Synapes City_Bartlett UCL

Synapses in human body are essential to neuronal function: neurons are cells that are specialized to pass signals to individual target cells, and synapses are the means by which they do so. Synapses exist in different structural forms exhibiting a variety of morphological complexities, which are complimented by a myriad of dendritic spine shapes.

Synapse City allows urban space to form spatial interactive culture within urban area, which pass the urban signals to individual part of a city. Synapse City strengthens the relationship between citizen and city as well as boost the connection of different functions of city.

SYNAPSE CITY RC 14

TutorsďźšRoberto Bottazzi Tasos Varoudis Studentsďźš ChenChin In Jiangrui Wan Yingqi Huang

September 2018

Deepest thanks to Roberto Bottazzi and Tasos Varoudis, for their endless effort and guidance which make this work possible.

TABLE OF CONTENT

1 Introduction

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2 Data Analysis and Visualisation of London

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3 Data Analysis and Visualisation of Elizabeth Olympic Park

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4 Data Transformation

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5 Design Generation from Data

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6 Design Concept

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7 Synapse City

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1 Introduction Movement in urban design represents the circulation networks within cities, which are what connects all programmatic spaces. This is not limited to interior spaces within cities, but also within different cities and towns. Movement also refers to the way people move through spaces. In particular, circulation routes are the pathways that people take through and around urban spaces. In order to create a better circulation, human had invented a system, that is what we called traffic. Traffic enables people to travel though urban spaces more convenient and efficient, it also gives cities an opportunity to grow. As time went by, for the growth of technology and economy, the type of traffic transportation had gone through a great change. Nowadays, people drive cars instead of carriages, take high speed rail instead of steam train. Moreover, the amount of traffic transportation on the road is much more larger than those in the past times. The traffic system that was built for carriages and steam trains clearly cannot meet the demand today.

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Movement and Circulation of Urban Design Movement in urban design refers to the way people move through spaces. In particular, circulation routes are the pathways that people take through and around urban spaces. Urban movement system enables people to travel though urban spaces more convenient and efficient, it also gives cities an opportunity to grow.

Although every space a person could access or occupy forms part of the circulation system of a city, when we talk about circulation, we typically do not try to account for where every person might go. Instead, we often approximate the main routes of the majority of users.To simplify further, architects and urban designers typically divide their thinking according to different types of circulation, which overlay with one another and the overall planning. The type and extent of these divisions will be project dependant, but might include: 路 direction of movement: horizontal or vertical; 路 type of use: public or private 路 frequency of use: common or emergency; 路 time of use: morning, day, evening, continuous.

Each of these types of circulation will require different consideration. The movement might be fast or slow, mechanical or manual, undertaken in the dark or fully lit, crowded or individual. The pathways might be leisurely and winding, or narrow and direct.

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1.1 Futurist Architecture and Movement Futurist movement of the early 20th century provides intriguing visions of movement both within artwork, the addition of the built environment, coinciding with the glorification of the machine, provided a unique style of architecture, and stimulating insight into movement and the relevance of the machine.

One of the neo-futurist visions by italian group superstudio in the 1960's promised total freedom of living, on an infinite gridded platform into which we may plug for energy, information or nutritive needs. This scenario, however, embodies a clear denial of the need for the interaction of body and architecture, instead it emphasises the relationship with body, machine and movement.

Contrasting this ideal by Superstudio whereby movement and freedom of living is paramount, London based architectural group. Archigram again drew inspiration from technology but in a much controlling fashion. The Walking City by Ron Herron had the idea of replacing the human bdy and its freedom of movement with a machine. Herron proposed enormous mobile robotic structure which could interconnect with each other to form large walking metropolises.

Advancements in technology has resulted in some of these futurists ideas being implemented at a smaller level. Through advancement in technologies, man is 'moving' faster and farther than ever before, but this movement is primarily a passive experience - we do not have control of these movements. Our bodies are being moved or propelled in space rather than moving ourselves. In essence we are actually experiencing less active movement in the horizontal and vertical planes than ever before, by using me chanical means such as elevators, escalators and vehicles.

Ran Herrron : A Walking City

Archigram Machine Movement

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1.2 Green Transport The new draft Mayor’s Transport Strategy aims to change the way people choose to travel. By 2041, the Mayor aims for 80% of all Londoners’ trips to be made by foot, by cycle, or by public transport.

Vehicle emissions can blight streets, harming health and contributing to climate change. London must meet legal air quality limits as soon as possible.

