Studio 3: Design Proposal for a Liveable Neighbourhood

ABCDE CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Made in Hulme Proposal of a design system for creating a liveable urban space Aaron Underhill Raya Pavlova Shambhavi Joshi

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Introduction Having previously explored how rapid urbanisation and densification affects cities, it was concluded that the approach to address this would be in the form of an urban system which addresses said issues, in order to minimise the negative effects and create more sustainable and liveable cities. The primary focus is walkability that promotes a healthy urban environment. The strategy is compactness of cities which identifies inhabitants’ home proximity to amenities including green spaces. Walkability is measured against two parameters of locations of amenities and green spaces in order to achieve a self-sufficient design.

ABCDE

The exploration of generative design theories and urban strategies have provided an interpretation of the generic design parameters essential for a liveable urban neighbourhood.

As a context specific approach, the use of participatory urbanism assists in gathering data to determine a number of parameters is used to drive a generative design model capable of producing a wide variety of iterations which can be measured against the aims of the designer and participants. This results in an optimised design which meets the criteria in question which can be taken forward.

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

This model is further enhanced through the exploration of urban design strategies including street network generation and parcel subdivision as well as acknowledging design considerations such as the distribution of building typologies and the need for adequate green open spaces and amenities within an urban landscape.

The conclusion of this project is a redefined neighbourhood created by a system tested in the context of Hulme, Manchester, where 90 residents (1.25%) within the area, were successfully surveyed. This system has conveyed the percentage of walkability achieved and a densified urban region whilst providing the required area per person of green space and amenities. Adapted to a rising population, it also addresses The UN’s Sustainability goals 9 and 11.

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Atelier Approach An Overview of learnings from Studio 2, carrying forward the design drivers to Studio 3 and listing the parameters of design

Studio 2: DESIGN OF AN URBAN NEIGHBOURHOOD

Data collection

Data Analysis

• • • • •

Walkability Desification Diversification Participatory Urbanism Inferences from surveys

• • • • •

Street networks Urban grid patterns Layouts and sizes of green spaces Building typologies Area of Amenities

METHODOLOGY

Generative Design

Studio 3 parameters

ABCDE

Combined Design Drivers: • Sustainable Development Goals • Promoting Walkability • Access to amenities • Design system

Optimisation CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Studio 2: Aaron Underhill, Raya Pavlova , Shambhavi Joshi

Digitalisation and Testing

• Walkable neighbourhood prioritizing pedestrians • Equal access to Green Spaces • All age groups friendly amenity areas • Active frontage • Lively streets

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Contents Page

A. Designing an Urban System.................06 B. Applying the Design System on a Local Level.................31 ABCDE

C. Evaluation Process.................55 D. Project Deliverables.................83

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

E. Reference.................90

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Thesis Statement High congestion, the distance of location and lack of amenities, along with a neglect for pedestrian priority, have all resulted in the degradation of the neighbourhood.

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However, this can be remedied through the approach of creating a walkable diverse and pedestrian orientated urban landscape. This can allow citizens take the initiative of living a sustainable lifestyle through a compact neighbourhood which promotes 6 key principles: An increase in local autonomy, connectivity, proximity, diversity, participation, and adaptability.

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

As a result, this design thesis aims to recreate an area of Hulme, Manchester, as a self sufficient and sustainable neighbourhood which promotes walkability.

This requires a firm understanding of the demands and needs of demographics within the area. This will be achieved through the approach of participatory design, where the involvement of citizens is embodied to realise the future scope of development within Hulme.

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CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

A Designing an Urban System

• Problem identification • Design a unique system to solve urban problem independent of context • Apply a context dependent system ABCDE

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Work Flow Overview Method of work

Urb an

u di o

ABCDE

Choice 2

Choice 3

Outcome

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Choice 3

Choice 2

Designer 2

Choice 1

Designer 3

Choice 1

* Case study dependent

Survey

Choice 3

Data

Designer 1 Choice 2

3D model

Goals

Choice 1

Research

Finalise Option 3

4 051 Iterations

Option 2

Ballot

Elimination

Evaluation

Team

Option 1

System

St

Arr a y s

90 Participants

Chapter A

Chapter B

Chapter C

Chapter D

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What are we proposing?

A complex urban system Why are we proposing a complex urban system?

To increase the liveability of more cities/ towns and diminish the urban densification of most populated cities

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How are we designing a complex urban system?

1) We identify the primary problem - densification, diversification and compactness of cities 2) We identify the secondary problem - citizen participation in urban planning and design 3) We measure walkability against requirements for green space and amenity distribution, and size per person 4) We involve the public to identify aims 5) We identify limitations, objectives and approach on a local level 6) We test the system on a local level 7) We introduce the most optimum design for an urban design project as a summary of data collection, computational optimisation, design decision making and participatory feedback

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

What is the focus of designing a complex urban system?

Walkability and providing access to green spaces and amenities Why is walkability the focus of designing a complex urban system?

1) It is a constraint any neighbourhood is dealing with is how far a person is willing to go before using a vehicle and identifies allocation of resources within a walking distance 2) It is as a measure to increase the liveability and quality of life of the neighbourhood, as well as human mental and physical well-being 3) It is a measure for residential, commercial and green area distribution within a neighbourhood

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ABCDE CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

View of Park as a space for interaction, socialisation and a meting point for all age groups

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Primary Problem Identification Using compactness strategy in evaluating the liveable design of a neighbourhood

Xm2 of land per person

Pedestrians

30 min

5 min

15 min

Park 10 min

Public Transport

Shop

Taxi/ Transport

2 min

Ownership of Cars

Post-office 8 min

Density

Proximity and Self-sufficiency

Urban density refers to the number of people living in m2 of land. In the case of compact cities, it refers to keeping residents close to community amenities. The buildings are low to compliment the human scale, give access to green spaces and encourage views.

When a person has access to everything they need in the community they live in ranging from stores to banks, then the city is self-sustaining. Ideally, the amenities in a compact city are located within a walking distance from where people live.

Flowerbeds

Cyclists

Pedestrians’ Priority The objective of a compact city is to design a walkable community which means that it supports and encourages pedestrian traffic. The flow of pedestrian traffic focuses on increasing the total area of sidewalks, green spaces, etc.

Trees Parks

ABCDE

School

Bank

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Work

Green Space Flowerbeds, trees, parks, etc areas are the elements of a city that define green spaces. These are the areas that create the landscape of the community and do not only enhance the aesthetics of it but also help fighting CO2 emissions.

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Secondary Problem Identification Master planning approach to fill the gap in urban design

Local

Presentation to partners, developers or public

tem sys

Propose

esi

gn

Planning the project and estimating the impact, cost, etc.

Implement the ideas of the public

ABCDE

ho wit

gap the fill

: To nity rtu Opp o

ch

h

Passive Design Participation through 3D space exploration

roa

Consult

app

oac

ppr

na

Inform the public

Consult Information, announcements, public hearings

-up

dow

Listen Gathering of demands and existing patterns

tom

Collecting ideas and information of successful projects

Bot

Top

ur d

Facilitate

Involve Active Design Participation through workshops, digital design tools

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Central

Government Decide

Public/ Citizens Collaborate • Interviews • Questionnaires • Collaborative mapping

Action: To create a system for livable cities using bottom-up approach

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Input and Output Parameters For an urban design system that can be applied everywhere

Urban grid layouts

Problem Identification

Population density, etc

Research Framework System

Generic Design Parameters Design Process

Amenities

Urban Design Theories

Design Development

Urban Masterplan

ABCDE

Green Space

Optimisation and Evaluation

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Promoting walkability to achieve a liveable neighbourhood by providing access of open green spaces and amenities within walking distance

Data Site Parameters

Context

Boundary

Participatory Urbanism

Survey

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1. Introduction to the reasoning for creating an urban system related to walkability ABCDE

2. Explain green space and

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

amenity parameters used against walkability

3. Showcase importance of

walkability through densification, diversification and urban grids

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Attractors and Detractors Parameters for a desirable neighbourhood and their effects

+

+

+

+

+ +

+

-

-

+

+

-

-

+

+

The more green space, the more outdoor activities The more cycling lanes, the more healthy population

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

+

The Less The more large roads, the more vehicles

ABCDE

+

The Less

+ + +

Large roads The more large roads, the less pedestrians

Green space The more green space, the less wasted space

Cycling lanes The more cycling lanes, the less parking

-

The less large roads, the less vehicles

The less green space, the less outdoor activities

The less cycling lanes, the less healthy population

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Neighbourhood Design Elements Outlining suggested elements and variables Community Space Options Economic

