Benjamin Sayers - M.Arch Thesis Project (Studio 3)

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SOUND MIND: THE FUTURE CAMPUS ADAM CHOWN, BEN SAYERS, DAN CRUSE ST3 PORTFOLIO


THESIS STATEMENT “If we continue to neglect the interconnected relation between space, activity and sound, we will most certainly fail to create sustainable urban development where the sonic environment is included as an important and self-evident aspect of the human experience.� Hallgren (2012)

THE PROBLEM

METHODOLOGY

SOLUTION

Increased environmental noise in urban areas has a direct correlation with increased mental illnesses.

We aim to use methods and lessons from the pavilion experimentation to design a building scale project.

Our solution is to develop a multi-faceted noise preventative framework which can be utilised on other scaled projects.


INTRODUCTION This project leads on from the experimentation of mental health prevention through sound therapy within a pavilion. We aim to tackle multiple ways environmental noise can be eradicated through different design methods at the building scale. The methods could potentially see application for new build or re-use of urban scale or occupancy scale projects.


OVERVIEW

STUDIO 1

STUDIO 2

STUDIO 3

Theory & Computational Methods

Architectural Problem

Output Pavilion Experimentation

Site Specific Context

Develop Method

Building Scale Project

Site Specific Context


0.1

02 APPROACH

IDENTIFICATION

03 METHOD

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01 PROBLEM

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04 CONTEXT

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05 DESIGN

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DEVELOPMENT

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The aim of this project is to design a system, which will in turn allow us to design a building.

n t a ti o

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06 EVALUATION

SYSTEM CONNECTIONS

SYSTEM WIDE INTERACTIONS

Temperature Control

Increased Daylight

Noise Prevention

Increased Ventilation

Measure Noise from Source

07 PROJECT

View Availability

References

This portfolio builds upon our previous research in acoustic application for the benefit of mental health. Our thesis takes experimentation from a pavilion test bed to a building in an urban context.

Measure Noise from Source

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3pm

Thesis Context

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1.0 2.0 3.0 4.0

APPROACH

METHOD

CONTEXT

PROBLEM IDENTIFICATION In this chapter we explore the issue of mental illness in a modern climate, through the increase in environmental noise, and how solutions can be addressed through the architectural medium.


HOW CAN ARCHITECTURE PREVENT MENTAL ILLNESS? In this chapter, we explore the ways in which mental illnesses can be seen as an architectural problem, and how we can go about solving these problems.


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1.1

MENTAL HEALTH

MORTALITY

Statistics DISEASE

1 in 4 people experience mental illnesses

Sleep Disturbance, Cardiovascular

each year[1]. Mental illness is the single largest burden of disease in the UK[2], being more common, longer lasting and impactful than other health conditions[3].

RISK FACTORS

Blood Pressure, Cholesterol, Blood Clotting, Glucose

There are roughly 6000 suicides each year and it’s the biggest killer of men under the age of 49, with the majority of mental conditions developing within people’s

STRESS INDICATORS

adolescent years[4]. We have identified mental health as

Autonomous Response, Stress Hormones

4.4 in 100

Post traumatic stress disorder (PTSD)

5.9 in 100

Generalised anxiety disorder

wider context. For this reason we aim to

7.8 in 100

Mixed anxiety and depression

3.3 in 100

Depression

present a thesis project which can aid the

20.6 in 100

Suicidal thoughts

2.4 in 100

Phobias

6.7 in 100

Suicide attempts

1.3 in 100

OCD

7.3 in 100

Self-harm

0.6 in 100

Panic disorder

an emergent concern within today’s

development of mental illness prevention. [1], [2], [3] - https://mhfaengland.org/mhfa-centre/research-and-evaluation/mental-healthstatistics/ [4] - https://www.bbc.co.uk/news/health-41125009 https://www.mentalhealth.org.uk/statistics

FEELINGS OF DISCOMFORT Annoyance, Disturbance

Number of People Affected


1.2

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Mental Health Stress

URBAN SOUND PLANNING

Increased Disease

Planning of the Acoustic Qualities in an Urban Environment

Decreased Productivity

Urban Planning does not consider sound with any significance, and as a result, creates micro-stressors in people’s lives.

