ADAPTABLE MORPHODYNAMICS | AA | EMERGENT TECHNOLOGIES AND DESIGN | MSc DISSERTATION | 2013-2014 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“I certify that this piece of work is entirely my/our own and that any quotation or paraphrase from the published or unpublished work of others is duly acknowledged.”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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Emergent Technologies and Design | AA |
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. 34
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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. Adaptable Morphodynamics
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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. Adaptable Morphodynamics
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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
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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
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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
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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%
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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. Adaptable Morphodynamics
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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. Adaptable Morphodynamics
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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
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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. Adaptable Morphodynamics
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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
Adaptable Morphodynamics
99
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
Adaptable Morphodynamics 101
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
Adaptable Morphodynamics 103
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
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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. .
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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
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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)
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EXPERIMENT 2
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5 m/s
(b)
Wind Direction EAST
EAST 5 Wind Direction 0
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Fig.6.23: Comparison of CDF analyses between Existing patch, Experiment 1 and 2 (a) Ground Floor level (b) 50 m Height
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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. 120 Emergent Technologies and Design | AA |
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
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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. 128 Emergent Technologies and Design | AA |
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.
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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
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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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