Creating streets and routes that encourage walking, cycling and public transport use will play a major role in reaching this goal. Transport for London (TfL) will deliver on this goal by using the Healthy Streets Approach to guide all of its decision making.For those vehicles that remain, it is essential that we reduce emissions as soon as possible and switch them to zero emission technologies.

The Mayor is working to ensure London’s entire transport system is zero emission by 2050. TfL will deliver their approach following wide-spread public consultation and building on the introduction of the Ultra Low Emission Zone and the Toxicity Charge (T-Charge).This includes delivering central London and town centre zero emission zones from 2025, creating a zero emission zone in inner London by 2040 and a London-wide zone by 2050.

Pedal Power by Caroline Tomlinson Photograph: London Transport Museum

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1.3 The Future for Skycycle System Exterior Architecture, Foster + Partners and Space Syntax – a team who share Lord Foster’s passion for the benefits of cycling – have jointly developed SkyCycle, a new approach to transform cycling in the capital. Following existing suburban railway corridors, a wide, secure deck would be constructed above the trains to create new cycle routes throughout London.

The proposed SkyCycle network follows existing suburban rail services and provides over 220 kilometres of safe, car free cycle routes which can be accessed at over 200 entrance points. Almost six million people live within the catchment area of the proposed network, half of whom live and work within 10 minutes of an entrance. Each route can accommodate 12,000 cyclists per hour and will improve journey times by up to 29 minutes.

The Mayor’s aim is for London to be the best major city in the world. However, the capital’s transport network is at capacity and faces the challenge of population growth of 12 percent over the next decade. The government has committed to investment in transport, through airport planning, high-speed rail, Thameslink and Crossrail. The Mayor’s transport strategy also seeks to address the needs of pedestrians and cyclists in the city’s crowded streets and in areas where the public realm is poor. The environmental and health benefits of cycling notwithstanding, the bicycle is a more efficient use of London’s limited space – we believe there is a pressing need for network modelling of new capacity for these active, self-determined modes of transport.

As London’s railway lines were originally built for steam trains, they follow contours that naturally reduce the amount of energy expended and avoid steep gradients. SkyCycle exploits this historic legacy. Associated benefits include the regeneration of the typically low value, often underutilised industrial sites next to railway lines; vertically layering the city to create new social spaces and amenities on these cycling high streets; and the integration of automated goods delivery networks.

Early studies of a SkyCycle system indicate that it provides capacity at a much lower cost than building new roads and tunnels. The possibility of the deck providing development opportunities for businesses along the route, particularly where it intersects with stations and bridges, has also been the subject of the study, exploring ideas for public/private commercial growth and regeneration. The SkyCycle study team will continue to further develop these scenarios, and the project has already been presented to the GLA, TfL and Network Rail, as well as to developers and contractors with specialist rail experience.

SkyCycle, by Foster + Partners, 2013 SkyCycle, by Foster + Partners, 2013

Skycycle,

by Fosterby + Partners, 2013+ SkyCycle, Foster

Partners, 2013

SkyCycle, by Foster + Partners, 2013

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1.4 Angular Segment Analysis of London —— Integration In this design, we use Space Syntax as our main method to test the spatial relationship betwen design and its surroundings. Space syntax is a theory and a set of methods about space, built on two ideas which reflect both the objectivity of space and our intuitive engagement with it. The key difference between space syntax and other approaches to space is that it seeks first of all to address space as relatedness, and as it is, and might be, created by buildings and cities, and as it is experienced by the people who use them. It is not that it is not interested in the spatiality of social processes, but it sets out from the idea that the most powerful evidence for spatiality must be the ways in which human beings actually organise and arrange real space. Space syntax then begins by studying the phenomenon of space as it is found in the real world, and from this works towards an understanding of the spatiality of human activity.

This is the traffic network of London. We ran the analysis through space syntax. This is the integration analysis of the existing road network. The red part of the image shows a higher integration of the cities, the result shows the potential movement of the city.

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2 Data Analysis and Visualisation of London In this chapter, we will illustrate the mobility data through a number of graphic conventions including heatmaps, mesh-based representations and others. The software employed to generate such visualisations include QGIS, Grasshopper [Rhinoceros plug-in] , and DepmathX, etc. The source of the data is taken from the Internet, mostly from https://data.gov.uk/ and https://tfl.gov.uk/. Our focus is the data of circulation and movement in order to identify areas which lack adequate infrastructural connections and, consequently, potential sites for intervention.

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Movement Data Movement is closely related with connectivity. Before we dive into the site, it is essential to know about the movement data around the site.

