4.05 1594974.962 0.733621 116123.0331

G4.06 1594902.364 0.733664 116023.2099

G4.07 1590801.962 0.733547 116130.8074

G4.08 1597170.873 0.732976 116033.7283

G4.09 1598227.839 0.732569 116080.2405

G4.10 1592561.589 0.733352 115997.7485

GENERATION 5

INDIVIDUAL V SE GE

G5.01 1595411.469 0.732684 116175.5981

G5.02 1594746.527 0.733703 115963.8049

G5.03 1585525.775 0.734638 116088.412

G5.04 1585571.559 0.734178 116102.2323

G5.05 1607520.056 0.732549 116039.5472

G5.06 1579536.881 0.732825 116004.9143

G5.07 1595882.609 0.733714 116029.1884

G5.08 1594310.549 0.733668 116098.7281

G5.09 1593135.413 0.733793 116148.9252

G5.10 1599223.589 0.732495 116078.7839

GENERATION 6

INDIVIDUAL V SE GE

G6.01 1587684.434 0.734539 116100.2647

G6.02 1584780.852 0.7344 116084.1998

G6.03 1585798.6 0.733781 116093.7343

G6.04 1592773.386 0.733679 116091.7737

G6.05 1594615.262 0.734544 116145.996

G6.06 1597753.491 0.733233 115982.9282

G6.07 1592306.812 0.733621 116091.9931

G6.08 1593687.215 0.733484 116102.6081

G6.09 1593639.394 0.733499 116112.4855

G6.10 1587297.849 0.734679 116083.8489

GENERATION 7

INDIVIDUAL V SE GE

G7.01 1593055.77 0.733766 116099.4932

G7.02 1595161.405 0.733894 116105.8061

G7.03 1593621.679 0.734368 116135.2601

G7.04 1590551.217 0.734218 116129.9112

G7.05 1588201.221 0.734152 116129.7559

G7.06 1591858.512 0.733831 116073.5112

G7.07 1591026.704 0.733324 115967.6332

G7.08 1596699.24 0.732949 116094.0727

G7.09 1590355.088 0.734099 116128.9564

G7.10 1596794.293 0.73303 115957.7204

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.1

GENERATION 8

INDIVIDUAL V SE GE

G8.01 1594113.643 0.73389 116138.1943

G8.02 1593507.075 0.733162 116121.5497

G8.03 1590690.788 0.733528 116185.6092

G8.04 1598269.786 0.733732 116095.2307

G8.05 1593175.433 0.733918 116123.2216

G8..06 1594015.383 0.733216 116090.8527

G8.07 1596713.269 0.733679 116105.2129

G8.08 1590017.908 0.733782 116155.7013

G8.09 1591172.441 0.734195 116120.8792

G8.10 1596827.424 0.732957 115934.5313

GENERATION 9

INDIVIDUAL V SE GE

G9.01 1594009.005 0.732907 116106.9329

G9.02 1595354.459 0.733496 116155.1164

G9.03 1590233.272 0.733503 116094.3701

G9.04 1600479.865 0.733186 116099.8226

G9.05 1585808.64 0.73351 116112.9823

G9.06 1591628.898 0.734114 116072.4971

G9.07 1594946.936 0.733741 116136.3197

G9.08 1594070.245 0.733063 116191.3242

G9.09 1593196.43 0.733691 116099.5001

G9.10 1595932.786 0.733707 116146.6829

GENERATION 10

INDIVIDUAL V SE GE

G10.01 1597391.879 0.733348 116167.8925

G10.02 1593908.082 0.73367 116108.547

G10.03 1593106.325 0.733358 116147.6699

G10.04 1591459.067 0.733296 116094.3998

G10.05 1592776.842 0.733367 116116.9999

G10.06 1591269.809 0.733197 116097.2068

G10.07 1592994.707 0.733873 116119.5339

G10.08 1598194.765 0.733318 116207.5689

G10.09 1588114.534 0.732831 116048.7496

G10.10 1596634.451 0.734515 116147.4609

GENERATION 11

INDIVIDUAL V SE GE

G11.01 1597247.521 0.732962 116203.4367

G11.02 1597323.66 0.733453 116130.6848

G11.03 1591329.524 0.733346 116074.2892

G11.04 1595308.613 0.733461 116139.7647

G11.05 1597892.637 0.733567 116171.5308

G11.06 1592903.993 0.733627 116096.3273

G11.07 1588685.292 0.733538 116110.211

G11.08 1590997.76 0.733114 116091.2428

G11.09 1593693.925 0.734335 116147.8023

G11.10 1599208.907 0.733432 116138.041

GENERATION 12

INDIVIDUAL V SE GE

G12.01 1593258.263 0.732802 116136.5818

G12.02 1588483.92 0.7337 116086.8328

G1203 1596351.344 0.733101 116196.5732

G12.04 1598028.302 0.733588 116080.1503

G12.05 1588439.046 0.734447 116066.422

G12.06 1595535.658 0.733748 116146.789

G12.07 1598768.241 0.733559 116119.778

G12.08 1584258.364 0.733457 116114.4806

G12.09 1591008.865 0.732594 116125.7551

G12.10 1604092.948 0.733575 116220.1162

GENERATION 13

INDIVIDUAL V SE GE

G13.01 1594783.91 0.734193 116120.5529

G13.02 1598220.483 0.733637 116075.42

G13.03 1597351.393 0.7338 116122.7372

G13.04 1596818.612 0.734133 116180.5729

G13.05 1592335.115 0.733053 116078.8049

G13.06 1600478.046 0.73294 116120.7437

G13.07 1594672.387 0.73442 116090.1541

G13.08 1602405.623 0.733768 116108.5238

G13.09 1602727.239 0.732785 116203.8363

G13.10 1590460.694 0.733404 116138.2306

GENERATION 14

INDIVIDUAL V SE GE

G14.01 1601176.416 0.733939 116128.8401

G14.02 1594379.213 0.733948 116104.7766

G14.03 1595471.847 0.734327 116095.739

G14.04 1594560.247 0.734679 116102.5937

G14.05 1602277.349 0.733825 116109.7115

G14.06 1602000.033 0.733912 116110.3495

G14.07 1592527.629 0.733835 116101.4457

G14.08 1603633.486 0.732751 116175.646

G14.09 1595705.835 0.733474 116196.1863

G14.10 1603887.968 0.734072 116184.9654

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.1

GENERATION 15

INDIVIDUAL V SE GE

G15.01 1600570.747 0.733742 116113.9758

G15.02 1600139.921 0.733676 116096.8459

G15.03 1600787.069 0.733979 116117.9436

G15.04 1602731.431 0.73305 116171.6473

G15.05 1600363.979 0.732652 116169.274

G15.06 1605039.17 0.7331 116166.5057

G15.07 1599099.43 0.734181 116094.7951

G15.08 1598034.153 0.733458 116125.8027

G15.09 1598811.71 0.734148 116106.7992

G15.10 1597289.407 0.73398 116099.231

GENERATION 16

INDIVIDUAL V SE GE

G16.01 1602310.137 0.73319 116118.7242

G16.02 1597127.935 0.733268 116162.5616

G16.03 1608970.203 0.733194 116197.6763

G16.04 1596869.812 0.733175 116087.8582

G16.05 1593775.349 0.733199 116106.8438

G16.06 1604268.064 0.73349 116162.1885

G16.07 1604862.825 0.733103 116177.1868

G16.08 1598156.261 0.734131 116094.9684

G16.09 1598632.661 0.733994 116100.979

G16.10 1600600.887 0.734019 116120.7948

GENERATION 17

INDIVIDUAL V SE GE

G17.01 1597834.65 0.733368 116164.1009

G17.02 1601401.189 0.733996 116121.2612

G17.03 1601151.016 0.733853 116122.3302

G17.04 1601003.921 0.733886 116120.7948

G17.05 1593253.525 0.733289 116099.0069

G17.06 1599664.324 0.733997 116118.9389

G17.07 1607655.597 0.733045 116186.9978

G17.08 1591725.819 0.733249 116100.7063

G17.09 1602025.752 0.734082 116119.7613

G17.10 1598547.04 0.733739 116131.8285

GENERATION 18

INDIVIDUAL V SE GE

G18.01 1608867.65 0.733091 116195.0055

G18.02 1599450.378 0.733716 116122.5919

G18.03 1606668.562 0.732884 116196.4455

G18.04 1600269.586 0.73432 116092.3267

G18.05 1596369.431 0.733845 116129.6164

G18.06 1599503.654 0.733935 116119.1807

G18.07 1604550.857 0.733591 116161.7888

G18.08 1604126.548 0.733374 116139.3742

G18.09 1592230.322 0.732997 116147.8585

G18.10 1600656.088 0.73375 116151.9788

GENERATION 19

INDIVIDUAL V SE GE

G19.01 1601768.924 0.733134 116149.2455

G19.02 1602783.135 0.733778 116155.231

G19.03 1604522.217 0.733866 116155.5735

G19.04 1603702.995 0.733596 116166.8964