Ame

n

e

Public

nc

Des

Walkable

s Prefere

ign

itie

Conside r

ons a ti

Large multi-family Low-rise: between 1 and 5 floors, 50-400 dwellings Mid-rise: between 5 and 9 floors, 30-110 dwellings High-rise: more than 9 floors, more than 100 dwellings

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

s s es s m

A ite

Small multi-family Detached Semi-detached Terraced house

Proje c

ssumptio

S

Transport Infrastructure Options

-

tA

t en

Office and Retail Low-rise: less than 7 floors Mid-rise: between 7 and 25 floors High-rise: more than 25 floors Skyscrapers: more than 40 floors

+

ns

Si

Commercial

Residential

les

Neighbourhood

n Variab

Traditional

ABCDE

D ig es

Transform e t

on a ti

Building Typology Options

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Designing Walkability Features Conceptual framework

• Sidewalk width • Traffic volumes • Building height • Number of people • Street width • Vegetation

• Enclosure • Transparency • Complexity • Linkage • Human scale • Coherence

• Sense of safety • Sense of comfort • Sense of belonging • Level of interest • Level of engagement • Level of interest

Physical Features

Urban Design Qualities

Individual Reactions

ABCDE

More Subjective

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More Objective

Overall walkability

Walking behaviour

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1. Introduce the reason

to create an urban system related to walkability

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

2. Explain green space and amenity parameters used for walkability 3. Showcase importance of

walkability through densification, diversification and urban grids

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Walkable Distance from Home to Amenities Distance proximity of amenities

ABCDE

Walking

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Cycling Using tram/ train

Using bus

Mapping the number, distance, mode of commute and number of people using a certain amenity and understanding the different scales of amenities required at various levels of urban planning

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Walkability Against Amenities Characteristics

Health

Commercial

Religion

Category

se fu eo

er v

Hyperblock level

Primary school

Hyperblock level

Secondary school

Hyperblock level

University

City level

Library

Neighbourhood level

Community centre

Neighbourhood level

Co-working centre

Neighbourhood level Hyperblock level

Sport centre

Neighbourhood level Hyperblock level

Sport field

Neighbourhood level Hyperblock level

Playground

Neighbourhood level

Health centre

Neighbourhood level

Grocery shop

Neighbourhood level

Restaurant

Neighbourhood level

Cafe

Neighbourhood level

Worship place

Neighbourhood level

Planning aspects

Age group

Access

COVID-19

ABCDE

Ch an g

es lin On

Pr iva te

lic

65 Pu b

e: >

Ag

565 e: 3

Ag

Ag

e: 1

-1 5 e: 3 Ag

-3 e: 0

535

n io Ag

Di

st

rib

ut

io ut rib st

Di

st

Nursery school

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Sport

an ce

n Social

Di

ea Ar Educative

ice

Defining amenities and their characteristics

Level

Importance of settings when planning a neighbourhood Design and space considerations The most important aspects of planning the urban plot are size of amenities or as defined as are is calculated in m2 and distance that is showcased in metres distance. Distribution varies in terms of scale and number of amenities of such kind. Age group corresponds to user groups of amenities. The concept of online services is and change of use are taken into consideration after the COVID-19 pandemic.

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Walkability Against Open Green Space Studying cities around the world and their open green space per capita in m2

30

1 PERSON

28.3

9 m2

minimum

23.1 20 14.0

x

5.6

4.4

Mumbai, India

6.5

Barcelona, Spain

9m2 3.5

ABCDE CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Tokyo, Japan

Moscow, Russia

World Health Organisation Standards

Paris, France

Toronto, Canada

Madrid, Spain

Area in m2

New York, USA

0 Rotterdam, Holland

per person

11.5

10

City, Country

x

12.6

Setting the minimum open green space area Required open green space per person “To measure dynamic characteristics of public spaces, one of the most frequently used indicators is the area of public spaces per person; “9 sqm per person” has been quoted as a universal standard...Another way to look at the availability is the share of public spaces out of built-up areas. Inclusiveness is often measured by the percentage of population living within walkable distance (e.g. 400m) to public spaces.” World Bank Group

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1. Introduce the reason

to create an urban system related to walkability

2. Explain green space

ABCDE

and amenity parameters used against walkability

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

3. Showcase importance of walkability through densification, diversification and urban grids

ABCDE

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Population Density per km2 Studying cities their and country perspectives around the world

x

Russia 4 per km

37 742 154

Canada x x

509 per km2 17 134 872

36 per km2

Holland x

x x

123 per km

65 273 511

Japan

France

x

India x

Spain

x

x

450 per km2

126 476 461

1 380 004 385

93 per km2 46 754 778

Most Dense Country

Density Per City

x

348 per km2

ABCDE

331 002 651

USA

2

Least Dense Country

City

Mumbai

Paris

Barcelona

New York

Moscow

Tokyo

Madrid

Toronto

Rotterdam

Density/ km2

21 000/ km2

20 000/ km2

16 000/ km2

10 715/ km2

8 537/ km2

6 158/ km2

5 300/ km2

4 334/ km2

3 087/ km2

Population

20 411 274

2 148 000

5 585 556

8 175 133

12 537 954

37 393 129

3 300 000

6 196 731

644 618

Most Dense City

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

x

x

145 934 462

2

x

x

x

9 per km2

Least Dense City

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Densification and Diversification Creating a diverse infrastructure for an increasing population

Site boundary

Low rise

Densification

Street grid network

Diversification

ABCDE

Green areas

Densification

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Mid rise

Pedestrianised

Diversification Typologies mix

High rise

Urban strategies By adopting both densification and diversification as theoretical approaches within the design process, this results in the outcome of an urban landscape which can adapt to the needs to their citizens.

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Grid-network and Block Variations Learning from the Great American City grid street and basic building typologies

Utah block

Georgia block

Benefits • Short path, increased walkability • Length and width of each block influences building design and context • Facilitates wayfinding and directness of route desired Urban block distribution

Potential

Mid-rise type

High-rise type

New York block

ABCDE

Portland block

Low-rise type

“...frequent streets and short blocks are valuable because of the fabric of intricate cross-use that they permit among the users of a city neighbourhood.”

Jane Jacobs, The Death and Life of Great American Cities

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Block typology Generic shape

American typical block by state

Great American city grid street

Short block = short walk

Rationalising the urban grid Previous studies using axial maps and topological distances (Hillier et al, 1993) have shown that movement flows throughout the city are strongly affected by the urban grid, which naturally creates a system in which journeys tend to pass through the most accessible locations. In such studies, the shortest path between two locations is interpreted as the least number of “changes of direction” between them.

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Grid-network Measures of Connectivity

Low-rise type

Mid-rise type

Block size

400m reach network distance mapped across different block sizes

High-rise type

Low-rise type

Large block

Block type

Small block

High-rise type

Mid-rise type Block type

x = 200m

x = 100m y = 100m

y = 200m Mixed use

Block size

Block size

Block size 100 to 225 metres

Diverse Typology

Reach Distance

Diverse Typology

Reach Distance

Diverse Typology

ABCDE

+

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

m

0

0

m

m 0

40

40

Street width 50 metres

40

-

+

+

+

-

Reach Distance

Reach Distance

Street width 25 to 50 metres

m

Reach Distance

0

m

m

-

40

0

0

40

40

-

Street width 50 metres

Determining an effective urban pedestrian network An effective urban pedestrian network is often identified by block length of about 60-90 metres and a maximum of about 100 metres. This is linked to the fact that the average walking distance is generally assumed to be around 400–500m gives us the measures to experiment with a reach distance. However, the walking distance for children, disabled and the elderly is shorter (Gehl 1987). According to Gruen (1965), it ranges from 200m (2 min) to 1,500 m (20 min) depending on the quality of the environment.

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Neighbourhood Urban Strategy Street network generation and parcel subdivision to create diversity x x Population per m2

Area of interest

ABCDE

Urban plot

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x y Plot size

Access points

Node points

Plot formation

Parameters based upon data

Access points identified

Nodes within a boundary

Urban Plot Formation

By using the data collated from the survey participants, a criteria based upon their requirements can be created. Urban plot sizes can be determined by the area of activity, and a population size which would utilise the area.