We start this process by collecting open data on London as the UK government has a very rich and open database. We collect our data in three ways: from the Internet, by directly collecting with hands through site visits, and, finally, by simulating movement through digital simulations. The movement system of London is quite rich and highly connected. The London bus and underground somehow become one of the most significant tourist attractions. Buses and undergrounds play a very important role in urban movement as we collect the data from Transportation of London, where has a detailed database of bus and underground every 15 minutes.

Movement also brings social problems to cities. Therefore, we also look at the data of accident, noise and pollution of London. The data is also collected from the internet. We transferred the data from a pile of numbers into maps by using computer software. By visualizing the data, we can see the movement of London more accurately. Some movement of data such as the data of pedestrian are very hard to collect from the internet.

With the help of computer software, we simulate the movement with different kinds of parameter.

By analyzing the movement data of London, it’s helpful for us to know how the site is connected with the surroundings and speculate on why issues related to circulation might be caused. The internet source of the data are UK Government Database, Transportation of London, Digimap, and Department of Transport.

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2.1 Bus Routes Concentration of London The bus stop concentration in London is shown in the following map. The data of the bus route sequences and locations are from TFL, and the exact route names using different bus stops are from Bus spider maps in TFL. The above and following maps are visualized with grasshopper. The lines represent different bus routes, and the heights represent the usage and possible concentration of each stop according to the calculation of the number of different routes. The bus stops with high concentration are highlighted, such as Walthamstow Station, High street orpington war memorial Station and Edgware Station. It can be seen that the usage of bus in central London is high. According to the Mayor of London, in central London, all double-deck buses will be hybrid by 2019 and all single-deck buses will emit zero exhaust emissions by 2020. By 2037 at the latest, all 9,200 buses across London will be zero emission. So, with green transport promoted in London, the public transport including the buses infrastructure should be paid more attention and improved.

Walthamstow Station

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Edgware Station 32 79 107 113 142 186 204 221 240 251 288 292 303 305 340 605 606 642 N5 N16 N113

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High Street Orpington War Memorial Station 51 61 208 353 684 B14 N199 R1 R2 R4 R5 R6 R7 R8 R9 R10 R11

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2.2 Underground Travelcard Usage of London The data of the underground travel card usage in London (Nov. 13, 2017)is recorded by Transportation of London (TFL). The data from TFL records all the data when people are scanning their oyster card and travel card when going in and out the underground stations. By visualizing the data every one hour, the origins and the destinations of each passengers is shown in this images. We connect those starting and ending points together and apply to all the data. The red columns shows the amount of the people passing through the underground stations. Higher columns represents busier underground stations such as Bank & Monument, Oxford Circus.

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2.3 Pedestrian Movement Potential The choice analysis map on the bottom and the agent base modeling analysis on the right are simulations which done by Space Syntax. The theory studies the relationship between spaces and predict the potential movement of a certain area.

The diagrams on the right are agent-based model analysis. An agent-based model is a simulation of individual movement behaviour in which ‘agents’ choose their direction of movement based on a defined visual field derived from visibility graph analysis, in which agents have access to precomputed information about what is visible from any given location in the map. The agent-based model allows the programmer to simulate the likely behaviour of people as they navigate through the environment.

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2.4 Annual Traffic Accidents Concentration This map shows the annual accident occurrence in London, 2016. The data is from https://data.gov.uk/ . We transfer the numbers into heat map via QGIS. First, we set a point to every single accident places and give them a buffer zone and a color ramp. In the following map, Areas with brighter colors have more accidents, which clearly have a more complex traffic status. Generally speaking, expect for the central of London, the volume is not too terrible. But in some of the places, which are on in the central of London but have a similar situation as central London does.

High value of accidents can lead to some traffic problems such as congestion, which also affect the transportation seriously.

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2.5 Traffic Noise Distribution The following map shows the traffic noise distribution in London. The source of the data is from https://data.gov.uk/. We transfer the number into maps by using QGIS. There are two main characteristic of this kind of noise. One is that they are wide-spread. Noise made by vehicles is the main part of the traffic noise. With the development of transportation above the ground level, the air craft generates a large volume of traffic noise.

Secondly, the volume of this kind of noise is enormous. In the following map, the orange color represents the noise from roads. The blue color represents the noise from rail. Brighter color areas have more severe traffic noise problem. The distribution of the noise from 55 decibel to over 75 decibel. It can be seen on the map that large amount of noise occurs mostly on main roads. The reason is main road usually have more vehicles passing through. Additionally, most of the land use of the site is residential. Noise can interfere with the residents and affect their life. People who are exposed to for a long time most likely to have eye fatigue, eye pain, visual impairment.