Fatigue

“If we continue to neglect the interconnected relation between space, activity and sound, we will most certainly fail to create sustainable urban development where the sonic environment is included as an important and self-evident aspect of the

Sleep Deprevation

human experience.” Hallgren (2012)

Architecture

Communications

Materiality Reverberation Form & Facade

Sensors Technology

Services

Communities

Construction Transport Vehicles Commercial Activity

Steps Voices Sports Activities

References https://www.unece.org/fileadmin/DAM/trans/doc/2016/wp29grb/GRB-63-05e.pdf

Negative Wellbeing

“We need more pronounced architectural tools to optimize the living conditions for urban inhabitants exposed to urban noise, which is causing psychoacoustic annoyance and even hearing loss. A sonically stressed population may also be productively impaired” Ponten (2009)


for mitigating and controlling the urban soundscape. Many of these methods are

OUR PROJECT FO CUS

application, however there is justification for other means. These include the use of electric cars and other modes of electric transport, and community knowledge of noise pollution. We will focus our

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controlling and manipulating internal and

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external noise to meet current and future programatic requirements. velo pe

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An overview of the possibilities found

found through practical architectural

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Architectural & NonArchitectural Ways of Treating and Mitigating Environmental Noise in an Urban Setting

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PREVENTION VS TREATMENT

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TION A G I T I M L A R U T ARCHITEC

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ON I T A G I T I OTHER M

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THE ENVIRONMENTAL NOISE CONTINUUM It may seem counter-intuitive to combat environmental noise with architecture, with the largest proponent being traffic noise, however the issue of environmental noise will remain through numerous ways after vehicles have become fully electric.


1.0

PROBLEM IDENTIFICATION

2.0 3.0 4.0 5.0

METHOD

CONTEXT

DESIGN DEVELOPMENT

APPROACH In this chapter, we explain the theories and computational methods which we will be using to develop our project.


HOW CAN COMPUTATIONAL TOOLS INFLUENCE THE DESIGN PROCESS? In this section we build upon our knowledge of generative design from our pavilion experimentation to further our computation competence, in order to better inform our design.


Generation

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An initial population is randomly generated with a sparse variety of genomes/phenomes. A small segment of these solutions will be suitable to carry forward.

2.1

GENETIC ALGORITHMS How can we Automate Generative Design with Computation? To carry out an evolutionary process with the use of computation, each function of the generative process must be written in code. The total process of this can be described as “Genetic Algorithms.�

Start Generation Generation

Crossover Parent 1 P1 C

P2

Parent 1

Calculate Individual Fitness

Child

Crossover

Crossover Selection

In our project, an initial group of designs will be generated and their fitness values are calculated. Depending on their fitness value, a feedback loop of random selection, breeding and mutation is implemented until a suitable design iteration is found. This is not a fully automated process and requires human input to decide which design iterations are suitable.

Phenomes are selected from two individual solutions (parents) and crossed over to create the next generation (child) which takes phenotypes from both parents.

Generate Initial Population

Using a set of performance metrics we can decide which phenotype are most desirable in the specific environment. These individuals are classed as suitable and selected for further crossovers.

Selection Mutation Finally, a minority of children will mutate, which develops a larger gene pool, in which new phenomes developed can be carried into later generations.

Yes

End

No

Random Selection of Parents Crossover to Produce Children

Selection

Mutation Mutation

Does Generation Satisfy Stop Criteria?

Mutation of Children

Evolutionary Process


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2.2

EXPLORING THE DESIGN SPACE The Human Interaction with Generative Design With the creation of the design space in mind, we created a design space which holds a balance of bias and variance, continuity and complexity, exploration and

Generate

Evaluate

Evolve

We must designate a ‘design space’ as a closed system which can generate all possible solutions for the design

This develops measures in which the system judges each design performance.

The use of evolutionary algorithms to search through the design space and select unique high performing designs.

exploitation. In this exploration, we decide on our spatial configuration in which the spheres represent our desired spaces. With a balanced design space, we were able to z

generate around 100 iterations which gave enough variety.

x

y

Using certain tools we can filter through a large number of iterations by defining what the desired outcome should be. By selected more suitable solutions, we can carry a strong ‘gene pool’ to the next

Parameters = X, Y and Z axis

stage of the process.

https://medium.com/

Vector of Input Data

Objective Functions

Constraint Functions

Input parameters that encompass every possible output

The objectives/goals of the optimisation

Constraints describe the feasibility of the possible solutions

Objectives = Minimise the volume of the box around the box inside Constraints = Maintain the volume of the internal box


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2.3

COMPLEX ADAPTIVE SYSTEMS What is a Complex Adapative System? A complex adaptive system is a system

The CAS Dismantled

in which a perfect understanding of individual parts and interactions does not auatomatically convey a pefect understanding of the whole systems behaviour. each individual agent interacts

Volume

and creates system wide patterns this will then influence the future interactions and the loop will continue, meaning the final

Porosity

Effectiveness Void

ouput will not be clear through the input.