This can be calculated through the formula below.

Once the site boundary is defined, the site context is explored in regards to circulation routes of the existing street network and areas which may intersect.

The location of amenities are placed in accordance with the data collated to create agent profiles. A street network can then be established by using the Shortest path tool, providing the ability to iterate and optimise different street networks which can then be scored based on the distance between nodes and how each agent profiles’ preferences are affected by each iteration.

Street network has enhanced the formation of urban plots. The resulting spaces from these networks can be utilised according to the placement/ distribution of amenities.

Once parameters are set and nodes assigned to each plot, the urban landscape follows. Massing of the resulting building typologies can be defined through the urban plot size and maximum space allocated; the Z axis can be utilised for excess area requirements for each node.

Area of interestâ&#x20AC;&#x2122;s m2 per person (Y m2) x Population size (X per X m2) = Urban plot size (U m2) < Maximum space allocated

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Deriving the Green Park Shape Defining shape and size of green spaces

PL AG AC OR E/ A T PU HE BL O IC PE SP N AC E

• Ecological benefit • Positive psychological impact • Visual landscape value • Improved air quality • Well-being of community • Well-being of individual Social cohesion and local identity on site in a regular shape

x = 12-24m Alexander “maximum” urban square

Lynch “ideal” urban square y = 12-24m

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• Intersection • Gatherings • Sport activities • Commercial activities • Waiting points for traffic • Usually square form

ABCDE

Park

Square

Physical role

Green

R S FO FIT EA NE AR BE N L EE ICA GR LOG O EC

Public

Preferred urban gird

Ecological role

x = 22m y = 22m

Gehl “optimum” urban square

x = 30-35m

y = 30-35m

The need for open spaces In line with the urban landscape, the shape of green spaces would follow the urban grid to further the narrative of achieving the proximity goals of the required building typologies.

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Massing Strategy Identiying the rules for controlling the massing

(w)

(h)

ABCDE

(h)

(w) (x)

(x)

Input:

height of building (h) width of building (w)

Rule:

the higher the building (h) / the wider the building (w), the wider the distance between buildings (x)

Output:

10 storey (h) = 20 m (x) 25 storey (h) = 28 m (x) 36 storey (h) = 35 m (x)

Input:

height of building (h) width of pedestrian area (w) width of road for cars (x)

Rule:

the higher the building (h), the wider the pedestrian area (w), the narrower the road for cars (x)

Output:

The additional height of buildings leads to increased pedestrian area, denser buildings and less cars

Input:

Correlation of an average walking travel time between a dwelling, office unit, amenities, etc

Rule:

Every dwelling in the neighbourhood should be well-served within maximum 2 minute walking distance

Output:

Resultant is the distance from a residential block to amenity based on population needs

Privacy and density

Active pedestrian streets

Average walking distance

Consideration One Controlling the street width

Consideration Two Controlling the street to pavement ratio

Consideration Three Controlling walkability distance

ABCDE

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(w)

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Design Considerations Identiying the rules for controlling the massing

Residential block (w)

Office block

Mixed use block

)l(

(h)

University block

(a)

Development densities within the perimeter of the block

Rule:

The development densities shall remain with a use as identified by the studies on population needs

Output:

Maximised perimeter and the block permeability measured by sidewalk spaces

Plot ratio defined by grid-network, site outlines and walkability strategies

Rule:

Each plot should have _% of building typology and _% of green area site coverage

Output:

Building area (h/w/l) Building offset green area (a) Green parks (b)

Input:

Defined local urban grid to be reflecting road and pedestrian network, and entry points

Rule:

Keep size of plots up-to 200m on the 4 sides, increase walkability and visibility

Output:

Increased walkability, visibility and security reclaimed for the use of pedestrians, decreased traffic flow

Grain city

Plot density and green space

Breathing streets

Consideration Four Controlling typologies

Consideration Five Controlling building offsets

Consideration Six Controlling pedestrian walkways

ABCDE

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Input:

Input:

ABCDE

(b)

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Unified Approach A summary of the methodology in a non-site specific context

Amenities

Buildings

A more in depth study of city layouts and decide upon a layout approach Existing urban layout examined - street hierarchy

Understand the amenity needs based on demographics and participatory data Set location of amenities based on same principle

Building typologies of amenities and how their elements can be applied to massing - materials, orientation, access

Parcel subdivision

Massing

Urban landscape

Rules parameters of parcel subdivision based on population size and people per square metre Define s street hierarchy - primary, secondary roads

Create a massing strategy and height strategy defined by the previous set of parameters and the preferences of interviewees

Finalised cohesive design to wrap up all considerations taken into account when making decisions for the planning of the neighbourhood

ABCDE

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Site

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â&#x20AC;¢ Local level context CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Applying the Design System

ABCDE //31

ABCDE

Work Flow Overview Method of work

Urb an

u di o

ABCDE

Choice 2

Choice 3

Outcome

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Choice 3

Choice 2

Designer 2

Choice 1

Designer 3

Choice 1

* Case study dependent

Survey

Choice 3

Data

Designer 1 Choice 2

3D model

Goals

Choice 1

Research

Finalise Option 3

4 051 Iterations

Option 2

Ballot

Elimination

Evaluation

Team

Option 1

System

St

Arr a y s

90 Participants

Chapter A

Chapter B

Chapter C

Chapter D

ABCDE

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Site Measurements Introducing extents of the site and its dimensions

80.5 m

36.5 m

0m

.8 25

45

m

m

.90

532

328 m

.2

68

ABCDE

m

m

5m

99

232.2

m .7

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

80.9

98.65 m

165.3 80.2

m

m

56.1

m 5 7.4

m

6

Perimeter: 2215.25 m Area: approx. 251,925 m2 Total population: ~7500 Avg. Density: 0.046 people/ m2

.80

217

m

Retaining the primary streets so as to retain the existing transport network in place and also establishing a reference base for new street generation Retaining the existing Trinity school

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Shared Goals

Objective: Plan a walkable and design a resilient neighbourhood

Population: Allow for an increase in population from 8,000 to over 12,000 in 10 years

Approach: Conduct a survey for participatory urban design and analyse the needs of the population

Approach: Improve mobility to public spaces - green parks and commercial uses - amenities

Green space: Distribution of green space in relation to density satisfaction of size and improved access

Action: Use collected data from conducted survey to meet project goalâ&#x20AC;&#x2122;s objective

Action: Use green parks and amenity distribution as a main driver for creating a walkable urban form to meet design goals

Aim: Achieve a minimum of 9m2 per person of green space throughout the neighbourhood

Social Goals

Local Goals

Design Goals

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Objective: Introduce a bottom up approach in (re-)designing neighbourhoods

ABCDE

Applying strategic thinking on a local level

Made in Hulme

ABCDE

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Input and Output Parameters For an urban design system that can be applied to a local level

Urban grid layouts

Problem Identification

Population density, etc

Research Framework System

Generic Design Parameters Design Process Urban Design Theories

Amenities

Amenity Space requirements

Urban Masterplan

Data

Population growth Green Space requirements

Design Development

ABCDE

Green Space

Optimisation and Evaluation

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Promoting walkability to achieve a liveable neighbourhood by providing access of open green spaces and amenities within walking distance

Hulme

Site Parameters

Context

Boundary

Participatory Urbanism

Survey

ABCDE

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Population Growth in Manchester Living in urban areas as an opportunity for diversification of the dense city

Manchester urban region

542 960

598 960

Current population

Future population

Densification By 2034

In 2020

Increase By 2050

2.1 People per household

ABCDE

74m2

Diverse population

Diverse housing

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Diversification

New household space

Diverse economy

Dwelling Size Increase by 2050 Housing cooperation projections Since the overall population of the United Kingdom increases and it is projected to be 66.8 million by 2050, housing will also go under transformation. Expectation of the new dwelling living space will give this project parameters to work on for the future design.

ABCDE

//36

Green Areas Open Space Demands Applying WHO guidelines per person to a local scale

1 PERSON

Distance from one’s home: 400m

Population size: 8000

№ of households: 4000

Green space designation guidelines: 9m2 x 4000 x 2.05

Total requirement for public open space: 73 800m2

ABCDE

Size of local parks and open spaces: 2 hectares = 20 000m2

Ward: Hulme

Average household: 2.05

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Green space per person: 9m2

9 m2

Local Parks and Open Spaces Definition Providing for court games, children’s play, sitting out areas and nature conversation areas.