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2.6 Annual Mean PM2.5 Concentration —2013 LAEI Update The following map shows the annual mean PM2.5 concentration in London, 2013. PM2.5 is one of the pollutant from air pollution, which is also one of the most harmful particulates in the atmosphere. Particulate matter (PM) are microscopic solid or liquid matter suspended in Earth's atmosphere.fine particles with a diameter of 2.5 μm or less are identified as PM2.5. The source of the data is https://data.gov.uk/. We transfer the number to map via QGIS. The data of the PM2.5 distribution is joined with the mapping of London Output Area Classification (LOAS). The range The distribution of PM2.5 ranging from 143.-21.1 g/m³. The result shows that the PM2.5 concentration is closely related to traffic network owing to harmful emission of vehicles. Also, central London have a higher PM2.5 concentration while open space including water surface and green spaces shows the opposite because of the positive impact on reducing air pollution.

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3 Data Analysis and Visualisation of Elizabeth Olympic Park The Queen Elizabetn Olympic Park Area is the origin site of RC14. After doing the analysis in London area. It is the time to look closer in our origin site and do the analysis on the data of circulation and movement. The source of the data are mosly fromhttps://data.gov.uk/ and https://tfl.gov.uk/. We did the visualization via QGIS, grasshopper ,DepthmapX, etc.

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Background The site of this design, Queen Elizabeth Olympic Park and Hackney Wick Area, is one of the largest green space, located at the east part of London, adjacent to the Stratford City development. It contains the athletes' Olympic Villages and several sporting venues including the London Stadium and London Aquatics Centre, besides the London Olympics Media Centre. High accessibility to the bus stops, overground and underground station improve the public transportation usage.

The Olympic Games was held successfully. According to some reports and researches, the area used to be an industrial area. In order to build the Olympic Park on time and provide a comfortable and suitable environment to athlete as well as visitors from all over the world, the British Government built up a series of traffic network including underground, overground, highways, bicycle ways, etc, to bring convenience for people to get access to the park and enjoy the game. As a result, there were 253,744 people passed though the newly built Stratford underground station on the busiest day during the 2012 Olympic Games.

The Olympic Games brings Stratford development, the park also becomes one of the most attractive places that citizens would like to spend their times on weekends and holidays. Due to the traffic count data by Transportation of UK, though the 2012 London Olympic Games were already ended, there’s still a huge amount of people travelling to Stratford station, especially weekends. The Olympic Park had turn Stratford from an industrial area to one of the most attractive residential area in east London. A great amount of residential buildings rose from those area where used to be factories. The population of Stratford had grown dramatically.

In order to understand the movement of the site, we collected the data of pedestrian, bicycles, buses, underground and traffic count by collecting, observing and simulating. Then we use some computer software to make the data visualized in order to read the data more accurate base on the location

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3.1 Existing Conditions Because of the advantages including the facilities and the location of this area, movement of people and traffic system became more and more frequent. Also, pushed by the Westfield shopping malls and other attracting destination, the land price continued to grow. So the functions of some area with high economic potential require substitution and the organization of the flow also needs to be improved. Especially for the Stratford station area, where the entrance of Qlympic park, Westfield shopping mall and other attractions are densely located, the improving method for this area might be implemented to other areas with similar characteristics.

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3.2 Land Use In this map, we have analyzed the land use, functions and the activities type of the Olympic Area. It can be seen that most of the areas are residential areas. In the middle of the map, which is the Olympic park, the type of land use is green space and recreational. Some public infrastructures and rivers penetrates all over the park. The river bank of the park becomes one of the most popular leisure places in London. There are some commercial areas as well. Most of those areas are located around tube stations. Some industrial areas stand near the Olympic park, but only some of them are still in used.

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3.3 Traffic Station Distribution The heatmap on the left shows the distribution of underground and bus stations in the site. Generally speaking, though there are quite many bus stops in the south west part of our site. Compared to somewhere like Stratford and Walthamstow Central right here, they have higher accessibility to other place.

The bus route analysis shows the route and quantity of buses stop location density analysis is generated based on the location density heatmap and the bus concentration analysis shows the incidence of congestion and concentration degree. The road integration analysis shows the closeness centrality of the network and incidence 0f the movement of pedestrain.

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3.4 Underground Station Catchment This map shows the underground station catchment. People who live in the area with light colour can get to the nearest underground station on foot which means they the main user of underground. Unfortunetaly, people who live in the dark area may seldom take underground. We also labled the main underground stations in site.