G19.05 1602788.654 0.734117 116106.8631

G19.06 1598862.005 0.734003 116077.2786

G19.07 1609382.595 0.733313 116196.1769

G19.08 1609603.394 0.733079 116188.0901

G19.09 1597011.379 0.732886 116115.412

G19.10 1608525.22 0.733804 116173.3633

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.2

FITNESS CRITERIA

VOLUME V

SUN EXPOSURE SE

GROUND EXPOSURE GE

GENERATION 1

INDIVIDUAL V SE GE

G1.01 2314499.995 0.775255 109529.5996

G1.02 2304458.066 0.775158 109646.8081

G1.03 2277438.097 0.774434 109430.9272

G1.04 2308741.729 0.774806 109517.1701

G1.05 2321477.973 0.775904 109577.46

G1.06 2310208.744 0.774721 109540.7879

G1.07 2324929.689 0.775931 109605.1147

G1.08 2276565.084 0.775561 109656.7638

G1.09 2294794.234 0.776239 109657.6045

G1.10 2293378.326 0.775274 109583.5126

GENERATION 2

INDIVIDUAL V SE GE

G2.01 2307209.941 0.775287 109475.4348

G2.02 2304379.844 0.774467 109646.5697

G203 2303200.149 0.775024 109649.9703

G2.04 2311199.106 0.775207 109644.4211

G2.05 2327241.893 0.774864 109639.2521

G2.06 2310207.726 0.776016 109588.1701

G2.07 2290452.725 0.774739 109540.736

G2.08 2321937.719 0.775938 109610.8121

G2.09 2335993.543 0.773809 109594.8329

G2.10 2306297.708 0.775795 109585.6151

GENERATION 3

INDIVIDUAL V SE GE

G3.01 2330133.352 0.773694 109560.6285

G3.02 2312480.191 0.775855 109488.9483

G3.03 2309637.833 0.776126 109597.5848

G3.04 2311091.417 0.775552 109613.2652

G3.05 2304291.128 0.775465 109660.895

G3.06 2321335.132 0.77584 109617.0345

G3.07 2302388.051 0.774742 109654.6985

G3.08 2305715.805 0.77423 109665.9365

G3.09 2309060.011 0.774187 109571.0996

G3.10 2314541.576 0.774997 109669.2019

GENERATION 4

INDIVIDUAL V SE GE

G4.01 2302344.326 0.774964 109553.3109

G4.02 2317451.241 0.775981 109600.4084

G4.03 2322526.414 0.776023 109625.0513

G4.04 2330648.982 0.773682 109586.9916

G4.05 2314726.878 0.774919 109588.3761

G4.06 2315074.803 0.773532 109564.4488

G4.07 2309414.337 0.774169 109655.3273

G4.08 2335389.048 0.77362 109542.7481

G4.09 2309939.913 0.775706 109569.3586

G4.10 2301438.822 0.773388 109617.601

GENERATION 5

INDIVIDUAL V SE GE

G5.01 2309843.482 0.773773 109528.3628

G5.02 2322738.008 0.775849 109653.8373

G5.03 2323630.934 0.775532 109687.8658

G5.04 2302622.979 0.775644 109595.4975

G5.05 2319619.844 0.775881 109579.2362

G5.06 2302380.929 0.775326 109547.1166

G5.07 2332766.309 0.7734 109544.7567

G5.08 2332560.668 0.773514 109590.9137

G5.09 2332818.374 0.776221 109614.3109

G5.10 2309341.289 0.775837 109647.3457

GENERATION 6

INDIVIDUAL V SE GE

G6.01 2327781.704 0.776523 109584.0721

G6.02 2336104.818 0.776545 109620.556

G6.03 2302276.603 0.77451 109518.3728

G6.04 2332261.476 0.776216 109606.2468

G6.05 2340547.767 0.77344 109579.4169

G6.06 2334424.043 0.776235 109634.3604

G6.07 2321007.805 0.775979 109577.0594

G6.08 2322273.608 0.775292 109700.4238

G6.09 2321312.544 0.775381 109544.469

G6.10 2330167.726 0.773539 109565.4771

GENERATION 7

INDIVIDUAL V SE GE

G7.01 2323179.389 0.775157 109695.4382

G7.02 2327162.085 0.775359 109696.0051

G7.03 2334522.323 0.77591 109605.4529

G7.04 2329720.472 0.776277 109606.0695

G7.05 2343964.087 0.773413 109652.0952

G7.06 2320269.854 0.775425 109492.7225

G7.07 2332084.561 0.776114 109606.2285

G7.08 2334579.864 0.776702 109624.0844

G7.09 2335245.201 0.776417 109644.5211

G7.10 2324175.975 0.774618 109519.7978

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.2

GENERATION 8

INDIVIDUAL V SE GE

G8.01 2331231.82 0.777137 109633.2819

G8.02 2329295.453 0.776303 109593.6272

G8.03 2328042.672 0.775788 109680.4988

G8.04 2321902.054 0.774857 109660.952

G8.05 2333586.674 0.775792 109595.7934

G8..06 2325330.47 0.774292 109642.173

G8.07 2333271.944 0.77525 109674.8251

G8.08 2335694.081 0.773655 109553.4543

G8.09 2333825.185 0.775283 109716.0542

G8.10 2317548.676 0.775292 109701.1603

GENERATION 9

INDIVIDUAL V SE GE

G9.01 2330094.937 0.776873 109629.4237

G9.02 2334734.086 0.773598 109476.2773

G9.03 2325916.428 0.775662 109681.122

G9.04 2348102.866 0.774843 109744.1921

G9.05 2326706.948 0.774946 109689.5819

G9.06 2328396.763 0.775337 109695.5491

G9.07 2333651.57 0.775457 109715.9058

G9.08 2334445.32 0.776336 109625.6593

G9.09 2334906.435 0.774632 109587.3961

G9.10 2326052.498 0.775302 109654.0316

GENERATION 10

INDIVIDUAL V SE GE

G10.01 2326273.856 0.775937 109732.5151

G10.02 2341576.446 0.775436 109667.1586

G10.03 2334110.336 0.775431 109465.8884

G10.04 2331640.827 0.77487 109642.2524

G10.05 2328614.878 0.774211 109649.84

G10.06 2340055.059 0.775887 109789.6083

G10.07 2317743.851 0.776933 109689.4367

G10.08 2346102.643 0.7743 109682.9586

G10.09 2321386.646 0.776831 109751.8506

G10.10 2347878.258 0.774125 109667.3702

GENERATION 11

INDIVIDUAL V SE GE

G11.01 2338440.726 0.774341 109677.6309

G11.02 2350220.088 0.775404 109652.2615

G11.03 2345450.355 0.776631 109789.7745

G11.04 2318482.809 0.776243 109781.5509

G11.05 2327481.449 0.775526 109705.7934

G11.06 2322402.75 0.775477 109721.5484

G11.07 2336986.873 0.775852 109796.4122

G11.08 2317754.912 0.776366 109780.9023

G11.09 2350878.335 0.774574 109650.3707

G11.10 2341804.081 0.774824 109679.3026

GENERATION 12

INDIVIDUAL V SE GE

G12.01 2336547.107 0.775901 109765.2436

G12.02 2337480.69 0.776082 109823.3721

G1203 2350014.805 0.775842 109671.0179

G12.04 2352172.008 0.775956 109810.2731

G12.05 2336546.784 0.77633 109764.2823

G12.06 2332208.907 0.775051 109794.7347

G12.07 2347235.285 0.775541 109739.9936

G12.08 2327664.506 0.776635 109743.3327

G12.09 2321130.36 0.775264 109788.4036

G12.10 2309443.079 0.775928 109701.2975

GENERATION 13

INDIVIDUAL V SE GE

G13.01 2346794.443 0.776611 109812.193

G13.02 2333421.833 0.776927 109797.9285

G13.03 2347344.414 0.77552 109697.1677

G13.04 2354383.262 0.776118 109784.3742

G13.05 2345953.753 0.775445 109724.6857

G13.06 2349028.816 0.776034 109860.669

G13.07 2328312.656 0.775326 109773.8303

G13.08 2331014.141 0.775617 109751.9791

G13.09 2339162.25 0.776225 109831.9694

G13.10 2343720.743 0.775147 109672.9438

GENERATION 14

INDIVIDUAL V SE GE

G14.01 2355735.577 0.77646 109800.1228

G14.02 2353539.633 0.776348 109770.1923

G14.03 2347365.642 0.77693 109829.9916

G14.04 2347079.412 0.776458 109796.1376

G14.05 2325971.244 0.77479 109778.0778

G14.06 2354249.853 0.776023 109729.763

G14.07 2326415.548 0.775391 109751.516

G14.08 2361413.331 0.777221 109762.8043

G14.09 2352280.697 0.775944 109866.3722

G14.10 2355941.85 0.775832 109851.7266

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.2

GENERATION 15

INDIVIDUAL V SE GE

G15.01 2348580.009 0.775875 109839.8237

G15.02 2348050.217 0.777056 109818.111