ABCDE

//37

Amenities Area on a Local Level Distribution and Capacity

Primary/Secondary Schools, Universities

9 m2

Public Squares, Activity spaces

2 m2

Community Centre

9 m2

Green spaces, Public parks

0.42 m2

Retail

1.4 m2

Medical facilities

1.4 m2

Cafe

Number of amenities Types of amenities

ABCDE

2 m2

5 m2

251 925 m2 Total site area

Grocery/ Convenience Stores

Study spaces Library, Co-working space

1.4 m2

Pubs, Clubs

1.4 m2

Restaurants, Eateries, Takeaways

1.5 m2

Multi-faith Prayer space

1.5 m2

Sports Centre

8.83 m2

Workplace

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

0.92 m2

2.32 m2 Average amenities space per person Total area : Total population = Amenities per person

Neighbourhood level planning of amenities distribution Types of amenities and their provision Provision of different types of amenities in the neighbourhood is based on the general area requirements per person per amenity. The total area of amenities per person is calculated based on the total site area coverage divided by the population projection.

ABCDE

//38

Metrics to work with

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Distribution and Capacity

View of open amphitheatre space

ABCDE

//39

Inclusion of Participatory Feedback Incorporating Hulme residents feedback in the design

Working Professional (without family)

o rt any group

Working professional

Retired

• Public squares • Green parks • Commercial centre • Healthcare • Transport facilities

15-20

Student

Sup

Student

p or

t in

dividual g r

Retired

Student

• Schools, university, etc • Religious spaces • Playgrounds • Workplaces

ps ou Business owner

Mark

roups User groups Various linkages and interaction points of user groups

15-20

5-10 min

Working Professional (with family)

action betwe ter

Working professional

Student

5-10

2-5 min

in

g en

Unemployed

10-15

10-20 min

5-10 min

• Cafes and restaurants • Community centre • Common workplaces • Public squares • Entertainment

5-10

5-10 min

Amenity options Where user group needs are taken into account

ABCDE

p

Unemployed

10-15

2-5 min

Interviewees groups

Housing preference

Amenity preference

Hulme population needs and preferences

Population’ Needs Analysis Having organised the participants’ preferences and requirements into subgroups, this information can be used to identify the needs of individuals and shared amenities which can then be incorporated into the design development of the master plan.

ABCDE

//40

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Sup

Small Business Owner with family

Detailed Amenity Requirements of Survey Participants Amenities required by various types of agents based on participatory survey

Working Professional (individual/ without family)

Working Professional (with family)

Small Business Owner with family

Retired

Currently Unemployed

ABCDE

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Student

//41

Participants Amenity Preference Mapping group of agents to understand amenity placement

Grocery/ Convenience Stores

1 AGENT x

preference preference preference

Primary/Secondary Schools, Universities Public Squares, Activity spaces Community Centre Green spaces, Public parks Retail, Workplaces Medical facilities

ABCDE

Cafes, common workspaces Study spaces, Libraries Pubs, Clubs

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Restaurants, Eateries, Takeaways

Amenity preference

Student

Working professional *without a family

Working professional

Retired

*with a family

Small business owner

Agent 18

Agent 17

Agent 16

Agent 15

Agent 14

Agent 13

Agent 12

Agent 11

Agent 10

Agent 9

Agent 8

Agent 7

Agent 6

Agent 5

Agent 4

Agent 3

Agent 2

Agent 1

Multi-faith Prayer space

Unemployed

*with a family

Amenity Placement Strategy With a strong concentration of amenities outside the site boundary, feedback from survey participants showed their preferences for amenities within the proposed urban landscape.

This information will be used to further develop the required number of amenities based upon demand.

ABCDE

//42

Participants Housing Preference Mapping group of agents to understand potential building typologies

Mixed Use (Commercial+Residential) Residential Block, Low Rise Apartment Block University Accommodation, High Rise Apartment Block Individual House, Terraced House

Working professional *without a family

Working professional

Retired

*with a family

Small business owner

Agent 18

Agent 17

Agent 16

Agent 15

Agent 14

Agent 13

Agent 12

Agent 11

Agent 10

Agent 9

Agent 8

Agent 7

Agent 6

Agent 5

Agent 4

Agent 3 Student

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Housing preference

Agent 2

Agent 1

ABCDE

Row Houses, Semi-detached Houses

Unemployed

*with a family

Housing Typology Strategy Further feedback regarding housing preferences conveys each participant groupâ&#x20AC;&#x2122;s requirements for housing. This will be utilised within the design process when creating housing typologies and the volume of each typology required according to demand.

ABCDE

//43

Amenities Spatial Calculations

1.1 m2

250 m2

7-10 m2

8-10

1:1000

Repair stores

1.4 m2

450 m2

75-90 m2

3-4

1:2000

Grocery/ Convenience Stores

1.4 m2

850 m2

75-90 m2

5-6

1:1500

Cafes, common workspaces

1.4 m2

1500 m2

250 m2

2-3

1:3500

Restaurants, Eateries, Takeaways

1.4 m2

1500 m2

250 m2

2-3

1:3500

Medical facilities

1.49 m2

300 m2

40-50 m2

3-4

1:2000

Multi-faith Prayer space

1.57 m2

5400 m2

2000 m2

02

1:3500

Primary/Secondary Schools, Universities

4.7 m2

11 750 m2

3500 m2

2-3

1:2500

Public Squares, Activity spaces

5.1 m2

2500 m2

2500 m2

01

1:5000

Green spaces, Public parks

9.0 m2

2500 m2

100 m2

3-4

1:3500

Space per person (m2)

Total space requirement (m2)

Min. plot area (m2)

No. of amenities

Ratio

Infrastructure category

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Bus stops

ABCDE

Identifying the optimum space requirements for amenities

Defining plot sizes With amenities requirements identified, spatial attributes can then be defined from the population size and site boundary area. Minimum and maximum plot areas for each infrastructure category can be used as parameters for the design optimisation process.

ABCDE

//44

Input and Output Parameters For an urban design system that can be applied with the help of participants

Urban grid layouts

Problem Identification

Population density, etc

Research Framework System

Generic Design Parameters Design Process Urban Design Theories

Amenities

Amenity Space requirements

Urban Masterplan

Data

Population growth Green Space requirements

Design Development

ABCDE

Green Space

Optimisation and Evaluation

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Promoting walkability to achieve a liveable neighbourhood by providing access of open green spaces and amenities within walking distance

Hulme

Site Parameters

Context

Boundary

Participatory Urbanism Survey

Site Demographics

Site specific demands

User Groups 90 participants

ABCDE

//45

Site Specific Methodology Breakdown Working towards one goal - walkability

S

S

S

S

7 tep

5 tep

3 tep

1 tep

Decide on amenities

Decide on building typologies

Generate possibilities

To analyse the existing context of the neigbourhood and its issues based on street patterns, transport network, infrastructure , and user perspectives

To apply already identified opportunities for what people value or need from the conducted interview and to can provide a design to meet their needs

Research, analyse, test and decide on building typologies while taking into account preferences of interview participants

Run a model based on all previous steps in order to make an informed decision for which pattern fit the characteristics a walkable neighbourhood

Clean existing site

Create short walk study

Optimal vision of site

Clean an existing site and prepare a basis to start a test based on improving site conditions while focusing on main goal - walkability

Research on walkable city patterns in order to test a short walk from a household to an amenity that will increase walkability aspect of the project

Research, analyse, test and decide on impact of optimal vision of amenities within the site in order to improve the safety aspect of the project

p

4

Ste

2

Ste

Ste

p

p

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Analyse existing site

6

ABCDE

//46

Stages of Development

Site analysis

Population survey

New grid-network

Stage One

Stage Two

Stage Three

Analyse current site characteristics The observational analysis aims to identify the current characteristics of the site such as buildingsâ&#x20AC;&#x2122; use, road networks, green spaces, amenity distribution, walkability aspects and development opportunities.

Interview population and analyse needs Identify infrastructure opportunities based on collected data from citizens living in the area. The data represents the needs of population which are currently not met and the preferences which will be used to create variations of the project.

New design strategy New infrastructure design strategy aims to introduce connectivity aspects in the studies of compact cities/ neighbourhoods. By adding a new grid-network, new plots, new building typologies and amenity preferences are defined.