Proximity

Transportation

Vertical layers

Function

Accessibility Horitzontal layers

SYSTEM CONNECTIONS


Smart City Sensor

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2.4 Urban Soundscape

In the Context of Environmental Noise

Transportation/ Works

of expertise. In the context of our study into

Without People Present

Relaxing + Nature

Lively

environmental noise the pattern language is a way of understanding the different levels and causes of environemntal noise in an urban soundscape.

Cars Screeching

Noise of Workers

Engines

Music + Chat

People Walking

People Shopping

Children Playing

Birds Singing

Smart solutions for acoustics within an

over urban acoustics. This includes access to live data feeds that can be introduced into building design during the design phase and also post occupancy. It is these methods that should further reinforce a reactive building to a constantly changing urban soundscape. References: [2] Denef, S., 2020. A Pattern Language of Social Media Practice in Public Security. [Online] Available at: http://media4sec.eu/pattern-language/ [Accessed 28 January 2020]. [3] Raimbault, M., 2005. Urban Sounscapes: experiences and knowledge. Elsevier, 22(05), pp. 339-350.

Traffic Lights

Construction Site

Traffic Flow

Coffee Shop

Pedestrian Area

Market Place

Playground with Fountain

Garden

Anticipate citizen demands

used in a number of test cities accross the

Counterract the ever changing urban soundscape

use of a range of acoustic sensors, currently

there is a greater control and governance

Information Park Maintenance

Management System Building Systems Management

BIG Data

Electricity Management

Automation

Air Quality/ Pollution

Limit values Waste Management

Risk evaluation Reactive Solutions

urban environment already exist through

globe. Through using these technologies,

Improve control in noisy and problematic areas

of describing good design practices or

Feed live data into reactive building systems

“patterns�. A pattern language is a method With People Present

Live Data

People Presence

Our inventory refers to a series of connected

patterns of useful organization within a field

Quantify the results of action plans

Make information accessible

ACOUSTIC PATTERN LANGUAGE & SMART SOLUTIONS

Mobility Patterns

Connectivity

Traffic Management

Acoustic & Noise Levels


COMPUTATION FOR OPTIMISATION We can use the previous theories as a framework for the generative methods we learned in studio 1. The application of complex adaptive systems, smart solutions and Christopher Alexander’s Pattern Language can further inform our design methods.


1.0 2.0

PROBLEM IDENTIFICATION

APPROACH

3.0 4.0 5.0 6.0

CONTEXT

DESIGN DEVELOPMENT

EVALUATION

METHOD This chapter explains how we aim to use the knowledge learned in the previous chapter, which has been built upon from the ST2 submission.


WHAT ARE THE GOALS OF THE PROJECT? Other than manipulating sound to combat environmental noise in Central Manchester, we need to aim to use the existing site in a different way, in order to benefit the university’s future.


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3.1

DESIGN OPPORTUNITIES Adaptive Aspects of the Building We’ve identified 3 individual methods for

Entrance

responsiveness to environmental variability,

Office

which ultimately allows the building to react more effectively to external stimulus. The geometry manipulation consists of either volumetric adpativity or internal adaptivity, the latter being a more achievable method of noise management.

Catering

Facade treatment allows for the effective deflection/absorption of noise before it

Teaching

reaches the internal environment, which we will be exploring as a responsive mechanism. Programmatic arrangement allows for the flexibile adaptivity of the internal environment and is a viable solution to preventing noise. We aim to simulate how sound is distributed on site at specific times and find the optimal arrangement without the need for it to be adaptive.

Geometry Manipulation

Facade Treatment

Programmatic Arrangment


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3.2

DESIGN PROCESS A Step by Step Projection to Outline our Design Process.