G15.03 2359213.521 0.776067 109861.8836

G15.04 2365141.575 0.775882 109866.6162

G15.05 2348582.965 0.777152 109819.7386

G15.06 2351432.494 0.775901 109753.1147

G15.07 2352693.072 0.775759 109847.2816

G15.08 2355585.222 0.776858 109827.9365

G15.09 2355474.829 0.776498 109815.4756

G15.10 2337244.819 0.776007 109750.61

GENERATION 16

INDIVIDUAL V SE GE

G16.01 2357286.493 0.775554 109822.2668

G16.02 235 4117.805 0.776857 109813.8812

G16.03 2351421.67 0.775483 109826.6916

G16.04 2359070.821 0.776073 109864.7128

G16.05 2345355.47 0.77665 109829.8005

G16.06 2364324.539 0.776914 109831.1571

G16.07 2354736.367 0.776507 109842.9097

G16.08 2346965.106 0.776782 109805.1826

G16.09 2356632.68 0.776363 109819.7745

G16.10 2355406.406 0.776277 109818.6314

GENERATION 17

INDIVIDUAL V SE GE

G17.01 2368391.148 0.776969 109831.4681

G17.02 2357236.916 0.776378 109838.7747

G17.03 2358366. 675 0.776495 109837.2478

G17.04 2354207.178 0.775273 109857.8345

G17.05 2352389.78 0.776208 109907.9417

G17.06 2359959.29 0.776326 109779.4466

G17.07 2358165.009 0.776311 109824.012

G17.08 2356136.093 0.77704 109797.1747

G17.09 2358249.549 0.776918 109850.9331

G17.10 2362328.508 0.775966 109845.4065

GENERATION 18

INDIVIDUAL V SE GE

G18.01 2357044.087 0.776442 109877.9495

G18.02 2353899.625 0.775721 109818.2056

G18.03 2362244.01 0.776669 109856.1769

G18.04 2368159.339 0.776235 109809.9198

G18.05 235 7016.513 0.776594 109893.1985

G18.06 2361861.08 0.776417 109801.2356

G18.07 2367638.257 0.777098 109823.2052

G18.08 2356977.913 0.776648 109797.7338

G18.09 2360238.474 0.775914 109846.1947

G18.10 2361715.753 0.775105 109891.5893

GENERATION 19

INDIVIDUAL V SE GE

G19.01 2356389.632 0.776396 109889.914

G19.02 2354509.007 0.776145 109807.6793

G19.03 2348751.395 0.776746 109879.9094

G19.04 2362540.192 0.776553 109823.4173

G19.05 2370091.287 0.776971 109839.5701

G19.06 23470 56.666 0.776061 109840.9835

G19.07 2368203.715 0.776181 109817.7759

G19.08 2359367.571 0.776358 109811.307

G19.09 2361001.531 0.776682 109862.8255

G19.10 2368822.518 0.77654 109821.3854

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.3

FITNESS CRITERIA

VOLUME V

SUN EXPOSURE SE

GENERATION 1

INDIVIDUAL V SE GE

G1.01 5807820.699 0.775791 297251.5223

G1.02 5805573.847 0.777863 297205.6306

G1.03 5791777.761 0.775966 297306.2069

G1.04 5810250.968 0.777799 297192.0252

G1.05 5829564.81 0.776186 297023.4301

G1.06 5759253.252 0.776727 297169.2724

G1.07 5830224.486 0.778725 297024.2883

G1.08 5782277.138 0.776498 297064.7242

G1.09 5845410.134 0.776263 297047.4789

G1.10 5815780.381 0.777108 297080.447

GENERATION 2

INDIVIDUAL V SE GE

G2.01 5818592.789 0.776162 296974.9572

G2.02 5777302.784 0.776862 297225.3946

G203 5763045.343 0.776368 297125.4245

G2.04 5773258.787 0.777289 297092.129

G2.05 5786841.425 0.776457 297061.9181

G2.06 5757110.949 0.776314 297233.0649

G2.07 5804560.021 0.777895 297216.8748

G2.08 5811027.937 0.777808 297240.5648

G2.09 5836225.246 0.775901 297009.3945

G2.10 5804572.632 0.776699 297256.882

GENERATION 3

INDIVIDUAL V SE GE

G3.01 5813783.938 0.777179 296961.2324

G3.02 5838291.942 0.775194 296986.2522

G3.03 5805343.019 0.777668 297206.0523

G3.04 5778349.321 0.776644 297206.881

G3.05 5851045.272 0.77637 297130.3948

G3.06 5791278.921 0.777222 297137.6136

G3.07 5798857.815 0.776484 297121.8688

G3.08 5802429.115 0.776893 296980.1122

G3.09 5809320.91 0.77824 297255.3926

G3.10 5805976.121 0.777712 297241.6924

GENERATION 4

INDIVIDUAL V SE GE

G4.01 5852465.59 0.776233 297187.8229

G4.02 5846856.116 0.776384 297101.4956

G4.03 5801648.256 0.776962 296997.1157

G4.04 5805965.536 0.778199 297271.8074

G4.05 5803512.49 0.778213 297228.7397

G4.06 5809207.95 0.778468 297226.0514

G4.07 5789612.131 0.7769 297065.8985

G4.08 5817783.982 0.77674 296948.2391

G4.09 5801975.393 0.776577 297018.3737

G4.10 5803515.446 0.777801 297227.4951

GENERATION 5

INDIVIDUAL V SE GE

G5.01 5849365.414 0.776179 297122.3964

G5.02 5803629.675 0.778172 297274.2527

G5.03 5805660.778 0.778515 297246.1374

G5.04 5810088.735 0.778344 297286.5371

G5.05 5776066.055 0.776515 297155.5923

G5.06 5857417.942 0.776509 297181.7855

G5.07 5810292.351 0.776699 296905.1633

G5.08 5805176.445 0.778295 297227.0141

G5.09 5820663.722 0.777635 297254.2343

G5.10 5785444.717 0.77723 297110.7129

GENERATION 6

INDIVIDUAL V SE GE

G6.01 5808732.929 0.777394 297433.4727

G6.02 5845281.339 0.777187 296977.3352

G6.03 5828916.018 0.776194 297135.6108

G6.04 5834818.582 0.776654 296892.9933

G6.05 5867278.12 0.776981 297346.4608

G6.06 5819753.74 0.777077 297109.5199

G6.07 5811071.787 0.778124 297260.041

G6.08 5807658.55 0.778446 297231.2451

G6.09 5817881.376 0.777593 297110.282

G6.10 5844846.277 0.776332 297200.1518

GENERATION 7

INDIVIDUAL V SE GE

G7.01 5846175.131 0.777242 297030.6002

G7.02 5815766.771 0.778721 297217.6263

G7.03 5809129.626 0.778124 297246.4133

G7.04 5844420.506 0.776954 297009.9787

G7.05 5813497.994 0.778254 297230.8679

G7.06 5843779.494 0.776263 297159.3831

G7.07 5809648.646 0.777711 297344.6894

G7.08 5865863.405 0.777727 297289.4979

G7.09 5811189.384 0.778446 297229.7554

G7.10 5866419.515 0.777324 297321.0668

GROUND EXPOSURE GE

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.3

GENERATION 8

INDIVIDUAL V SE GE

G8.01 5874356.468 0.777642 297357.7625

G8.02 5812610.314 0.777744 297226.6312

G8.03 5818729.804 0.777878 297244.258

G8.04 5845392.048 0.776914 297073.0573

G8.05 5874073.798 0.776903 297243.6687

G8..06 5848744.479 0.777364 297361.7456

G8.07 5806647.1 0.777507 297362.3037

G8.08 5853888.737 0.777 297270.0051

G8.09 5827723.693 0.777759 297302.2957

G8.10 5851506.902 0.77738 297287.9302

GENERATION 9

INDIVIDUAL V SE GE

G9.01 5814766.558 0.777548 297359.7113

G9.02 5822696.797 0.777504 297238.8631

G9.03 5837101.519 0.776399 297399.3351

G9.04 5830373.394 0.778515 297212.1949

G9.05 5803840.459 0.777467 297128.2355

G9.06 5865145.696 0.776731 297315.3006

G9.07 5804432.796 0.777275 297169.1271

G9.08 5817886.783 0.777382 297281.9973

G9.09 5810058.983 0.777161 297214.1633

G9.10 5821343.569 0.777296 297110.9865

GENERATION 10

INDIVIDUAL V SE GE

G10.01 5809288.73 0.777776 297371.3852

G10.02 5829364.751 0.777164 297319.4477

G10.03 5821538.7 0.777216 297266.1215

G10.04 5829331.491 0.77721 297369.5316

G10.05 5833661.553 0.777884 297152.6962

G10.06 5829883.011 0.777951 297246.7515

G10.07 5810932.578 0.777556 297303.8607

G10.08 5828049.623 0.777868 297330.3607

G10.09 5837411.479 0.778104 297166.4312

G10.10 5809939.582 0.77777 297259.5765

GENERATION 11

INDIVIDUAL V SE GE

G11.01 5841053.066 0.777547 297353.4837