ABCDE

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Introduction to design development stages

//47

Stages of Development

Amenity placement

Building placement

Iteration analysis

Stage Four

Stage Five

Stage Six

Identify amenity distribution Based on previously conducted interview of people living in the area, preferred different amenities are distributed randomly on the site in order to conclude iterations where human agents will self-organise around the preferred amenity.

Distribute preferred building typologies Based on previously conducted interview of people living in the area, preferred different building typologies are distributed on the site in order to conclude iterations where human agents will self-organise around the preferred typology.

Allow human agent self-organisation To understand the most suitable preferred amenity and building typology, plenty of potential outputs should be tested and evaluated so that considered urban theories and population needs are achieved towards a walkable neighbourhood.

ABCDE

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Introduction to design development stages

//48

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Aerial View of vehicular route and pedestrian routes

ABCDE //49

ABCDE

Distribution Strategy of Urban Parcels

Total area Placeholder

Total area Placeholder

Total area Placeholder

Total area Placeholder

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Strategic planning of amenitiesâ&#x20AC;&#x2122; provision

Parcel Subdivision Placeholder x

y x

y x x

Distribution within a Site Distribution strategy The distribution of amenities happens in three different strategies based on the size of amenities and their users. The big scale amenities are located close to perimeter roads because of the easy connection to other parts of the city. The amenities within neighbourhood level are located close to people who have highest interest towards those amenities. Block level facilities are at the centre of intersections for best connection.

ABCDE

//50

Defining Massing Density

Amenity as an Attractor

Plot Distribution

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Depicting Urban Typology using Amenity as attractor points

High Density Building Typology around amenities with high attractor points

ABCDE

//51

Spatial Distribution Strategy

Amenity as a Repulsor

Plot Distribution

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Defining the massing around the green park attractor

Low/Medium Density Building Typology around amenities with high repulsor points

ABCDE

//52

ABCDE CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Evaluation Process â&#x20AC;¢ Creating optimised outcomes using generative design ABCDE

//53

Work Flow Overview Method of work

Urb an

u di o Choice 3

Choice 2

ABCDE

Choice 3

Choice 2

Designer 2

Choice 1

Designer 3

Choice 1

Outcome

90 Participants

Chapter A

Chapter B

Chapter C

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

* Case study dependent

Survey

Choice 3

Data

Designer 1 Choice 2

3D model

Goals

Choice 1

Research

Finalise Option 3

4 051 Iterations

Option 2

Ballot

Elimination

Evaluation

Team

Option 1

System

St

Arr a y s

Chapter D

ABCDE

//54

Design Development Explained Following stages of project development

Stage 1

Stage 2

Stage 3

10m 10m Stretford Road Bonsall Street

Booth Street Boundary Lane

Stage 4

Stage 5

Stage 6

Stage 7

Stage 8

Stage 9

Stage 10

Stage 11

Stage 12

Z X

Z

Z X

ABCDE

X

Z

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

X

% Commercial He ight from

low

rise igh rise to h

% Residential % Green land

*Please check additional media files if video does not run

% Street use

ABCDE

//55

Input and Output Parameters Incorporating the inferences into the process as input parameters and evaluating them against necessary output parameters Road Offset Urban Grids Population density, etc

Research Promoting walkability to achieve a liveable neighbourhood by providing access of open green spaces and amenities within walking distance

Framework System

No. of Green spaces Size of Green spaces Input parameters

Generic Design Parameters Design Process Urban Design Theories

Amenities

Amenity Space requirements

Design Development

Urban Masterplan

Data

Population growth Green Space requirements

Output parameters

ABCDE

Green Space

Optimisation and Evaluation

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Urban grid layouts

Problem Identification

Hulme

Site Parameters

Context

Boundary

Participatory Urbanism Survey

Site Demographics

Site specific demands

User Groups 90 participants

ABCDE

//56

Parcel Subdivision Experiments

*video

*video

*video

No Control

Limited Control

Majority Control

Random street network With the aid of the computational tool, DeCoding Spaces, a street network can be established within the defined site boundary. However, with no parameters set with regards to the plot widths, no clear urban pattern can be defined; the outcome results in an organic street network driven by street orientation and density/street frequency, which then influences the urban block layout.

Addressing anchor points The street network can have a somewhat controlled pattern through the definition of a street hierarchy. This is done by identifying an existing main route to use as an anchor point, which secondary and tertiary streets can be created from. This also leads to the basic control of the resulting urban plots, where the minimum width of all plots can be raised or lowered.

Creating rules for plot boundaries Street hierarchy and plot parameters are combined to define the urban landscape. By creating rules for plot boundaries based on the nodes (amenities) locations and population size, a min plot area can be defined which will accommodate the appropriate building typology. Street hierarchy remains, with main roads identified as primary routes, and is further developed.

ABCDE

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Street Network Generations

//57

Detailed Building Typologies Defined through participatory feedback and plot calculations

Typologies

Flats block

Mixed-use

Student Accommodation

Low-rise

Mid-rise

Row house

Mixed-use

Library

Single family house

Retail

ABCDE

High-rise

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion GSEducationalVersion

GSEducationalVersion

Office

Semi detached house

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

Mixed-use

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

GSEducationalVersion

ABCDE

//58

Residential Building Typologies Dimensions

h = 8000mm

w = 78

00mm

GSEducationalVersion

mm

0 00

7 l=

h = 16000mm

w = 15

000mm

h = 10000mm

l=

mm

0 00

31

h = 42000mm

GSEducationalVersion

00mm

GSEducationalVersion

m

0m

l=

0 60

ABCDE

w = 85

h = 16000mm

GSEducationalVersion

0

w = 11

70

700mm

7 l=

mm

w = 15

000mm

l=

mm

m

0 00

31

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

h = 8000mm

GSEducationalVersion

l=

w = 10

000mm

m 00

0

18

GSEducationalVersion

Low-Rise Housing

Mid-Rise Housing

High-Rise Housing

Low-rise is considered between 1 and 5 floors in height and it accommodates 1-2 dwellings. Considered maximum height is 12 metres.

Mid-rise is considered between 5 and 9 floors in height and it accommodates 30-110 dwellings. Considered maximum height is 30 metres.

High-rise is considered more than 9 floors in height and it accommodates more than 100 dwellings. Considered maximum height is 50 metres

ABCDE

//59

Commercial Building Typologies Dimensions of commercial - office, retail Le

ve l3 40 00

Le

ve

l2 0

h = 47000mm h = 29000mm h = 15000mm m

200

00m

m

l=

m 000

30

w=

w= 110

00m

m

l=

m 00m

120

00m

m

000mm

l = 24

110

ABCDE

w=

h = 31000mm CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

h = 27000mm h = 13000mm w=

mm

110

00m

m

l=

00 210

w=

mm

100

00m

m

l=

00 180

w=

110

00m

m

m

l=

0m 100

1

Low-Rise Commercial

Mid-Rise Commercial

High-Rise Commercial

Low-rise office buildings are considered between 1 and 5 floors in height.

Preferred maximum height is 15 metres.

Mid-rise is considered between 5 and 9 floors in height and ground floor is allocated for retail purposes only. Preferred maximum height is 30 metres.

High-rise is considered more than 9 floors in height and is allocated to office use only. Ground floor area is used for reception/ access to the building. Considered maximum height is 50 metres

ABCDE

//60

Commercial Building Typologies Dimensions of mixed use - housing, retail, leisure, education

h = 50000mm

h = 25000mm

h = 12000mm

Le

ve

l0 0

mm

110

00m

m

l=

00 200

w=

100

w=

mm

00

00m

m

l

50 =2

200

mm

0m

m

l=

00 200

ABCDE

w=

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

h = 42000mm h = 21000mm

h = 14000mm w=

200

00m

m

l

m

m 000

0 =2

w=

m

400

00m

m

0m 500

4 l=

w=

700

mm

0m

m

l=

00 200

Low-Rise Commercial

Mid-Rise Commercial

High-Rise Commercial

Low-rise office buildings are considered between 1 and 5 floors in height.

Preferred maximum height is 15 metres.

Mid-rise is considered between 5 and 9 floors in height and ground floor is allocated for retail purposes only. Preferred maximum height is 30 metres.