Tottenham Hale Station

Sevensister Station

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3.5 Underground Travelcard Usage From the data of the main underground stations in the site,We analysis the value of people passing though the tube station. In the graph on the right side, red line means weekdays, the green one is Saturday, and the blue one is Sunday. We can see people go inside the tube station in the morning and come back in the afternoon. Weekends barely changes.

Walthamstow Station

Tottenham Hale Station

Leyton Station

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Sevensister Station

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3.6 Traffic Count In order to understand the traffic situation of the base, we count the traffic data of the whole year in the site and classified the data. For the sake of clarity of all kinds of traffic flow data, we transform the data to the shown in the figure on the left, the vertical height of different roads generation based on numerical, highly representative of the traffic volume throughout the year. Each color represents a kind of vehicle.

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3.7 Movement Volume of Public Bicycle The picture below shows the cycle traveling movement of site. The lines are the actual trips people takes. The hight represents the amount of cycles in one route. In the pictures on the right side, the little green points are cycle docking points. The blue lines represents the movement of traveling out side the site and the purple lines are people cycling into the site. From this pictures we can see there’s more people cycling in the east side of the area.

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4 Data Transformation After carrying out a detailed analysis on different areas of our site, we concluded that movement could be imagined by other means such as energy. We invented an internal system to transform movement in to energy which was broadly divided into ‘positive’ and ‘negative’ energy.

In this chapter , we will illustrate how we transform the data and what does that mean to us. The source of the data are mostly from https://data.gov.uk/ and https:// tfl.gov.uk/.

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Transform Energy From Movement Energy can be generated by many kinds of ways. One of those ways is to be created by movement. If we think movement can be some energy means. The analysis on movement will be more meaningful that movement can be treated with the problem of energy.

So we divide the energy created by movement into two kinds of energy. One is called positive energy, and another one is negative energy. We calculate this two kinds of energy by using different kinds of data. The positive energy is the one which generates from physical activities such as cycling and jogging. And the negative energy is calculated by the mathematical association of NOx, petrol and energy, which caused by vehicles.

In order to compare the positive and negative energy, we have to translate them into the same unit, which is the unit of energy, joule.

We found some data from https://tfl.gov.uk/ and https://data.gov.uk/. We translated the number into 3 dimensional mesh by using grasshopper and QGIS. The x and y coordinate represents the geographic information and the high represents the value of energy.

As for positive energy, the unit of human physical activities is calorie. The following formula can turn calories into joule: Calorie consume = distance × weight(65 kg) × 9.8 joule We use another formula to transfer negative energy by the following formula: 1 μg/m³= 2.1413 joule/m³ After doing the calculation and turn them into mesh. We subtract the positive energy from the negative energy and found out that most of the value we get is negative. We would like to add more positive energy and decrease some negative energy through the design.

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4.1 Surroundings We combine all the data we have and decided to zoom in and take a deeper analysis. We found out the south part in the wire frame of the site has more data we can find as well as there are many contradictions here. So we decided to go in deep research in this area and zoom in our site.

Modern, former Olympics venue with striking weave-shapped roof and pool for diving and swimming.

London Aquatics Centre

Victoria Park

London Stadium Stadium built for 2012 Olympics, and home of West Ham United FC, hosting sports events and concerts.

Arcelormittal Orbit The Arcelormittal orbit is a 114.5m tall sculpture and observation tower in the Queen Elizabeth Olympic Park.

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St. John's Church

Statford Station

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4.2 Negative Energy Plot We plot the area with negative energy, which clearly shows which part of the area have the most severe problem cause by movement. The problems are concentrated in those which have higher value of traffic counts and those where road network are highly integrated.

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4.3 Positive Energy Map The positive mesh done by shows the most popular for cyclist and pedestrian in the area. The Olympic Park clearly attracts more people to jog and cycle. The height represents the calories that people burn in specific areas, which also refers to a healthier area.

Based On The Combination Map of Pedestrain And Cycling pedestrain calaries cycle calaries

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4.4 Negative Energy Map The negative mesh which transferred from the negative energy plot shows a clear result of which area have the most movement problem. Instead of those area which have higher traffic counts, the area with higher integration and higher possibility to cause traffic congestion show higher value of negative energy.

Based On Moto Viehcles 62

Stratford

Crossing of A126 & Wick Rd

Crossing of A11 & A12

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4.5 Positive and Negative Energy Combination Map This is the energy mesh of a combination of positive energy and negative energy. The height of the mesh, which is the value of the energy, is the value of positive energy plus negative energy. The peak of the mesh all remain negative means the value of negative is much more higher than the positive ones.