G11.02 5806165.485 0.777898 297322.7484

G11.03 5820510.35 0.77777 297399.4023

G11.04 5843908.2 0.777906 297252.7426

G11.05 5823495.598 0.77839 297158.621

G11.06 5840805.506 0.778118 297155.3763

G11.07 5834359.253 0.777558 297229.6098

G11.08 5845795.32 0.777738 297267.8424

G11.09 5823985.312 0.777564 297379.0566

G11.10 5843967.467 0.777343 297211.4929

GENERATION 12

INDIVIDUAL V SE GE

G12.01 5839285.535 0.778077 297334.2144

G12.02 5828373.143 0.77772 297186.231

G1203 5835848.936 0.777727 297300.195

G12.04 5846722.891 0.777994 297149.6803

G12.05 5851861.309 0.777855 297259.197

G12.06 5816397.028 0.777269 297352.7349

G12.07 5842328.32 0.777801 297181.9103

G12.08 5825805.637 0.77804 297142.0362

G12.09 5850669.169 0.77813 297141.6877

G12.10 5836434.627 0.777597 297291.4712

GENERATION 13

INDIVIDUAL V SE GE

G13.01 5827317.891 0.777708 297193.3724

G13.02 5821136.539 0.778068 297294.1016

G13.03 5829021.273 0.777275 297260.9197

G13.04 5837233.16 0.778043 297376.4508

G13.05 5842320.865 0.77809 297125.2465

G13.06 5844402.247 0.777683 297191.6004

G13.07 5835666.579 0.777699 297316.4544

G13.08 5834942.862 0.777906 297184.5363

G13.09 5835207.63 0.777819 297111.9173

G13.10 5836389.181 0.777456 297296.8245

GENERATION 14

INDIVIDUAL V SE GE

G14.01 5838518.97 0.777691 297316.1211

G14.02 5828730.711 0.777639 297184.1662

G14.03 5836180.192 0.778125 297386.9358

G14.04 5843843.776 0.778123 297127.954

G14.05 5849468.043 0.777111 297212.8695

G14.06 5815804.165 0.777564 297349.3619

G14.07 5825689.337 0.777537 297193.3883

G14.08 5835088.646 0.778098 297379.9035

G14.09 5834855.477 0.777588 297190.588

G14.10 5841156.369 0.777717 297144.3641

6. EXPERIMENT 2: OCTOPUS DATA HIGH POROSITY AREA A1.3

GENERATION 15

INDIVIDUAL V SE GE

G15.01 5835295.239 0.777549 297390.9941

G15.02 5819455.147 0.777583 297270.2963

G15.03 5834252.816 0.777456 297133.1658

G15.04 5831853.502 0.777974 297172.2596

G15.05 5864703.575 0.777867 297245.5309

G15.06 5814036.88 0.778552 297281.7086

G15.07 5829634.438 0.777528 297306.9662

G15.08 5842323.14 0.778098 297401.6084

G15.09 5824238.146 0.777535 297227.4259

G15.10 5842143.381 0.7784 297270.5154

GENERATION 16

INDIVIDUAL V SE GE

G16.01 5835064.898 0.778015 297400.613

G16.02 5841886.582 0.777961 297431.6618

G16.03 5839900.502 0.77814 297281.6255

G16.04 5841840.897 0.778187 297294.9141

G16.05 5845421.159 0.778714 297324.7374

G16.06 5834560.66 0.777482 297316.2685

G16.07 5859154.318 0.777647 297375.239

G16.08 5815499.528 0.778296 297228.3068

G16.09 5833556.31 0.777886 297426.0162

G16.10 5846790.715 0.777801 297318.7664

GENERATION 17

INDIVIDUAL V SE GE

G17.01 5843833.694 0.778413 297317.0774

G17.02 5849548.587 0.778583 297312.2402

G17.03 5826434.651 0.778118 297297.9068

G17.04 5848600.127 0.777839 297288.255

G17.05 5862892.57 0.777919 297396.9808

G17.06 5846901.454 0.778172 297401.1256

G17.07 5860386.675 0.777606 297333.7909

G17.08 5858171.488 0.777639 297363.5919

G17.09 5831257.329 0.778394 297333.589

G17.10 5851279.21 0.778679 297406.4612

GENERATION 18

INDIVIDUAL V SE GE

G18.01 5857100.053 0.777959 297324.6106

G18.02 5851997.315 0.777886 297418.0022

G18.03 5854667.202 0.777629 297420.3114

G18.04 5868889.558 0.778661 297404.9265

G18.05 5840281.034 0.778144 297404.5561

G18.06 5875200.666 0.778605 297409.9468

G18.07 5849759.937 0.77846 297414.741

G18.08 5843903.926 0.77833 297320.0018

G18.09 5830180.614 0.777863 297300.4095

G18.10 5841417.792 0.778413 297365.4342

GENERATION 19

INDIVIDUAL V SE GE

G19.01 5858900.028 0.777945 297349.5071

G19.02 5856715.243 0.778069 297336.7426

G19.03 5844981.893 0.778248 297368.4975

G19.04 5854661.797 0.778528 297414.5117

G19.05 5853772.826 0.777587 297417.3658

G19.06 5868930.459 0.778483 297411.2312

G19.07 5854986.449 0.77772 297334.759

G19.08 5857798.785 0.778335 297416.5613

G19.09 5853685.141 0.777654 297408.8861

G19.10 5862983.649 0.777737 297460.5971

6. EXPERIMENT 2: ranking high POROSITY AREA A1 V

V

V

GE

GE

SE

SE

GE

SE

G1.01

G1.02

G1.03

G1.04

G1.05

G5.01

G5.02

G5.03

G5.04

G5.05

G8.01

G8.02

G8.03

G8.04

G8.05

G1.06

G1.07

G1.08

G1.09

G1.10

G5.06

G5.07

G5.08

G5.09

G5.10

G8..06

G8.07

G8.08

G8.09

G8.10

V

V

V

GE

SE

GE

SE

GE

G11.01

G11.02

G11.03

G11.04

G11.05

G14.01

G14.02

G14.03

G14.04

G14.05

G11.06

G11.07

G11.08

G11.09

G11.10

G14.06

G14.07

G14.08

G14.09

G14.10

V

SE

G19.01

G19.02

G19.03

G19.04

G19.05

G19.06

G19.07

G19.08

G19.09

G19.10

V

V

GE

GE

SE

SE

GE

SE

G1.01

G1.02

G1.03

G1.04

G1.05

G5.01

G5.02

G5.03

G5.04

G5.05

G8.01

G8.02

G8.03

G8.04

G8.05

G1.06

G1.07

G1.08

G1.09

G1.10

G5.06

G5.07

G5.08

G5.09

G5.10

G8..06

G8.07

G8.08

G8.09

G8.10

V

V

V

GE

SE

GE

SE

GE

G11.01

G11.02

G11.03

G11.04

G11.05

G14.01

G14.02

G14.03

G14.04

G14.05

G11.06

G11.07

G11.08

G11.09

G11.10

G14.06

G14.07

G14.08

G14.09

G14.10

SE

G19.01

G19.02

G19.03

G19.04

G19.05

G19.06

G19.07

G19.08

G19.09

G19.10

6. EXPERIMENT 2: ranking high POROSITY AREA A1 V

V

V

GE

GE

SE

SE

GE

SE

G1.01

G1.02

G1.03

G1.04

G1.05

G5.01

G5.02

G5.03

G5.04

G5.05

G8.01

G8.02

G8.03

G8.04

G8.05

G1.06

G1.07

G1.08

G1.09

G1.10

G5.06

G5.07

G5.08

G5.09

G5.10

G8..06

G8.07

G8.08

G8.09

G8.10

V

V

V

GE

SE

GE

SE

GE

G11.01

G11.02

G11.03

G11.04

G11.05

G14.01

G14.02

G14.03

G14.04

G14.05

G11.06

G11.07

G11.08

G11.09

G11.10

G14.06

G14.07

G14.08

G14.09

G14.10

SE

G19.01

G19.02

G19.03

G19.04

G19.05

G19.06

G19.07

G19.08

G19.09

G19.10

6. EXPERIMENT 2: OCTOPUS DATA MEDIUM POROSITY AREA A2.1

FITNESS CRITERIA

VOLUME V

SUN EXPOSURE SE

GROUND EXPOSURE

GENERATION 1

INDIVIDUAL V SE GE

G1.01 2067416.266 0.775391 108946.9874

G1.02 2064133.912 0.777945 109120.3663

G1.03 2100802.16 0.775353 109036.6612

G1.04 2067685.015 0.777166 108323.1209

G1.05 2062421.684 0.775862 108959.208

G1.06 2075397.728 0.776378 108401.4894

G1.07 2061925.16 0.776053 109141.1344

G1.08 2070419.656 0.776344 108242.5034

G1.09 2095154.092 0.775561 108940.208

G1.10 2096120.33 0.775423 108973.2104

GENERATION 2

INDIVIDUAL V SE GE

G2.01 2065619.433 0.777916 109040.1667

G2.02 2065383.199 0.776449 109000.794

G203 2102253.732 0.775543 109045.2296

G2.04 2075988.249 0.776412 108433.3196

G2.05 2089540.203 0.776655 108564.1225

G2.06 2084982.112 0.775948 108805.7937

G2.07 2095237.969 0.775175 108954.8861

G2.08 2094525.742 0.775289 108915.2158

G2.09 2070393.609 0.776069 108249.1155

G2.10 2095804.512 0.775556 108911.8883

GENERATION 3

INDIVIDUAL V SE GE

G3.01 2063904.594 0.778278 108904.2252

G3.02 2075653.137 0.776711 108421.7994