High-rise is considered more than 9 floors in height and is allocated to office use only. Ground floor area is used for reception/ access to the building. Considered maximum height is 50 metres

ABCDE

//61

ABCDE CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

View of various building typologies planned across the segregated Stretford road

ABCDE

//62

Optimisation Process Placeholder

Basic building forms and types

Good iterations

Bad iterations

Form parameters: length, height, width

ABCDE

1, 2, 3 ... 4051 Maximum values 4.0 20 6 200 9.0 35 20 000 165 000 50 000 10.0 3 60 000

Road Setback Plot Randomiser Green Space No Green Space Plot Randomiser Road offset-green space,school Plot Threshold People-site Green space-context [m2] Green space on site [m2] Green space per person [m2] Amenity space per person [m2] Amenity Space-site [m2] Basic building forms and types

Minimum values 2.0 0 4 50 6 20 0 145 000 30 000 0 0 20 000

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Optimisation process

Promoting walkability: Min length of road - 30m Max length of road - 100m

ABCDE

//63

Generating Design Iterations Generated design explained

Number of green spaces around the site is generated

Green space distribution around the site is randomised

Road offset dedicates space for extra mobility activities

Plot sizes are generated and volumes of blocks are created

Population density is projected to affect all metrics

Distribution of green spaces to achieve desired walking distance

Total green space to satisfy population density metrics

Green space allocation of 9m2 per person (WHO standards)

x

Max

Road offset

Plot randomiser

Number of green spaces

Green space randomiser

Road offset - green space

Plot threshold

People on site

4.0

20

6.0

200

9.0

35

24 000

8.5 3.5

15

5.5

3.0

10

5.0

22 000

165 000

20 000

160 000

Green space on site

50 000

100

x

x

Green space per person

Amenity space per person

14

3.0 60 000

30

18 000

7.5

45 000

12 2.6

155 000

40 000

4.5

50

25

150 000

35 000

145 000

30 000

2.4

2.2

12 000

Min

40 000

8

14 000 6.5

50 000

10

16 000 5

Amenity space - site

2.8

7.0 2.5

Total amenity space to achieve desired walking distance

x

150 8.0

Mid

Green space - context

Amenity space allocation per person calculated in m2

ABCDE

Plot randomiser affects the urban grid layout of the project

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Offset of a line on both sides so that a road is created

0

30 000

6 2.0

Generative design parameters By using Design Explorer, an open source tool to explore design iterations, a large number of design options can be generated based on set parameters.

These parameters are defined through design strategies applied to the design process and feedback from survey participants which has been translated into measurable metrics.

ABCDE

//64

Generated Design Iterations Design evaluation explained

x Road offset

Plot randomiser

Number of green spaces

Green space randomiser

Road offset - green space

Plot threshold

People on site

Green space - context

Green space on site

x x

x

Green space per person

Amenity space per person

Amenity space - site

Max

Mid

Iteration #2

Iteration #3

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Iteration #1

ABCDE

Min

Attributes iteration #1 Attributes iteration #2 Attributes iteration #3

ABCDE

//65

Extreme Inputs Testing outcomes of extreme values of two inputs at once Evaluating maximized, medium and minimized values of inputs - Plot grid Randomizer and Green space location randomizer Maximized

Medium

Minimized

Max

Max

Max

Min

Mid

Mid

Min

Min

2

20

201

6

x 18507

166526

51611.7

9

35

2

12

x x

8.99

51

5

x x

2.31

42842

16894

154049

39135

7

27

4

0

x x

9.11

1

5

6

x x

2.37

40081

15107

151513

36599

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Mid

20

x x

10.02

x

2.39

ABCDE

36216

//66

Extreme Inputs Testing outcomes of extreme values of two inputs at once Evaluating maximized, medium and minimized values of inputs - Plot grid Randomizer and Green space location randomizer Maximized

Medium

Minimized

Max

Max

Mid

Mid

Mid

Min

Min

Min

3

4

1

6

x 14 986

160527

45613

7

20

4

4

x x

9.47

151

6

x x

2.11

42789

14 986

156 909

41 994

7

20

4

4

x x

10.46

151

6

7

x x

2.71

40 734

14 986

156 909

41 994

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Max

20

x x

10.46

x

2.71

ABCDE

40 734

//67

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Green park used as a buffer from the Mancunian Highway

ABCDE //68

ABCDE

Urban Design Iterations Parameter Driven Massing Iteration 1

Iteration 2

Iteration 3

Iteration 4

Iteration 5

Max

Mid

Min

Site Population: 17,950 Green space per person: 7.8sqm Amenity space per person: 2.4sqm

Site Population: 18,953 Green space per person: 7.4sqm Amenity space per person: 2.5sqm

Site Population: 15,720 Green space per person: 9.4sqm Amenity space per person: 2.6sqm

Iteration 6

Iteration 7

Iteration 8

Iteration 9

Site Population: 13,234 Green space per person: 11.1sqm Amenity space per person: 2.5sqm

Site Population: 15,917 Green space per person: 9.4sqm Amenity space per person: 2.4sqm

Site Population: 17,385 Green space per person: 9.5sqm Amenity space per person: 2.5sqm

Site Population: 16,687 Green space per person: 9.9sqm Amenity space per person: 2.5sqm

Iteration 10

Iteration 11

Iteration 12

Iteration 13

Site Population: 17,102 Green space per person: 8.8sqm Amenity space per person: 2.2sqm

Site Population: 18,586 Green space per person: 8.1sqm Amenity space per person: 2.4sqm

4

4

151

6

x 14 986

Site Population: 18,384 Green space per person: 7.8sqm Amenity space per person: 2.7sqm

Site Population: 17,661 Green space per person: 8.4sqm Amenity space per person: 2.5sqm

156 909

41 994

7

20

x x

10.46

x

2.71

40 734

ABCDE

//69

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Site Population: 15,248 Green space per person: 9.2sqm Amenity space per person: 2.5sqm

Urban Design Iterations Parameter Driven Massing Iteration 14

Iteration 15

Iteration 16

Iteration 17

Iteration 18

Max

Mid

Min

Site Population: 18,560 Green space per person: 8.1sqm Amenity space per person: 2.4sqm

Site Population: 12,418 Green space per person: 11.7sqm Amenity space per person: 2.4sqm

Site Population: 13,380 Green space per person: 11.5sqm Amenity space per person: 2.4sqm

Iteration 19

Iteration 20

Iteration 21

Iteration 22

Site Population: 18,560 Green space per person:8.1sqm Amenity space per person: 2.4sqm

Site Population: 18,249 Green space per person:7.9sqm Amenity space per person: 2.5sqm

Site Population: 13,771 Green space per person: 11.2sqm Amenity space per person: 2.2sqm

Site Population: 12,876 Green space per person: 13.1sqm Amenity space per person: 2.6sqm

Iteration 23

Iteration 24

Iteration 25

Iteration 26

Site Population: 19,217 Green space per person: 7.5sqm Amenity space per person: 2.5sqm

Site Population: 13,751 Green space per person: 9.2sqm Amenity space per person: 2.3sqm

3

4

151

4

x 15 085

Site Population: 20,233 Green space per person: 7.1sqm Amenity space per person: 2.7sqm

Site Population: 18,303 Green space per person: .9sqm Amenity space per person: 2.8sqm

147 982

33 068

6

20

x x

980

x

2.25

33 954

ABCDE

//70

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Site Population: 20,585 Green space per person:7.3sqm Amenity space per person: 2.5sqm

Urban Design Iterations Parameter Driven Massing Iteration 27

Iteration 28

Iteration 29

Iteration 30

Iteration 31

Max

Mid

Min

Site Population: 15,126 Green space per person: 11.1sqm Amenity space per person: 1.5sqm

Site Population: 16,375 Green space per person: 9.4sqm Amenity space per person: 2.5sqm

Site Population: 16,639 Green space per person: 8.7sqm Amenity space per person: 2.5sqm

Iteration 32

Iteration 33

Iteration 34

Iteration 35

Site Population: 15,517 Green space per person: 9.9sqm Amenity space per person: 2.4.sqm

Site Population: 15,628 Green space per person: 10.7sqm Amenity space per person: 2.4sqm

Site Population: 16,886 Green space per person: 8.9sqm Amenity space per person: 2.7sqm

Site Population: 16,982 Green space per person: 8.9sqm Amenity space per person: 2.4sqm

Iteration 36

Iteration 37

Iteration 38

Iteration 39

Site Population: 17,092 Green space per person: 9sqm Amenity space per person: 2.5sqm

Site Population: 17,575 Green space per person: 9.5sqm Amenity space per person: 2.6sqm