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5 Design Generation from Data In order to generate a better movement for the pedestrian and the bicycle, we choose three kinds of algorithms which guided the process of generating movement paths through the site.

We picked several points [Attractive Points] based on the data analysed and which remained fix as they allowed us to connect the network proposed to the existing one.

Then run the algorithms. Additionally, we analyzed the result through DepthmapX.

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Data Morphogenesis In the last chapter we transfer the data into energy unit and found out that certain part of the site have a dramatically high value of negative energy. Some part of the site have either high value of positive energy or negative energy, which may mean a huge amount of urban movement or traffic chaos. In order to have better understand of situation that the data are telling us, we did a further analysis by visiting the site and collect the data.

We analyze the surrounding of the area as well as the possible causes of the problems. We took land use, bicycle usage, green space, station distribution into consideration. The results of Space Syntax analysis are also added into options for further analysis. Then we use some algorithms of python to classify the areas that the data have higher integration and connection.

The purpose of the design is to create a better circulation for city to improve the spatial interactive culture of city. Three kinds of algorithms are used to form for morphogenesis design. The spatial relation of the options are then test in DepthmapX, which is a computer software for Space Syntax analysis.

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5.1 Existing Conditions There are quite many historical buildings in the site. Some of them are abandoned. Although they bring a better image to the city, They are making the traffic more complicated. The complicated traffic network is one of the reasons that caused the traffic problems. The traffic network cannot hold a large amount of vehicles while more and more people working and living in the place. Because of the complicated traffic network, pedestrain have to pass though several streets to get to anoter place. Some people are passing the street even when the red light is on. This is also one of the reasons that caused accidents. Some sidewalk in the site is only 2-3 metres wide, which clearly cannot hold a huge amount of pedestrains.

Straford International Station

Stratford Underground Station

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5.2 Space Syntax Analysis The map on the left is angular segment analysis with radius as 1000 and it shows the integration of the road network. The zoom-in area is the Stratford station area with high integration and choice value,and roads with bright color means the ones with higher value. It can be concluded that important bus routes or tube station are usually located at the places with high visibility an connectivity.

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5.3 Data Visualization Data analytic can be done by using computer language. As python is one of the most dominate computer languages, we start by transferring the data into heatmap for further analysis. The heatmap show the value of each data and the relationship with their location of the site.

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5.4 Data Layering The diagram below are the relationship between all the data shown in the previous page by using python. Then we ran these data though PCA (Principle Component Analysis) and Clustering Analysis, which are the algorithm of machine learning. The result shown on the right, where the brighter area illustrate the locations that have more relations between different data.

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5.5 Multi-layer Data Synthesis With all the layers overlapping, it can be seen that the loop with higher brightness is the place where the values of the bus stop concentration, the incidence of pedestrian going through, the negative energy and the accidence frequency are high, However, the cycle frequency is rather low at the loop.

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5.6 Points Selecting In order to connect identified spaces for further design, we selected the points with high value of data intersection as well as the data of interest points. The location shown in this image have high potential of gathering people.

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5.7 Building up Networks We use three kinds of algorithms to generate the road network. The algorithms mainly creates the shortest path between multiple points. These algorithms can generate a more efficient road network. The three algorithms are grid spreading capture, kernal density and wooly path. We ran the algorithms several times and we got different results. Then we chose only one result each algorithm to do further design because those three results shows a better recognition of road network.

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5.8 Grid Spreading Capture As the first approach to discover the possible ways to connect our kernel points in our site, we do different experiments by changing parameters including the number of segments and strength, which can influence the connecting paths. This definition uses points to pinch grid pathways. The logic of this method is : 1. Create a grid 2. Measure distance between grid intersections and pinch points 3. Remove points outside of the desired radial range from each pinch point 4. Replace points within the range with pulled points overlapping the pinch points 5. Remove overlapping points that exist in the same x,y,z coordinates 6. Connect points to make new pinched grid

Grid Spreading Capture Sample in 3 Dimension

Grid Spreading Capture Sample in 2 Dimension

Grid Spreading Capture Sample in 2 Grasshopper

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5.9 WoolyPath The strategy of the design comes a research of Frei Otto. Frei Otto was a German architect and structural engineer noted for his use of lightweight structures. He was awarded the Pritzker Architecture Prize in 2015.

The reaserach is called the minimal path system. Minimal path system is a simulation system that can optimal the route lenghth. In a derect path system, every point is connected with every other point by the shortest route. In 2009, he published a book called Occupying and Connecting. In this book, he illustrated several experiments de did in order to explain the system more clearly.