Analyse Envrionmental Data That Interacts With The Chosen Urban Block

Determine The Internal & External Acoustic Qualities & Desired Internal Noise Levels

Internal Panelisation & Room Definition

Define The Building Envelope & Internal Arrangement Based On Adjacency Study

Responsive Ceiling

Identify Sound Source Locations/Types

Noise

Establish Facade Geometry Based on ST1 Study

Defined Adjacency Arrangement Around Circulation Cores

Fixed Ceiling

Map Urban Soundscape & Retrieve Acoustic Data

Establish Facade Absorb or Diffusion

Solar Facade Development & Treatment

This shows our vision for the design process from concept to building. This sequence

Road Traffic Pedestrian Traffic Construction Air Pollution Trams/trains Residential areas Commercial areas

Define Building Envelope

has been influenced by our research in the ST1, Serpentine Pavillion, methodology and

Project Acoustic Information Onto Proposed Massing Elevations

adapted and improved so it can be applied on a larger, building scale.

Facade Panelisation & Rationalisation

Input Noise Data

Divide facade into Equal Segments

Privacy x2 -6d

B

Arrange Adjacecnies Based On Predetermined Data Sets

Identify Appropriate Urban Block

Type A

Iterating Internal Geometry

Establish distance from noise source

Establish decibel reduction over distance

Type B Type C

Daylight dB

48

Determine The Internal Programme & Spatial Qualities Requried

Materiality Number of bounces Distance from noise Decibel rating

Type D

Define Goal for number of Panel types

dB

102

Determine Urban Block Circulation Core

Input Sound Transmission

Determine Vertical Arrangement of Spaces Based on External Acoustic Qualities

Xm2 Xm2

Connecting Internal Spaces

Xm2

Lecture Theatre

3

Seminar Rooms

5

Research Laboratory

2

Cafe

1

Offices

8

Sort Panels based on Different Panel Types

The Determined Adjacency Sizes Interact With Site Specific Data

Establish facade Geometry

Establish Diffuser or Absorber

An Adjacency Arrangement Is Defined

Generate Floor Plates

Distance from noise Programme requirements Materiality Street facing Distance from noise Decibel rating Height from the ground

Sort the Panels into groups by Panel type


Input Parameters

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We are using a variety of number sliders to allow for the manipulation of varying data inputs feeding into a parametric model, modelled in grasshopper to allow for complete design control based of a series of data inputs.

3.3

MASSING

0 1 2 3 4

Linear Semi Private Courtyard Perimeter Atrium Tower

Typologies Input

Building Typology A

B

C

D

E

Iterating to find Number of Floors

Optimal

Generative Algorithm

Input variables and measureable output data sets that we will use to test the urban block’s acoustic performance

4

5

6

7

8

Output Measures

9

The genetic algorithm allows us to explore an exponential amount of design options in order to best satisfy our design goals based of measurable outputs.

Building Depth

We measure the designs generated by the generative algorithm process by a set of predefined goals. To filter through the designs that satisfy the criteria set at the start of the process we can use the output measures to help filter the possible designs

Elevation Orientation 0

Here shows a range of the input variable

0.5

Decibel Levels at Elevation Panels

1

No. Of decibels

Min

that we will use to manipulate each of the

Building Typology Selection

Number of Building Blocks

urban block typologies that we intend to test 0

for acoustic performance. These include

0.5

Environmental Data Input Max

Max/Minimum Decibel Levels

1

Area Sq.

Min

Max

variables involved in its physical form and others are varying testing measures. From

Building Location (X,Y,Z)

the input data set we will acheive a urban

5

6

7

Internal Building Volume

8

9

Min

block typology that we can then test its

Min

can search the design space for outcomes that suit our desired outputs. Here we can

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75

85

Max

Map Privacy

Total Elevation Panel Surface Area (m2)

Desired Access Points

measureable outcomes. We do this so we

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15

25

35

45

Max

Typology A Linear

also cross test different solutions that benefit the buildign design in different ways. An example of trade off would be the

A1

A2

A3

A4

A5

A6

A7

A8

A9

A10

Typology B Perimeter

acoustic performance and how that affects the overall building footprint.

Input Noise Data B1

B2

B3

B4

B5

B6

B7

B8

B9

B10

C2

C3

C4

C5

C6

C7

C8

C9

C10

Typology C Atrium

C1 Typology D Tower

D1

Input Daylight Data D2

D3

D4

D5

D6

D7

D8

D9

D10


Xm2

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3.4

0 1 2 3 4 5 6 7

Input Parameters We are using a variety of number sliders to allow for the manipulation of varying data inputs feeding into a parametric model, modelled in grasshopper to allow for complete design control based of a series of data inputs.