3

4

101

5

x 15 906

Site Population: 15,827 Green space per person: 9.5sqm Amenity space per person: 2.5sqm

Site Population: 16,095 Green space per person: 10.4sqm Amenity space per person: 2.2sqm

145 305

30 391

5

24

x x

9.13

x

2.39

38 167

ABCDE

//71

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Site Population: 14,896 Green space per person: 10.7sqm Amenity space per person: 2.4sqm

Iteration 40

Iteration 41

Iteration 42

Iteration 43

Iteration 44

Max

Mid

Min

Site Population: 13,176 Green space per person: 11sqm Amenity space per person: 2.6sqm

Site Population: 21,806 Green space per person: 6.9sqm Amenity space per person: 2.8sqm

Site Population: 13,176 Green space per person: 11sqm Amenity space per person: 2.6sqm

Iteration 45

Iteration 46

Iteration 47

Iteration 48

Site Population: 11,992 Green space per person: 14sqm Amenity space per person: 2.5sqm

Site Population: 12,751 Green space per person: 13.2sqm Amenity space per person: 2.5sqm

Site Population: 11,992 Green space per person: 14sqm Amenity space per person: 2.5sqm

Site Population: 12,751 Green space per person: 13.2sqm Amenity space per person: 2.5sqm

Iteration 49

Iteration 50

Iteration 51

Iteration 52

Site Population: 13,155 Green space per person: 11.7sqm Amenity space per person: 2.4sqm

Site Population: 13,435 Green space per person: 11.5sqm Amenity space per person: 2.7sqm

4

4

151

5

x 13435

Site Population: 13,155 Green space per person: 11.7sqm Amenity space per person: 2.4sqm

Site Population: 13,435 Green space per person: 11.5sqm Amenity space per person: 2.7sqm

154944

40030

9

20

x x

11.53

x

2.76

37063

ABCDE

//72

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Site Population: 21,806 Green space per person: 6.9sqm Amenity space per person: 2.8sqm

Generated Design Iterations Designerâ&#x20AC;&#x2122;s input and considerations on choosing final output

Designer 1 - Raya Pavlova

Preferred iteration #3

Preferred iteration #2

Road offset: 4 Plot randomiser: 4 Green Park No: 4 Green space randomiser: 101 Road offset-green space,school: 7 Plot threshold: 24 People-site: 14 046 Green space-context [m2]: 141 006 Green space on site [m2]: 26 092 Green space per person [m2]: 10 Amenity space per person [m2]: 2.70 Amenity space-site [m2]: 37 963

Road offset: 4 Plot randomiser: 16 Green park No: 6 Green space randomiser: 151 Road offset-green space,school: 7 Plot threshold: 20 People-site: 14 986 Green space-context [m2]: 156 909 Green space on site [m2]: 41 994 Green space per person [m2]: 10.46 Amenity space per person [m2]: 2.71 Amenity space-site [m2]: 40 734

Road offset: 4 Plot randomiser: 0 Green park No: 6 Green space randomiser: 151 Road offset-green space,school: 6 Plot threshold: 20 People-site: 15 805 Green space-context [m2]: 156 909 Green space on site [m2]: 41 994 Green space per person [m2]: 9.92 Amenity space per person [m2]: 2.73 Amenity space-site [m2]: 43 175

Attributes iteration #1

Attributes iteration #2

Attributes iteration #3

Residential

Commercial

Park

School

Residential

Commercial

Park

School

Residential

Commercial

Park

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Preferred iteration #1

School

ABCDE

//73

Generated Design Iterations Designerâ&#x20AC;&#x2122;s input and considerations on choosing final output

Designer 2 - Shambhavi Joshi

Preferred iteration #3

Preferred iteration #2

Road offset: 2 Plot randomiser: 8 Green park No: 5 Green space randomiser: 101 Road offset-green space,school: 9 Plot threshold: 24 People-site: 16 984 Green space-context [m2]: 145 305 Green space on site [m2]: 30 391 Green space per person [m2]: 8.55 Amenity space per person [m2]: 2.25 Amenity space-site [m2]: 38 243

Road offset: 2 Plot randomiser: 4 Green park No: 6 Green space randomiser: 151 Road offset-green space,school: 7 Plot threshold: 20 People-site: 17 565 Green space-context [m2]: 156 909 Green space on site [m2]: 41 994 Green space per person [m2]: 8.93 Amenity space per person [m2]: 2.31 Amenity space-site [m2]: 40 708

Road offset: 3 Plot randomiser: 4 Green park No: 4 Green space randomiser: 151 Road offset-green space,school: 6 Plot threshold: 20 People-site: 15 085 Green space-context [m2]: 147 982 Green space on site [m2]: 33 068 Green space per person [m2]: 9.80 Amenity space per person [m2]: 2.25 Amenity space-site [m2]: 33 954

Attributes iteration #1

Attributes iteration #2

Attributes iteration #3

Residential

Commercial

Park

School

Residential

Commercial

Park

School

Residential

Commercial

Park

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Preferred iteration #1

School

ABCDE

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Generated Design Iterations Designerâ&#x20AC;&#x2122;s input and considerations on choosing final output

Designer 3 - Aaron Underhill

Preferred iteration #3

Preferred iteration #2

Road offset: 2 Plot randomiser: 8 Green park No: 6 Green space randomiser: 1 Road offset-green space,school: 7 Plot threshold: 27 People-site: 16 010 Green space-context [m2]: 160 527 Green space on site [m2]: 45 613 Green space per person [m2]: 10.02 Amenity space per person [m2]: 2.24 Amenity space-site [m2]: 35 875

Road offset: 3 Plot randomiser: 4 Green park No: 5 Green space randomiser: 101 Road offset-green space,school: 9 Plot threshold: 24 People-site: 15 906 Green space-context [m2]: 145 305 Green space on site [m2]: 30 391 Green space per person [m2]: 9.13 Amenity space per person [m2]: 2.39 Amenity space-site [m2]: 38 167

Road offset: 2 Plot randomiser: 8 Green park No: 4 Green space randomiser: 101 Road offset-green space,school: 6 Plot threshold: 27 People-site: 18 526 Green space-context [m2]: 141 006 Green space on site [m2]: 26 092 Green space per person [m2]: 7.61 Amenity space per person [m2]: 2.71 Amenity space-site [m2]: 50 388

Attributes iteration #1

Attributes iteration #2

Attributes iteration #3

Residential

Commercial

Park

School

Residential

Commercial

Park

School

Residential

Commercial

Park

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Preferred iteration #1

School

ABCDE

//75

Manual Selection of Design Iterations Designerâ&#x20AC;&#x2122;s input and considerations on choosing final output

Designer 1+2+3

Designer 2 iteration #3

Designer 3 iteration #2

Road offset: 4 Plot randomiser: 16 Green park No: 6 Green space randomiser: 151 Road offset-green space,school: 7 Plot threshold: 20 People-site: 14 986 Green space-context [m2]: 156 909 Green space on site [m2]: 41 994 Green space per person [m2]: 10.46 Amenity space per person [m2]: 2.71 Amenity space-site [m2]: 40 734

Road offset: 3 Plot randomiser: 4 Green park No: 4 Green space randomiser: 151 Road offset-green space,school: 6 Plot threshold: 20 People-site: 15 085 Green space-context [m2]: 147 982 Green space on site [m2]: 33 068 Green space per person [m2]: 9.80 Amenity space per person [m2]: 2.25 Amenity space-site [m2]: 33 954

Road offset: 3 Plot randomiser: 4 Green park No: 5 Green space randomiser: 101 Road offset-green space,school: 9 Plot threshold: 24 People-site: 15 906 Green space-context [m2]: 145 305 Green space on site [m2]: 30 391 Green space per person [m2]: 9.13 Amenity space per person [m2]: 2.39 Amenity space-site [m2]: 38 167

Iteration attributes

Iteration attributes

Iteration attributes

Residential

Commercial

Park

School

Residential

Commercial

Park

School

Residential

Commercial

Park

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Designer 1 iteration #2

School

ABCDE

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Work Flow Overview Method of work