G3.03 2088317.29 0.776431 108549.7003

G3.04 2070686.879 0.776069 108276.0404

G3.05 2090609.495 0.776569 108564.1225

G3.06 2089431.577 0.776356 108564.5624

G3.07 2068732.764 0.777933 109059.6075

G3.08 2066972.134 0.776414 109002.0717

G3.09 2101572.332 0.775526 109022.1267

G3.10 2087891.832 0.776776 108543.8698

GENERATION 4

INDIVIDUAL V SE GE

G4.01 2089535.941 0.777324 108680.3657

G4.02 2062520.736 0.776866 108825.1592

G4.03 2096419.487 0.77676 109068.9458

G4.04 2075246.916 0.775643 108983.5211

G4.05 2065857.378 0.777939 109066.0891

G4.06 2060956.393 0.776314 108984.0467

G4.07 2066455.335 0.776293 109005.5898

G4.08 2075716.821 0.776447 108425.5355

G4.09 2088444.515 0.776656 108560.8237

G4.10 2065033.648 0.778434 108919.7353

GENERATION 5

INDIVIDUAL V SE GE

G5.01 2088083.536 0.776443 108593.0703

G5.02 2089923.83 0.776609 108567.8305

G5.03 2094870.251 0.776431 109058.5728

G5.04 2094464.262 0.776483 109053.8969

G5.05 2095556.372 0.777439 109062.2722

G5.06 2090022.821 0.776416 109124.5136

G5.07 2079872.703 0.775797 108441.7625

G5.08 2065979.617 0.777598 108783.4006

G5 .09 2066162.523 0.77707 108537.8685

G5.10 2087034.826 0.776447 109057.1623

GENERATION 6

INDIVIDUAL V SE GE

G6.01 2096076.185 0.777158 108601.2856

G6.02 20883 08.121 0.776654 109027.2426

G6.03 2094470.456 0.776639 109037.2672

G6.04 2095250.607 0.776379 109067.9015

G6.05 2088534.875 0.776573 109010.8551

G6.06 2065997.122 0.777002 108519.5203

G6.07 2091954.413 0.776891 108973.9309

G6.08 2068120.89 0.775884 108856.0522

G6.09 2100502.438 0.775774 108932.9779

G6.10 2086062.881 0.776612 109243.6075

GENERATION 7

INDIVIDUAL V SE GE

G7.01 2093382.849 0.775826 109044.8666

G7.02 2091945.671 0.776832 109048.4034

G7.03 2094562.923 0.77709 109045.0362

G7.04 2064771 .264 0.776131 108591.2663

G7.05 2097692.143 0.776486 108564.711

G7.06 2095897.172 0.776032 108953.1236

G7.07 2093962.913 0.776552 109046.9942

G7.08 2096083.784 0.775912 109084.8475

G7.09 2087568.923 0.77639 108883.7332

G7.10 2105911.665 0.775866 109087.803

GE

6. EXPERIMENT 2: OCTOPUS DATA MEDIUM POROSITY AREA A2.1

GENERATION 8

INDIVIDUAL V SE GE

G8.01 2094566.871 0.776325 108522.0371

G8.02 2097018.727 0.776642 109083.3615

G8.03 2091641.855 0.776453 109021.3731

G8.04 2091243.277 0.775535 109062.7465

G8.05 2090482.164 0.775631 109003.8344

G8..06 2094849.485 0.776958 108541.6936

G8.07 2093308.026 0.775874 109070.2654

G8.08 2096067.844 0.776294 109015.1824

G8.09 2091603.679 0.775779 109096.6718

G8.10 2096778.972 0.775951 109057.1883

GENERATION 9

INDIVIDUAL V SE GE

G9.01 2095802.777 0.77518 109094.778

G9.02 2098686.649 0.776492 109075.1511

G9.03 2095483.121 0.776875 109096.6807

G9.04 2099223.874 0.774573 109107.1237

G9.05 2095510.28 0.776353 108555.2086

G9.06 2094330.979 0.776014 109068.403

G9.07 2090125.179 0.774955 108996.6632

G9.08 2092647.258 0.776215 109086.9775

G9.09 2099842.406 0.776294 109012.8466

G9.10 2095509.676 0.776457 109078.8774

GENERATION 10

INDIVIDUAL V SE GE

G10.01 2108032.905 0.775567 109091.375

G10.02 2093115.313 0.775929 109089.4895

G10.03 2098374.968 0.776411 109107.0616

G10.04 2092129.648 0.775787 109061.3677

G10.05 2097822.808 0.776481 109047.6583

G10.06 2101677.063 0.774993 109146.4649

G10.07 2098362.052 0.776422 108548.4173

G10.08 2094594.365 0.776802 108496.4785

G10.09 2096710.664 0.775637 109047.0324

G10.10 2097463.842 0.776595 108537.8072

GENERATION 11

INDIVIDUAL V SE GE

G11.01 2105723.134 0.775985 109072.6756

G11.02 2097087.611 0.775562 109071.8623

G11.03 2096017.266 0.775288 109068.2295

G11.04 2106084.673 0.776626 109149.7916

G11.05 2098996.714 0.776553 108541.1302

G11.06 2091681.845 0.775891 109020.86

G11.07 2098174.287 0.776706 109006.513

G11.08 2098986.091 0.776595 108524.0177

G11.09 2090487.906 0.775995 108460.8523

G11.10 2100637.151 0.776739 108550.6108

GENERATION 12

INDIVIDUAL V SE GE

G12.01 2102138.333 0.776768 108575.6388

G12.02 2104736.368 0.775562 109081.5139

G1203 2107982.188 0.776076 108531.6303

G12.04 2094376.463 0.775465 108967.2501

G12.05 2098491.227 0.777143 109022.7519

G12.06 2103177.953 0.77646 109172.6705

G12.07 2099657.282 0.776358 108517.6443

G12.08 2103405.778 0.777136 108540.2122

G12.09 2099935.884 0.77599 109161.0765

G12.10 2101609.513 0.775481 108969.483

GENERATION 13

INDIVIDUAL V SE GE

G13.01 2099397.105 0.777118 109072.1642

G13.02 2096907.597 0.776014 108488.5564

G13.03 2106228.744 0.776942 109074.6797

G13.04 2089087.929 0.776559 108481.7355

G13.05 2098479.732 0.775846 109114.1146

G13.06 2105768.657 0.776871 108551.3167

G13.07 2105726.752 0.775504 109053.3874

G13.08 2096325.499 0.775996 109151.888

G13.09 2096765.078 0.776351 109111.2509

G13.10 2099697.261 0.776085 109171.5841

GENERATION 14

INDIVIDUAL V SE GE

G14.01 2098656.474 0.776324 108455.7602

G14.02 2103952.816 0.776916 108569.7259

G14.03 2096011.956 0.776259 109137.4168

G14.04 2106381.453 0.776722 109089.0382

G14.05 2103009.621 0.776632 109116.6322

G14.06 2102225.466 0.776356 109105.2398

G14.07 2109334.393 0.777334 109047.2842

G14.08 2104716.753 0.77672 108623.419

G14.09 2101729.548 0.77634 108540.3117

G14.10 2095800.843 0.776674 108508.4225

6. EXPERIMENT 2: OCTOPUS DATA MEDIUM POROSITY AREA A2.1

GENERATION 15

INDIVIDUAL V SE GE

G15.01 2099523.475 0.77643 109077.7927

G15.02 2106042.998 0.776402 109145.5577

G15.03 2112358.596 0.777659 109055.3205

G15.04 2099970.808 0.775944 109011.1874

G15.05 2104485.341 0.776649 109117.55

G15.06 2096021.861 0.776194 109143.9158

G15.07 2105391.863 0.776685 108643.3857

G15.08 2104167.182 0.776951 108587.2996

G15.09 2117886.498 0.775549 109136.6883

G15.10 2090828.412 0.77698 109032.3323

GENERATION 16

INDIVIDUAL V SE GE

G16.01 2105721.941 0.776821 109117.7823

G16.02 2111455.506 0.777435 109050.9491

G16.03 2104392.732 0.776649 109113.9694

G16.04 2102380.929 0.77658 109105.8757

G16.05 2101724.457 0.776604 108636.4717

G16.06 2108558.25 0.77665 109128.539

G16.07 2110059.766 0.777728 109028.5622

G16.08 2103795.218 0.776556 109117.55

G16.09 2111641.272 0.776396 109191.4308

G16.10 2111768.591 0.775313 109084.0725

GENERATION 17

INDIVIDUAL V SE GE

G17.01 2108506.201 0.776213 109070.9987

G17.02 2111624.297 0.776417 109027.7064

G17.03 2099843.389 0.777062 109025.9718

G17.04 2115444.248 0.777171 109140.0754

G17.05 2112864.816 0.776579 109155.245

G17.06 2105803.508 0.775562 109042.9451

G17.07 2110563.26 0.777607 109039.9678

G17.08 2103868.962 0.776562 109123.2022

G17.09 2113314.722 0.77724 109111.4009

G17.10 2099325.975 0.776718 108575.4321

GENERATION 18

INDIVIDUAL V SE GE

G18.01 2099692.561 0.7772 109013.317