ADJACENCIES

Xm2

Lecture Theatre Collaborative Quiet Study Research Lab Office Retail Accommodation Plant

Programme Spatial Requirements Input Output Measures We measure the designs generated by the generative algorithm process by a set of predefined goals. To filter through the designs that satisfy the criteria set at the start of the process we can use the output measures to help filter the possible designs

on Spatial Acoustic Propoperties Individual Room Placement Efficiency

Room Types

Generative Algorithm

For Each Room Type

0%

0

1

2

3

4

5

6

7

0

100

200

300

400

100%

Overall Room Placement Efficiency Total All Rooms

0%

100%

500

Building Programme Density Internal Acoustic Requirements 25

35

45

0%

20%

40%

60%

80%

Map Adjacencies by Combining External Data

100%

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Room Placement 0 500 Order

1.

Daylight Requirements (lux)

Here shows the input and output variables

The genetic algorithm allows us to explore an exponential amount of design options in order to best satisfy our design goals based of measurable outputs.

Room sizes (m2)

These are the data sets that we intend to use to manipulate the room locations and the output measures we will be testing

Find Optimal Proximities Based

Internal Adjacencies Arrangement

2.

3.

1000

that we are using to manipulate the spaces and their primary adjacencies on the site.

1. Mixed

We are able to use these inputs to generate a number of different scenarios that best suits site specific data. From 1. the changing Room Placement this we can manage a wide rage of design Order options and output the best solutions to compare against each other. This also

1. Retail multiple options allows us to carry forward

3. 4.7.

Retail - Accommodation

Retail - Accommodation - Lecture Collaborative

Retail - Accommodation - Lecture Collaborative

Retail

Single

Room Room Placement Placement Number of Rooms 1. 2. 2.Order Order Retail - Accommodation 1 10 20

1. 3.

Core Generation

1. 4. 2. 3.

2. 5. 3.

3. 6.

Select Building Typology

Retail Retail

A Retail - BAccommodation C D - Lecture E

Adjacencies Fit Around Cores

Collaborative

into the next design phases.

2.4.

Mixed vs Single Use

2. 4.5. 4. 3. 5.

Retail Retail -- Accommodation Accommodation Retail - Accommodation - Lecture Collaborative

4. 7.6. 5.

5. 8. 6.

Retail Retail -- Accommodation Accommodation -- Lecture Lecture -Collaborative Collaborative - Lecture Retail - Accommodation

Envelope Around Adjacencies

Collaborative - Quiet

4. 7.8. 6.

Retail Retail -- Accommodation Accommodation -- Lecture Lecture -Collaborative Collaborative - Lecture Retail - Accommodation Collaborative - Quiet - Lab

6.

7. 9. 8.

8.

Xm2

Lecture Theatre

3

Seminar Rooms

5

Research Laboratory

2

Cafe

1

Offices

8


Lecture Proximity to circulation cores

3.5

25

Collaborative Proximity to circulation cores

Proximity to building perimeter

Noise

ADJACENCIES & VOID GEOMETRY Exploring the Weightings for External Environmental Inputs & Case Study

Daylight

Proximity to ground floor

Views

Proximity to circulation cores

Proximity to building perimeter

Noise

Daylight

Proximity to ground floor

Views

Privacy

Programme placed through testing

Office Proximity to circulation cores

Proximity to building perimeter

Noise

Daylight

Proximity to ground floor

Views

Privacy

Cores placement through Testing Proximity to building perimeter

Noise

Daylight

Proximity to ground floor

Views

Privacy

Privacy

Cut out geometry can be used to manipulae environmental noise

Laboratory

Accommodation

Proximity to circulation cores

Retail

Plant

Proximity to circulation cores

Proximity to building perimeter

Noise

on weightings of each programme toward

Proximity to circulation cores

Proximity to building perimeter

Noise

Proximity to circulation cores

Proximity to building perimeter

Noise

Proximity to building perimeter

Noise

specific environmental requirements. Daylight

Proximity to ground floor

Daylight

Proximity to ground floor

Daylight

Proximity to ground floor

TEK by BIG

Daylight

Proximity to ground floor

From this diagram, you can see the requiements

we

set

out

for

each

programme, and how the weighting

Void area left from programe placment

Areas where the void meets the facade.