Wool-thread Model Wool-thread model is one of the model from Detour path networks experiment. The image on the left side is a ring with dry wool connected and the image on the right side is the same model wet wool connected together. The wet wool is adsorbed together by the tension of water, forming a transformation of multiple paths into one single path. The intention of this experiment is to reduce the total length of each point to direct path.

Source: Wool-thread model, Frei Otto, Institute for Lightweight Structures (ILEK), Struttgart, 1991

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5.10 Kernel Density Estimation-based Edge Bundling Edge bundling is a recent, increasingly promising, technique which generates graph layouts of limited clutter. Bundled layouts can be used to get insight into the coarse-scale of network, geographical maps, and software systems. Kernel Density Estimation-based Edge Bundling is equivalent to sharpening the edges' density map. This in turn pulls edges towards the center of their local point spatial distribution, which achieves the Bundling. Given an initial graph drawing, it can be converted to a density map using kernel density estimation (KDE) and the normalized density map gradient can be computated so that each edge will be moved in the gradient direction.

Yeast graph (6646 edges) source from: University of Groningen

Amazon graph (899792 edges) source from: University of Groningen

Amazon graph (899792 edges) source from: University of Groningen

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5.11 Integration Analysis We chose only one result each algorithm to do further design because those three results shows a better recognition of road network.

The integration analysis in 500 metre and 1000 metre shown below illustrates that the the newly designed kernal density and wooly path have higher integration with the surrounding road network, while grid spreading capture doesn’t have much spatial connections with the existing road network.

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5.12 Choice Analysis The choice analysis in 500 metre and 1000 metre shown below illustrate the potential movement of the design. The newly designed kernal density road network not only show a higher potential of movement value, compared with the integration analysis in the previous page, we decided to use kernal density to do further design.

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6 Design Concept This chapter is going to illustrate how different layers are generated and merged together. In general, traffic flows are divided into three levels. The upper level is the pedestrian and cycling paths.The middle level is the original ground level.

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Hierarchy of Networks In last chapter we analyzed the movement data by translating it into positive and negative energy.

The results of this analysis show a high value of negative energy throughout the area. In order to lower the value of negative energy and increase that of positive energy, our strategy is to create a hierarchical traffic system to distribute the traffic in to different levels. We focus on the level for pedestrian and cyclist to encourage people travel in a healthier way.

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6.1 Hierarchical Traffic System In last chapter we analyze the movement data by transferring them into positive and negative energy. The result shows a high value of negative energy throughout the area. In order to lower the value of negative energy and increase positive energy, our strategy is to create a hierarchical traffic system to distribute the traffic in to different levels. We focus on the level for pedestrian and cyclist to encourage people travel in a more healthy way.

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6.2 Pedestrian and Bicycle Level The first level is designed for pedestrian and cyclist. The concept of this level is to build a highway for generating positive energy. The points starts from the location chosen in the previous chapter. We adjust the road network with the existing condition and add some spaces to the place that have higher value of integration and choice. Some of the selected points are chose to be the connecting nodes of multiple levels.

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starting points of pedestrian level connecting nodes with ground pedestrian surface connecting nodes with other two layers designed route of pedestrian level designed pedestrian route santander bicycle docking points

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6.3 Public Transportation Level The mid level is for public transportation. We start by designing the road network by analyzing the bus routes and bus stops. The aim is to distribute the bus routes of the area and adjust the numbers of the bus stops so that every part of the site have at least one bus stop. While distributing the bus routes can decrease the possibility of causing traffic congestion, the newly designed bus routes enable people to travel more efficiently as well as not sacrificing the convenience of getting to some popular places

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6.4 Vehicle Level We place the vehicle, which may generate negative energy, to the level under the ground level. The aim is to build tunnels so that vehicles can pass though the are more efficiently. We also set some parking areas for residents who live in Stratford city.

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underground car network starting points connecting nodes with other two levels underground level car network ground level car network entrance and exit of temporary parking lots underground parking lots

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6.5 Flow System This is an image of three level over lapped. The white lines are the pedestrian and bicycle level, blue lines are bus level and red lines are car level.

The circle symbols are the connecting points of the multilevel.

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6.6 Spatial Strategy Different spatial strategies are used in different kinds of situation. Adding pedestrian path above can separate different kinds of traffic system to different levels. It also creates some extra spaces to add some extra functions such as extra greening.Some buildings are closely attach with the path, which also increase the connectivity between the road and the building. The path has a high connectivity not only within buildings, but also between parks. They also play as an extension greening belt since it used to have a boundary between buildings and parks.