G18.02 2115532.746 0.776952 109157.3535

G18.03 2112320.432 0.777084 109097.3908

G18.04 2108626.458 0.777625 109059.2689

G18.05 2115617.702 0.777259 109119.4414

G18.06 2111493.187 0.776271 109167.8111

G18.07 2107451.939 0.776256 109075.2121

G18.08 2115426.507 0.776533 109122.1823

G18.09 2110219.684 0.77759 108589.2921

G18.10 2114787.547 0.777355 109099.2673

GENERATION 19

INDIVIDUAL V SE GE

G19.01 2117553.023 0.777397 109143.1627

G19.02 2114644.895 0.777466 109119.4414

G19.03 2116327.949 0.777084 109149.8701

G19.04 2117218.727 0.777177 109157.4856

G19.05 2108605.102 0.777475 108583.7954

G19.06 2107930.999 0.77751 109048.4207

G19.07 2114062.851 0.777338 109099.2673

G19.08 2113996.132 0.777286 109086.0615

G19.09 2116594.391 0.776331 109105.9294

G19.10 2105684.922 0.777631 109060.3736

6. EXPERIMENT 2: OCTOPUS DATA MEDIUM POROSITY AREA A2.2

FITNESS CRITERIA

VOLUME V

SUN EXPOSURE SE

GROUND EXPOSURE

GENERATION 1

INDIVIDUAL V SE GE

G1.01 656244.6281 0.786742 47428.06705

G1.02 649358.7485 0.788137 47393.89019

G1.03 656600.2787 0.784045 47774.90315

G1.04 657122.5524 0.789468 47527.94287

G1.05 660021.002 0.787056 47707.86678

G1.06 651914.5681 0.786879 47617.78061

G1.07 659711.0161 0.787982 47650.22331

G1.08 647862.0372 0.786698 47531.4956

G1.09 659770.4764 0.786772 47666.34401

G1.10 663021.8045 0.785805 47565.86144

GENERATION 2

INDIVIDUAL V SE GE

G2.01 649643.0447 0.789527 47412.71162

G2.02 654768.3909 0.787201 47493.61485

G203 659880.1464 0.787827 47648.39278

G2.04 660143.12 0.787568 47717.85784

G2.05 659350.4893 0.787885 47632.5854

G2.06 648944.9289 0.787959 47393.89019

G2.07 648546.2623 0.78652 47527.16418

G2.08 658114.2183 0.783944 47778.12315

G2.09 658634.9888 0.787033 47701.14023

G2.10 659910.1187 0.786803 47709.71474

GENERATION 3

INDIVIDUAL V SE GE

G3.01 649729.791 0.789448 47418.87247

G3.02 659093.8447 0.787515 47701.78023

G3.03 654861.7872 0.784502 47673.30192

G3.04 653320.0835 0.788483 47534.40791

G3.05 648059.7719 0.788155 47401.04164

G3.06 659229.8765 0.787523 47654.10491

G3.07 658142.8046 0.78863 47711.11342

G3.08 649967.7887 0.786656 47399.7654

G3.09 659807.62 0.78791 47632.5854

G3.10 659645.8266 0.786872 47719.92144

GENERATION 4

INDIVIDUAL V SE GE

G4.01 657881.0489 0.787493 47645.60488

G4.02 658931.1613 0.787515 47711.5504

G4.03 654021.0725 0.786252 47630.60226

G4.04 662855.2455 0.788056 47704.12091

G4.05 648096.1596 0.788485 47410.62496

G4.06 647582.2006 0.788312 47387.23672

G4.07 659181.2413 0.787694 47711.54857

G4.08 657191.7499 0.788377 47714.61917

G4.09 659325.8923 0.787977 47623.17883

G4.10 649377.1482 0.789626 47418.18027

GENERATION 5

INDIVIDUAL V SE GE

G5.01 660223.3097 0.787796 47717.45002

G5.02 662780.4704 0.787955 47705.75765

G5.03 644880.6565 0.789016 47574.02318

G5.04 661259.6425 0.788176 47548.18368

G5.05 660292.3167 0.787994 47717.44103

G5.06 653055.2054 0.786098 47612.59007

G5.07 660156.308 0.78768 47656.4816

G5.08 661394.0089 0.788326 47678.5556

G5.09 662060.9976 0.787978 47704.12091

G5.10 649739.3592 0.788282 47434.03053

GENERATION 6

INDIVIDUAL V SE GE

G6.01 661026.9575 0.788054 47710.49712

G6.02 663955.85 0.788128 47695.16597

G6.03 662472.633 0.788658 47680.34457

G6.04 661496.4058 0.787727 47705.75765

G6.05 662486.5407 0.787424 47726.85932

G6.06 661051.4447 0.788798 47683.03616

G6.07 659473.6168 0.788197 47715.0972

G6.08 660448.6336 0.787618 47725.82144

G6.09 661293.2062 0.78813 47667.56657

G6.10 661534.1576 0.788724 47720.8194

GENERATION 7

INDIVIDUAL V SE GE

G7.01 659856.4934 0.787738 47709.37152

G7.02 659999.007 0.788141 47678.53078

G7.03 661977.9261 0.788516 47655.16668

G7.04 662808.5972 0.787392 47712.14674

G7.05 661699.799 0.78858 47674.44048

G7.06 659445.5671 0.787821 47723.34127

G7.07 663327.0588 0.788029 47700.66863

G7.08 661497.1698 0.787727 47686.30258

G7.09 660087.8388 0.788075 47667.56657

G7.10 661886.0552 0.788336 47698.57399

GE

6. EXPERIMENT 2: OCTOPUS DATA MEDIUM POROSITY AREA A2.2

GENERATION 8

INDIVIDUAL V SE GE

G8.01 664690.8749 0.787604 47707.49849

G8.02 661637.4395 0.787625 47654.37572

G8.03 660803.4829 0.788222 47658.69499

G8.04 658827.2092 0.787761 47664.9207

G8.05 662525.7185 0.787189 47714.6551

G8..06 661772.2412 0.787284 47693.78561

G8.07 659908.2633 0.78777 47649.53997

G8.08 664685.6376 0.788188 47702.12849

G8.09 657767.2406 0.788075 47672.44227

G8.10 658024.5887 0.78769 47696.36561

GENERATION 9

INDIVIDUAL V SE GE

G9.01 668119.7008 0.788128 47728.36719

G9.02 666580.6333 0.787246 47737.50387

G9.03 659416.4801 0.787946 47631.46704

G9.04 667263.3483 0.787909 47759.19343

G9.05 660780.835 0.787081 47687.28032

G9.06 666774.9035 0.788239 47721.81458

G9.07 659464.1134 0.788024 47668.36292

G9.08 663719.7324 0.786916 47717.95109

G9.09 664487.3585 0.787858 47664.72933

G9.10 660308.5133 0.787789 47642.92286

GENERATION 10

INDIVIDUAL V SE GE

G10.01 662578.0456 0.787365 47661.07157

G10.02 666954.5782 0.787828 47729.0667

G10.03 664194.457 0.787069 47675.46548

G10.04 661024.7603 0.788575 47677.35099

G10.05 665411.0087 0.788366 47756.08413

G10.06 666359.2585 0.788262 47741.16457

G10.07 664847.9868 0.787261 47748.72163

G10.08 664582.0735 0.787955 47762.41282

G10.09 666018.471 0.788234 47688.23202

G10.10 660667.2421 0.787289 47697.3831

GENERATION 11

INDIVIDUAL V SE GE

G11.01 663071.0344 0.787268 47749.46977

G11.02 664000.3906 0.788747 47716.1652

G11.03 662163.4923 0.787754 47749.59491

G11.04 666929.2247 0.788267 47755.47357

G11.05 665741.5437 0.787955 47741.29261

G11.06 667548.333 0.788417 47731.62586

G11.07 666253.587 0.78811 47762.19815

G11.08 665140.0135 0.787697 47730.67446

G11.09 662988.7986 0.788985 47664.06546

G11.10 666388.6004 0.788838 47680.83718

GENERATION 12

INDIVIDUAL V SE GE

G12.01 665319.5076 0.787604 47752.09609

G12.02 668775.4724 0.788559 47746.76858

G1203 666299.5343 0.788158 47742.89838

G12.04 666585.697 0.788389 47738.83783

G12.05 663309.4788 0.787551 47750.17238

G12.06 664470.0696 0.788681 47729.39262

G12.07 665389.8728 0.788711 47750.62534

G12.08 667644.7366 0.788978 47744.7329

G12.09 665750.4393 0.789698 47695.7974

G12.10 663122.4997 0.787597 47648.98295

GENERATION 13

INDIVIDUAL V SE GE

G13.01 666418.5481 0.789419 47718.29692

G13.02 663524.411 0.787722 47715.52273

G13.03 667915.4111 0.788024 47731.26944

G13.04 663276.6636 0.788179 47721.70434

G13.05 665255.4727 0.7881 47760.71382

G13.06 667283.4383 0.787521 47728.24202

G13.07 670752.0967 0.788589 47750.43953

G13.08 666603.6687 0.788615 47747.19266

G13.09 665083.1656 0.786919 47737.91695

G13.10 668620.4717 0.788328 47756.68634

GENERATION 14

INDIVIDUAL V SE GE

G14.01 667595.7539 0.788229 47748.0377