In order to create a self-organising adjacency mechanism, we must first decide

Quiet Study

Views

Privacy

Views

Privacy

Views

Privacy

Views

Creates outdoor spaces in an urban environment

Privacy

dictates the most favourable positioning for those programmes. Once weightings are decided, the order of placement then dictates which programme Can be used to filter out stale air and internal noise

has priority of placement where crossover of placement could be an issue. The next chapter expl

Click to View Video

Click to View Video

Click to View Video

Allows people to transition from inside to outside


Input Parameters

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We are using a variety of number sliders to allow for the manipulation of varying data inputs feeding into a parametric model, modelled in grasshopper to allow for complete design control based of a series of data inputs.

3.6

PANELISATION

Spatial Requirements (max dB value) 30

35

40

45

50

Generative Algorithm

Output Measures

The genetic algorithm allows us to explore an exponential amount of design options in order to best satisfy our design goals based of measurable outputs.

We measure the designs generated by the generative algorithm process by a set of predefined goals. To filter through the designs that satisfy the criteria set at the start of the process we can use the output measures to help filter the possible designs

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Xm2 Xm2

Requirements Input

Absorb/Diffuse (Concave/Convex Geometry)

Input Parameters and Performance Metrics To optimally treat a space with the use

Convex

Concave

Spread of Sound

External Facade Geometry Forming

Morph Room Shape 4

5

6

7

8

Min

Absorption

0

1

2

Min

Max

3

FIXED

Frequency Cancellation

We can create a number of solutions to the problem by varying the following input

Min

Scale ‘Acoustic Pocket’

what a successful design is and what an unsuccessful design is.

Max

9

of acoustic panels, we must first know

Kinetic Panel Systems

Max

parameters: spatial requirements (dB value), concave/convex geometry of panels and acoustic pressures, the morphing of the space, the scale of the space and the frequency cancellation. Iterating to find Optimal

By measuring the spread of sound and the absorption of the sound using ray-based and gradient based performance metrics, we can understand what the best solution is.

FLEXIBLE

Xm2

Programme Spatial

Fixed Panel Optimisation

Lecture Theatre

3

Seminar Rooms

5

Research Laboratory

2

Cafe

1

Offices

8


3.7

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PANELISATION

Click to View Video

Click to View Video

Methods for Static and Kinetic Internal Panelisation Programmes vary in acoustic requirements, as specific rooms may need to be more flexible in their response to internal noise than others. The left of the page shows an experimentation toward the reduction of reverberation we carried out in Studio 1, and the right shows a kinetic ceiling for flexible programme.

Number of Attractor Points 8

Distribution of Attractor Points 6

Depth of Acoustic Panel 6

Scaling of Acoustic Panels 10 8

7 5

4

6

2

Number of

70 60

6 5

5

Sound Focus Direction

4

Distribution

4

Depth of

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8

6

7

40

Scaling of Acoustic Panels 10

5 4

6

2

30

Number of

Sound Focus Direction 70 60

6 5

5

Sound Focus

6

Depth of Acoustic Panel

60 50

40

Distribution of Attractor Points

8

50

0

Scaling of

Number of Attractor Points

4

Distribution

4

Depth of

60 50

50 40 40

0

Scaling of

70

Sound Focus

30


Input Parameters

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3.8

Output Measures

We are using a variety of number sliders to allow for the manipulation of varying data inputs feeding into a parametric model, modelled in grasshopper to allow for complete design control based of a series of data inputs.

FACADE

Generative Algorithm The genetic algorithm allows us to explore an exponential amount of design options in order to best satisfy our design goals based of measurable outputs.

Sound Source Location X,Y,Z Axis

We measure the designs generated by the generative algorithm process by a set of predefined goals. To filter through the designs that satisfy the criteria set at the start of the process we can use the output measures to help filter the possible designs

Input Noise Data Facade Sound Diffusion No. Of decibels

Min

Setting Out Clear Goals, Inputs of Data and Measures to Filter Through Potential Facade Design Options

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65

75

85

External Facade Geometry Forming

6

7

8

65

75

Max

Establish distance from noise Establish decibel reduction source over distance

85

Max

9

Material Absorption Factor 0

0.5

Min

15

25

35

45

dB

48

Max

Wall Build-Up From

1

Decibel Readings

to acheive, a set of inputs that we can test Distance from Sound Source

against and a series of measures so as to

dB

102

filter the different design options.