Urb an

u di o Choice 3

Choice 2

ABCDE

Choice 3

Choice 2

Designer 2

Choice 1

Designer 3

Choice 1

Outcome

90 Participants

Chapter A

Chapter B

Chapter C

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

* Case study dependent

Survey

Choice 3

Data

Designer 1 Choice 2

3D model

Goals

Choice 1

Research

Finalise Option 3

4 051 Iterations

Option 2

Ballot

Elimination

Evaluation

Team

Option 1

System

St

Arr a y s

Chapter D

ABCDE

//77

Participatory Feedback

Get feedback

Interactive consultation

Public

Ask for feedback Give direct feedback

ABCDE

Designers

Computation Technology

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Design

Shortlisted iteration for final design proposal

Consultation feedback: • add an extra green park • make one high street feature • redistribute green parks Taking the feedback to create final model of the shortlisted design

ABCDE

//78

Testing Outcome Final design evaluation

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Road Offset: 5 Plot Randomizer: 4 No. of Green spaces: 5 Green Space Randomizer: 101 Road Offset from Green space: 6.1 Plot Threshold: 20 People on Site: 14586 Green space - context: 148990.25 sq m Green space - site:34076.0 sq m Green Space per person: 10.43 sq m Amenity space per person: 2.389 sq m Amenity Space - site: 35880.12 sq m

ABCDE

//79

ABCDE CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Project Deliverables â&#x20AC;¢ Drawing set of the final generative outcome A B C D E F G //80

Master Plan Explaining how the design outcome fits in with the context of the site

nia

Hatch

tre eS

idg

oa d

br

m Ca

nW ay

Hulme Park

n Way

et

nia Mancu

Stretford Road

Higher Ca

Birely Campus MMU

Manchester School of Architecture

treet mbridge S

eet

Booth Str eet

Booth Str

Trinity C of E High School

ess R oad Princ

enh ays Gre

Lan

e

ad

ays

o Oxford R

enh

Lloyd Street

Lan

e

UoM University Campus

Gre

ABCDE

Princess Road

All Saints Park MMU

A B C D E F G //81

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ncu

Oxford R

Ma

Master Plan Characteristics

Walkability access of amenities

Walkability access of green parks

Walkability Access

Amenities

Shopping Restaurants

Cafes Healthcare

Services Education

Amenity Locations

Green spaces

6 - 10m Low Rise 10 - 15m Low Rise

16 - 28m Mid Rise 28 - 32m Mid Rise

32 - 40m High Rise 40 - 50m High Rise

Building Heights and their spread across site

A B C D E F G //82

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

An representation of the walkability and accessibility measures of the final design outcome

Site Sections and Response to Context Longitudinal site sections highlighting treatment of existing and proposed site features Deta il

1

Deta il

2

Manchester freeway

Green median to separate cycle corridor and vehicular road

___m wide Poynton Street (Existing)

Tree plantations acting as a buffer

__m wide Stretford road

Low Rise Housing Typology

Recreational Green Park

Leisure Park for Residential Area

__m wide Road

Stretford Pedestrian Promenade Mid-Rise Row House Apartments

Low Rise Housing Typology

Bonsall Street

3

Corner Shop and Amenity Centre for Community

ABCDE

Low Rise to Mid Rise to High Rise Hierarchy of Housing

Manchester School of Art

The Assembly

Bright Building

MMU Business School

Liberty Living Apartments

Crowne Plaza

Unite Student Apartments

Duffield Court

A

Long Section AAâ&#x20AC;&#x2122; Aâ&#x20AC;&#x2122;

Longitudinal site section explaining the spread of green parks on site, the massing hierarchy of buildings, segregation of pedestrian and vehicular traffic on Stretford road and architectural response to Manchester freeway by creating a landscape buffer and a dense green park to minimise noise and also to establish a physical site boundary

0.5 0

1.5 3.5

A B C D E F G //83

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Deta il

Site Sections and Response to Context Longitudinal site sections highlighting treatment of existing and proposed site features Deta il

4

5

Narrow vehicular street with restricted access for school convenience of school children

Recreational green space for surrounding residential area

Mixed Use building typology with Ground Level for Commercial Use Public Square to promote interaction of all age groups

Hise Rise typology for MMU Student Accomodation

Cycle friendly track with restricted car access to residents

Green spaces for leisure

Cycle friendly street

__m wide Road Trinity School (Existing)

6

Stretford Commercial Pedestrian Promenade

Perimeter Block with private green spaces

___m wide Stretford Road

Deansgate Tower Complex Hulme Bridge

The Assembly

Duffield Court

William House

Unite Student Apartments

Trinity School (exiting)

B

Long Section BBâ&#x20AC;&#x2122; Bâ&#x20AC;&#x2122;

Longitudinal site section through existing school building explaining the narrow streets developed besides school complex for ease of walking restricting the vehicle speed, the low rise to high rise hierarchy from green park to MMU campus area, the commercial public square acts as an integrator for MMU campus and the Hulme community

0.5 0

1.5 3.5

A B C D E F G //84

ABCDE

Green plantation buffer from existing street

Deta il

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Deta il

Site Sections and Response to Context Short site sections highlighting treatment of existing and proposed site features Deta il Local shopping/ common workspaces

Deta il

7

8

9

Green avenue created for future development use such as open parking, temporary kiosks or 2nd promenade

Vehicular Road

Commercial, amenities, cafes, etc

Deta il

Mixed Use building typology Amphitheatre + Community Centre

Public square

Pedestrianized Street

Stretford Road Pedestrian Promenade

Commercial lower levels of building

Detail showing increment in building heights beginning from low rise near green parks to high rise on the site periphery

Short Section CC’

C’ D’

C

E’

D E

Short Section EE’

Short Section DD’ Short sections representing the scenarios at different locations of site, explaining the connectivity through green parks, segregation of vehicular and pedestrian commute and placement of recreational and community development amenities.

0.5 0

1.5 3.5

A B C D E F G //85

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

ABCDE

Pedestrianized street

Spatial Character of Green Spaces

• Designed to be located at the edge of the site where MMU teaching campus ends • Promotes open interactions, provides a space for art, provides green zones • Caters to all age groups of people • Designed to encourage growth and well-being of students in university halls, visitors, other Hulme residents • Provides a notion of a landmark of entering Hulme; acts as an urban borderland

Stretford Promenade

Community Park • Defines the edge of the site towards Hulme bridge • Acts as a community park promoting growth of community, a place of interaction promoting development of individual and diverse community groups • Provides a place for leisure, retreat, relaxation and/or group interaction

• The proposal provides a segregation of the pedestrian and vehicular movement along Stretford road as it is a main route of commute for many • The Promenade bears mixed use and commercial housing typologies with amenities like retail, cafes, shops, restaurants, etc on the lower floors • The street is designed to promote local businesses as well as commercial stakeholders • The promenade marks as a mode of interaction between various age groups and acts as a connector of the Multipurpose park and the Community park

A B C D E F G //86

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

Multi-purpose park

ABCDE

An insight into application of amenity data and user group spatial analysis into design of green parks on site

CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

References

ABCDE //87

ABCDE

References

James, Paul; Holden, Meg; Lewin, Mary; Neilson, Lyndsay; Oakley, Christine; Truter, Art; Wilmoth, David (2013). “Managing Metropolises by Negotiating Mega-Urban Growth”. In Harald Mieg and Klaus Töpfer (ed.). Institutional and Social Innovation for Sustainable Urban Yue, Ricci, et al. “The Human Dimension of Visibility Degradation in a Compact City.” Natural Hazards, vol. 82, no. 3, July 2016 Haaland, Christine, and Cecil Konijnendijk van den Bosch. “Challenges and Strategies for Urban Green-Space Planning in Cities Undergoing Densification: A Review.” Urban Forestry & Urban Greening vol. 14, no. 4, 2015 Dempsey, Nicola (2010) Revisiting the Compact City? Built Environment 36

ABCDE

Wolsink, Maarten. “Environmental Education Excursions and Proximity to Urban Green Space – Densification in a ‘Compact City.’” Environmental Education Research, vol. 22, no. 7, Oct. 2016 Jenks, M., Burton, E. and Williams, K. (Editors), 1996, The Compact City: A Sustainable Urban Form?

Eiu.com. (2020). The Worldwide Cost of Living Survey. [online] CPU studio 03 | Aaron Underhill, Raya Pavlova & Shambhavi Joshi

McKinsey (2018). Thriving amid turbulence: Imagining the cities of the future. [online] McKinsey (2017). Future of Cities | McKinsey & Company. [online] Institution, G. (2019). How to Put Participatory Urban Planning into Practice? Our mission today.

ABCDE

//88