G14.02 667568.8316 0.788612 47761.38847

G14.03 669780.0886 0.788336 47756.41637

G14.04 668114.8075 0.788483 47727.4476

G14.05 666344.6704 0.788536 47737.40878

G14.06 666699.3292 0.788589 47749.4776

G14.07 665651.5468 0.788607 47744.10285

G14.08 666433.186 0.787745 47757.68943

G14.09 666704.038 0.788737 47740.0932

G14.10 665195.2793 0.787777 47761.19132

6. EXPERIMENT 2: OCTOPUS DATA MEDIUM POROSITY AREA A2.2

GENERATION 15

INDIVIDUAL V SE GE

G15.01 666620.0567 0.789143 47768.55264

G15.02 667958.9992 0.788338 47744.52828

G15.03 667069.8122 0.788965 47768.18523

G15.04 665788.1199 0.787544 47740.10331

G15.05 665419.8162 0.787727 47764.47304

G15.06 667475.195 0.787874 47737.59931

G15.07 669378.2416 0.788488 47752.89607

G15.08 666040.6844 0.788559 47743.76505

G15.09 667412.1368 0.788587 47757.57236

G15.10 666249.2141 0.788688 47721.74146

GENERATION 16

INDIVIDUAL V SE GE

G16.01 668642.7591 0.788584 47776.80515

G16.02 667213.059 0.788564 47765.11243

G16.03 667251.3619 0.787849 47743.22446

G16.04 667558.3602 0.78899 47771.50427

G16.05 667453.9683 0.788225 47765.30173

G16.06 666611.9176 0.78844 47737.7066

G16.07 665790.9201 0.788607 47770.40939

G16.08 667928.23 0.788973 47759.53112

G16.09 666816.4041 0.788359 47736.07526

G16.10 664984.7412 0.788077 47728.34603

GENERATION 17

INDIVIDUAL V SE GE

G17.01 669077.1468 0.78899 47756.62873

G17.02 667424.4349 0.78879 47771.50427

G17.03 667569.3812 0.789041 47771.50427

G17.04 668344.03 0.788633 47775.58207

G17.05 667515.5431 0.789041 47769.374

G17.06 667515.9564 0.789066 47777.44704

G17.07 667915.5628 0.788336 47734.76838

G17.08 668091.8756 0.788404 47774.21712

G17.09 668794.7329 0.789016 47770.12884

G17.10 667114.1502 0.788968 47769.89542

GENERATION 18

INDIVIDUAL V SE GE

G18.01 669184.2888 0.788607 47780.86764

G18.02 668751.0227 0.78881 47759.49731

G18.03 668319.8641 0.788785 47775.65527

G18.04 667480.4652 0.788968 47763.20674

G1 8.05 667677.535 0.789143 47777.85653

G18.06 667528.8902 0.788968 47789.36042

G18.07 668898.5423 0.788711 47768.03932

G18.08 667261.8376 0.788278 47761.55475

G18.09 668715.0909 0.789143 47762.22091

G18.10 668821.9808 0.788945 47761.90319

GENERATION 19

INDIVIDUAL V SE GE

G19.01 669058.8853 0.788785 47772.38761

G19.02 667311.0584 0.788841 47779.10486

G19.03 670201.2102 0.789275 47772.08426

G19.04 667486.8281 0.788838 47773.8229

G19.05 670113.1632 0.789168 47772.65335

G19.06 666578.1033 0.788856 47759.26876

G19.07 670112.681 0.788836 47780.84982

G19.08 667606.4043 0.78899 47771.69565

G19.09 669865.4709 0.789272 47750.24173

G19.10 669441.5627 0.789171 47763.61153

6. EXPERIMENT 2: ranking medium POROSITY AREA A2 V

V

V

GE

GE

SE

SE

GE

SE

G1.01

G1.02

G1.03

G1.04

G1.05

G5.01

G5.02

G5.03

G5.04

G5.05

G8.01

G8.02

G8.03

G8.04

G8.05

G1.06

G1.07

G1.08

G1.09

G1.10

G5.06

G5.07

G5.08

G5.09

G5.10

G8..06

G8.07

G8.08

G8.09

G8.10

V

V

V

GE

SE

GE

SE

GE

SE

G11.01

G11.02

G11.03

G11.04

G11.05

G14.01

G14.02

G14.03

G14.04

G14.05

G19.01

G19.02

G19.03

G19.04

G19.05

G11.06

G11.07

G11.08

G11.09

G11.10

G14.06

G14.07

G14.08

G14.09

G14.10

G19.06

G19.07

G19.08

G19.09

G19.10

V

V

V

GE

GE

SE

SE

GE

SE

G1.01

G1.02

G1.03

G1.04

G1.05

G5.01

G5.02

G5.03

G5.04

G5.05

G8.01

G8.02

G8.03

G8.04

G8.05

G1.06

G1.07

G1.08

G1.09

G1.10

G5.06

G5.07

G5.08

G5.09

G5.10

G8..06

G8.07

G8.08

G8.09

G8.10

V

V

V

GE

SE

GE

SE

GE

SE

G11.01

G11.02

G11.03

G11.04

G11.05

G14.01

G14.02

G14.03

G14.04

G14.05

G19.01

G19.02

G19.03

G19.04

G19.05

G11.06

G11.07

G11.08

G11.09

G11.10

G14.06

G14.07

G14.08

G14.09

G14.10

G19.06

G19.07

G19.08

G19.09

G19.10

6. EXPERIMENT 2: OCTOPUS DATA LOW POROSITY AREA A3

FITNESS CRITERIA

VOLUME V

SUN EXPOSURE SE

GROUND EXPOSURE

GENERATION 1

INDIVIDUAL V SE GE

G1.01 1140336.221 0.797647 82162.12697

G1.02 1140001.401 0.798449 81938.44682

G1.03 1129338.756 0.797743 82215.95971

G1.04 1135674.403 0.799063 81962.21346

G1.05 1142415.595 0.798051 82120.71009

G1.06 1130362.737 0.797667 82013.71822

G1.07 1122077.015 0.796958 81976.34241

G1.08 1154432.693 0.799003 82122.41814

G1.09 1143114.663 0.798492 81923.8673

G1.10 1115455.413 0.798019 82011.84434

GENERATION 2

INDIVIDUAL V SE GE

G2.01 1141616.952 0.798201 82197.0367

G2.02 1126045.556 0.797084 82155.42232

G203 1144851.556 0.799228 82068.86877

G2.04 1138941.944 0.797328 82016.15213

G2.05 1156258.495 0.798664 82345.49278

G2.06 1137652.151 0.798148 81967.02657

G2.07 1134643.388 0.797706 82030.82862

G2.08 1134783.722 0.798013 82173.31849

G2.09 1131512.756 0.798658 82244.54523

G2.10 1140910.365 0.79693 81925.66901

GENERATION 3

INDIVIDUAL V SE GE

G3.01 1141587.415 0.799262 82115.91945

G3.02 1147167.318 0.798216 82166.8374

G3.03 1140542.203 0.798189 82211.74719

G3.04 1141182.365 0.798355 82200.9596

G3.05 1134999.014 0.798022 82055.07911

G3.06 1156011.125 0.798695 82336.43401

G3.07 1149945.27 0.798667 82273.78636

G3.08 1136403.225 0.798597 82262.39059

G3.09 1136627.64 0.797683 81904.10633

G3.10 1135281.15 0.797582 82179.47159

GENERATION 4

INDIVIDUAL V SE GE

G4.01 1156094.401 0.798847 82372.96093

G4.02 1155680.292 0.798948 82358.48347

G4.03 1146582.526 0.798126 82202.75203

G4.04 1143470.468 0.799745 82183.33835

G4.05 1135671.898 0.797587 81896.1218

G4.06 1150420.713 0.79874 82261.01666

G4.07 1141743.258 0.798442 82199.79967

G4.08 1141107.126 0.798254 82195.88652

G4.09 1141690.222 0.798113 82177.8333

G4.10 1135681.654 0.799046 82170.94115

GENERATION 5

INDIVIDUAL V SE GE

G5.01 1144956.721 0.798357 82210.98241

G5.02 1157256.978 0.798779 82389.74045

G5.03 1159273.872 0.799226 82437.69278

G5.04 1150954.309 0.798445 82230.62597

G5.05 1153258.974 0.799543 82291.50796

G5.06 1144802.285 0.799174 82232.91066

G5.07 1154333.261 0.799032 82360.88349

G5.08 1142660.596 0.798619 82185.31595

G5.09 1137203.102 0.798293 82204.21957

G5.10 1159241.315 0.799088 82362.96277

GENERATION 6

INDIVIDUAL V SE GE

G6.01 1157921.808 0.799279 82410.82706

G6.02 1159343.487 0.799195 82425.77754

G6.03 1157485.922 0.798866 82391.25463

G6.04 1153060.877 0.799431 82285.77864

G6.05 1156556.764 0.799523 82412.595

G6.06 1157888.246 0.798948 82388.39953

G6.07 1158903.807 0.799226 82425.03385

G6.08 1159818.931 0.799206 82443.3722

G6.09 1147393.71 0.798894 82301.83809

G6.10 1153886.534 0.799071 82320.41758

GENERATION 7

INDIVIDUAL V SE GE

G7.01 1157879.446 0.798866 82406.56792

G7.02 1156719.806 0.799346 82373.45813

G7.03 1158732.742 0.799074 82426.3042

G7.04 1156254.869 0.798844 82384.93558

G7.05 1155693.511 0.799411 82348.91621