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7 Synapse City The central proposal of this project is the redesign of derelict site in the area which will be converted into a central hub for mobility. The design process started by using an algorithm called field line. Given a number of fixed points [which we made to correspond to the major circulation nodes in the area], this algorithm can generate a series of flow line. We set some points and used as inputs for the field line to reinforce the interaction between the new circulation paths proposed and the existing road network. Then we simplified the lines and employed as a starting point for the next design iteration.

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7.1 Field Line Growth The existing Stratford city centre is one of the reason why the movement of Stratford appears in chaos. By designing a more fluent movement for this place, we start by generating the flow lines by using an algorithm called field line. We observed the formation and extract some of the lines, then adjust the height of the lines to create landscape and buildings according to the location of nodes and the designed road networks. The generation process give rise to the connectivity between every elements of the design.

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7.3 Catalogue of Typologies Different kinds of design strategies are used to create the landscape of the design to make the buildings and the landscape as well as the surroundings are connected more fluent. The aim is to make the design become one part of the flow system of the designed road network.

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7.4 Design Scheme Analysis This is an image showing every single components of the design. There are the road network for pedestrian and bicycle, the buildings and landscape of the center of the site, the road network of public transportation, the road network of vehicles and the connecting points of different levels. It can be lifts, stairs or ramps.

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7.6 Visibility Graph Analysis Visibility graph analysis investigates the properties of a visibility graph derived from a spatial environment. The analysis can be applied to two levels, eye level for what people can see, and knee level for how people can move which is critical to understand spatial layouts.

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ABM Simulation of Movement Potential2 20000 Timesteps 0.1 Agent per TS 30 Field of View 5 Steps to Decision 1000 Agent TS

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ABM Simulation of Movement Potential1 Timesteps 20000 Agent per TS 0.1 Field of View 20 Steps to Decision 3 Agent TS 1000

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ABM Simulation of Movement Potential3 Timesteps 20000 Agent per TS 0.1 Field of View 15 Steps to Decision 5 Agent TS 1000

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ABM Simulation of Movement Potential1 Timesteps 20000 Agent per TS 0.1 Field of View 20 Steps to Decision 3 Agent TS 1000

ABM Simulation of Movement Potential2 Timesteps 20000 Agent per TS 0.1 Field of View 30 Steps to Decision 5 Agent TS 1000

ABM Simulation of Movement Potential3 Timesteps 20000 Agent per TS 0.1 Field of View 15 Steps to Decision 5 Agent TS 1000

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ABM Simulation of Movement Potential1 Timesteps 20000 Agent per TS 0.1 Field of View 20 Steps to Decision 3 Agent TS 1000

ABM Simulation of Movement Potential2 Timesteps 20000 Agent per TS 0.1 Field of View 30 Steps to Decision 5 Agent TS 1000

ABM Simulation of Movement Potential3 Timesteps 20000 Agent per TS 0.1 Field of View 15 Steps to Decision 5 Agent TS 1000

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3D-view of Time-based Movement Potential Analysis

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ABM Simulation of Movement Potential1 Timesteps 20000 Agent per TS 0.1 Field of View 20 Steps to Decision 3 Agent TS 1000

ABM Simulation of Movement Potential2 Timesteps 20000 Agent per TS 0.1 Field of View 30 Steps to Decision 5 Agent TS 1000

ABM Simulation of Movement Potential3 Timesteps 20000 Agent per TS 0.1 Field of View 15 Steps to Decision 5 Agent TS 1000

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3D-view of Time-based Movement Potential Analysis

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ABM Simulation of Movement Potential1 Timesteps 20000 Agent per TS 0.1 Field of View 20 Steps to Decision 3 Agent TS 1000

ABM Simulation of Movement Potential2 Timesteps 20000 Agent per TS 0.1 Field of View 30 Steps to Decision 5 Agent TS 1000

ABM Simulation of Movement Potential3 Timesteps 20000 Agent per TS 0.1 Field of View 15 Steps to Decision 5 Agent TS 1000

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7.7 Energy Combination Map After the design, we calculated the positive and negative energy again by using the same methods. Before the design, the value of negative energy is extremely high. With the design of a new movement. The value of negative energy is decreased and all part of the site appears with positive energy.

energy map before design

energy map after design

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7.8 Energy Flow The green dots of this image are the positive energy that people create by burning calories. The design of synapse city creates a more efficient and healthy movement for city by working with the movement data and flows with different speeds.

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