G7.06 1158465.147 0.79963 82379.13603

G7.07 1157485.206 0.799335 82411.04773

G7.08 1157796.585 0.799178 82418.72951

G7.09 1158681.783 0.798861 82415.06308

G7.10 1159845.005 0.799669 82433.15872

GE

6. EXPERIMENT 2: OCTOPUS DATA LOW POROSITY AREA A3

GENERATION 8

INDIVIDUAL V SE GE

G8.01 1157737.783 0.799568 82309.78947

G8.02 1160224.777 0.799666 82424.65505

G8.03 1153296.552 0.799431 82298.55281

G8.04 1157718.141 0.799115 82414.07884

G8.05 1158462.777 0.799074 82462.85737

G8..06 1156821.733 0.799436 82410.1468

G8.07 1156945.78 0.799503 82435.57322

G8.08 1155534.034 0.798773 82350.58503

G8.09 1158226.887 0.79927 82374.98584

G8.10 1157790.603 0.799495 82365.4817

GENERATION 9

INDIVIDUAL V SE GE

G9.01 1160694.311 0.799343 82483.81643

G9.02 1155534.666 0.79851 82375.97607

G9.03 1158 507.833 0.79922 82420.08763

G9.04 1158838.008 0.799054 82418.16677

G9.05 1157342.415 0.799229 82411.66322

G9.06 1156397.097 0.79975 82368.31708

G9.07 1157025.147 0.799436 82501.81277

G9.08 1156913.118 0.799874 82364.28373

G9.09 1156566.742 0.799312 82375.8903

G9.10 1160306.401 0.799596 82455.53375

GENERATION 10

INDIVIDUAL V SE GE

G10.01 1157635.559 0.79979 82419.23859

G10.02 1155549.21 0.79933 82359.9227

G10.03 1157693.878 0.79892 82392.15225

G10.04 1156328.93 2 0.799781 82368.50366

G10.05 1161424.144 0.798978 82517.90507

G10.06 1154540.197 0.799846 82373.56926

G10.07 1158094.561 0.799274 82470.29104

G10.08 1158440.831 0.799554 82455.13057

G10.09 1156509.629 0.799385 82379.38812

G10.10 1158156.389 0.799689 82370.68545

GENERATION 11

INDIVIDUAL V SE GE

G11.01 1157497.541 0.799874 82389.75203

G11.02 1156959.357 0.79864 82406.18325

G11.03 1157571.017 0.799201 82431.10982

G11.04 1155478.793 0.799759 82340.46553

G11.05 1154457.318 0.799235 82423.33704

G11.06 1156152.275 0.800053 82408.52082

G11.07 1157831.138 0.799506 82403.59659

G11.08 1155237.779 0.799223 82394.84014

G11.09 1158100.103 0.799672 82444.98134

G11.10 1159121.498 0.79906 82446.55565

GENERATION 12

I NDIVIDUAL V SE GE

G12.01 1153217.15 0.799229 82357.20546

G12.02 1158804.032 0.799181 82436.94091

G1203 1157485.563 0.799734 82377.17704

G12.04 1158258.717 0.798645 82451.81593

G12.05 1161516.673 0.799476 82491.48594

G12.06 1158353.205 0.79908 82399.39858

G12.07 1157798.687 0.799605 82379.90404

G12.08 1157875.664 0.799243 82459.80744

G12.09 1157128.631 0.799921 82395.91384

G12.10 1154850.231 0.799608 82400.91925

GENERATION 13

INDIVIDUAL V SE GE

G13.01 1160833.399 0.799156 82463.63662

G13.02 1157869.793 0.799054 82422.30858

G13.03 1160853.799 0.799596 82419.3678

G13.04 1156384.948 0.799927 82472.19281

G13.05 1155276.842 0.799661 82420.89774

G13.06 1158862.924 0.799554 82382.59333

G13.07 1162516.673 0.799518 82489.0984

G13.08 1156220.421 0.799131 82439.94762

G13.09 1158081.955 0.798809 82432.59075

G13.10 1156459.065 0.799032 82428.71768

GENERATION 14

INDIVIDUAL V SE GE

G14.01 1157617.614 0.798781 82417.21412

G14.02 1161191.482 0.799366 82484.3392

G14.03 1162313.294 0.799142 82424.86173

G1 4.04 1158586.42 0.799798 82449.32261

G14.05 1160401.653 0.799495 82425.17803

G14.06 1160982.431 0.799524 82415.92473

G14.07 1159506.245 0.800188 82509.16772

G14.08 1160798.405 0.799004 82464.62432

G14.09 1163076.51 0.799459 82490.79217

G14.10 1160315.593 0.799882 82424.91952

6. EXPERIMENT 2: OCTOPUS DATA LOW POROSITY AREA A3

GENERATION 15

INDIVIDUAL V SE GE

G15.01 1163708.552 0.79956 82491.12903

G15.02 1161994.136 0.799352 82492.35736

G15.03 1163011.831 0.799445 82497.37414

G15.04 1161859.84 0.799563 82454.75789

G15.05 1159672.975 0.800104 82510.89377

G15.06 1160397.776 0.799666 82431.09625

G15.07 1163172.784 0.799263 82484.6793

G15.08 1163413.142 0.79949 82493.00254

G15.09 1162620.623 0.799389 82490.39471

G15.10 1162397.752 0.799212 82419.1426

GENERATION 16

INDIVIDUAL V SE GE

G16.01 1162252.684 0.799237 82463.64216

G16.02 11631 95.502 0.799669 82507.24718

G16.03 1160928.881 0.799481 82456.36895

G16.04 1164496.426 0.799546 82502.51767

G16.05 1162178.316 0.799521 82471.31785

G16.06 1160743.59 0.799913 82514.68579

G16.07 1162229.163 0.799706 82501.29765

G16.08 1163230.443 0.799526 82479.87028

G16.09 1163119.437 0.799518 82491.37262

G16.10 1160580.057 0.799694 82423.84604

GENERATION 17

INDIVIDUAL V SE GE

G17.01 1161563.853 0.799282 82447.67358

G17.02 1163460.945 0.799487 82526.43309

G17.03 1163394 .805 0.7997 82481.10194

G17.04 1163610.473 0.7994 82470.89994

G17.05 1162735.924 0.799538 82455.48766

G17.06 1164107.377 0.799501 82508.43989

G17.07 1161754.499 0.799392 82499.57183

G17.08 1163311.182 0.799734 82495.80746

G17.09 1163788.67 0.799436 82518.95316

G17.10 1163851.888 0.799644 82487.22131

GENERATION 18

INDIVIDUAL V SE GE

G18.01 1163575.774 0.799478 82506.69311

G18.02 1162008.853 0.799378 82475.91624

G18.03 1164525.2 0.799268 82534.03034

G18.04 1163810.703 0.799459 82514.73859

G18.05 1162 766.928 0.799582 82520.67948

G18.06 1163824.705 0.79956 82514.28093

G18.07 1163846.167 0.799462 82476.52829

G18.08 1162733.533 0.799263 82484.72995

G18.09 1165170.249 0.799319 82520.27671

G18.10 1162568.079 0.79975 82488.60803

GENERATION 19

INDIVIDUAL V SE GE

G19.01 1163353.309 0.799647 82521.46773

G19.02 1162651.559 0.799532 82524.03231

G19.03 1164855.359 0.799473 82518.4369

G19.04 1163611.279 0.799714 82501.2572

G19.05 1164246.328 0.79935 82528.51767

G19.06 1163429 .013 0.799392 82537.52971

G19.07 1165802.663 0.799779 82509.10154

G19.08 1163105.454 0.799179 82514.04805

G19.09 1165467.79 0.799338 82531.02929

G19.10 1163591.104 0.79931 82541.06803

6. EXPERIMENT 2: ranking LOW POROSITY AREA A3

V

V

V

GE

GE

SE

SE

GE

SE

G1.01

G1.02

G1.03

G1.04

G1.05

G5.01

G5.02

G5.03

G5.04

G5.05

G8.01

G8.02

G8.03

G8.04

G8.05

G1.06

G1.07

G1.08

G1.09

G1.10

G5.06

G5.07

G5.08

G5.09

G5.10

G8..06

G8.07

G8.08

G8.09

G8.10

V

V

V

GE

SE

GE

SE

GE

SE

G11.01

G11.02

G11.03

G11.04

G11.05

G14.01

G14.02

G14.03

G14.04

G14.05

G19.01

G19.02

G19.03

G19.04

G19.05

G11.06

G11.07

G11.08

G11.09

G11.10

G14.06

G14.07

G14.08

G14.09

G14.10

G19.06

G19.07

G19.08

G19.09

G19.10

6. Genetic algorithm definition :Experiment 2

Fitness Criteria

Grid Subdivision

184 Emergent Technologies and Design | AA |

6. Genetic algorithm definition :Experiment 2

Data exchange between rhino and grasshopper plataform.

Lady Bug plug-in for Solar and Ground Exposure optimization.

Adaptable Morphodynamics 185

6. Octupus, multi-objective optimization

186 Emergent Technologies and Design | AA |

6. Octupus, multi-objective optimization

Adaptable Morphodynamics 187

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