Privacy

For the facade design the inputs were

Temperature Control

9am

9am

collected from the site. The measures were Noise Prevention

Facade Zoning

Privacy

Increased Ventilation

Temperature Control

12pm

and the goals were to meet the internal acoustic requirements of our programme. Temperature Control

Increased Daylight

Noise Prevention

3pm

3pm Noise Prevention

Increased Daylight

Determine Vertical Arrangement of Spaces Based on External Acoustic Qualities

12pm

Privacy View Availability

Increased Ventilation

Privacy View Availability

Increased Ventilation

Temperature Control

Measure Noise from Source

6pm Temperature Control

Increased Daylight

9pm Increased Ventilation

9pm View Availability

Establish Diffuser or Absorber

Increased Daylight

Geometry Formed From

6pm

Privacy View Availability

Noise Prevention

Input Sound Transmission

Increased Daylight

developed for environmental noise data sound transmission and decibel reduction

B

Internal Audible Sound

To test the design of the facade we first must define a set of goals we are looking

55

x2 -6d

Find Decibel Distances

Sound Transmission Class Min

5

No. Of decibels

Min

95

External Acoustic Panel Scale 4

Max

Facade Sound Absorption

Decibel Volume 45

Noise Data Input

Zoning Requirements

Noise Prevention

Increased Ventilation

Establish facade Geometry

View Availability

Establish facade Geometry


Typical

29

3.9

Transition zone

A - Typical

FACADE How does the Data Inform the Elevation?

Fixed zone

By collecting noise data from the site, we were able to evaluate how a building on site would receive this noise, by raytracing

Transition zone

from noise sources to the elevation of the building, and generating a colour for each segment of the elevation depending on the level of noise reaching that point. Hanwha Headquarter by UN Studio (right)

Fixed zone

shows how a facade can react more intelligently to it’s surrounding by having fixed zones where there may be less variation in noise quality, and adaptive zones where a higher variation in amplitude is experienced.

Fixed

We aim to use a similar method. By using the collected data, we can create a facade which is informed by it’s environment.

ENVIRONMENT INFORMS FACADE Transition

Measure Noise from Source

Adaptive

Hanwha Headquarters by UN Studio


THE TRADE OFF Each stage of our design process contains a trade off. Noise eradication priority would come at the expense of other environmental issues, such as daylight, temperature and ventilation. Now the design space has been set, we can begin to optimise how the spaces are arranged and sound internally manipulated.


1.0 2.0 3.0

PROBLEM IDENTIFICATION

APPROACH

METHOD

4.0 5.0 6.0 7.0

DESIGN DEVELOPMENT

EVALUATION

PROJECT

CONTEXT In this chapter, we explore the problem of mental health. We also explore the ways in which a building scale project will react differently to a pavilion project to prevent mental illnesses.


WHAT DID WE LEARN IN STUDIO 1? Our main area of focus was to use the pavilion as an experimentation for methods and design processes to be used at a larger scale.


33

4.1

THE CONTEMPORARY PAVILION Sylvia Lavin on the Contemporary Pavilion Sylvia Lavin identifies two key aspects in which the pavilion can be successful: by

THE CONTEMPORARY PAVILION

N O I L I V ST PA

THE FUTURE PA VILION

A THE P

taking inspiration from previous pavilions as an experimentation for future projects, and for the close collaboration between

Architect

Architect

Architect

Artist

the artist and architect. “generate a complex interaction between art and architecture that produces objects, of which the pavilion might be one, that

Pavilion

Pavilion

seek to be situated within complex and extensive networks.”

We are designing a pavilion for experimentation purposes, and aim to use what we’ve learned to inform our thesis project.

Project

Project

Project

Project

Pavilion

Project

Project

Project


34

10.10

TITLE SUBTITLE Text

References


THE SOUND MIND PAVILION We were able to successfully simulate the correct sound manipulation within our pavilion and therefore succeeding in our experimentation to design a pavilion which can combat mental illnesses through sound therapy.


36

4.2

150

SITE NOISE CATEGORISATION

125

Where is the Site Noise Coming From?

100

In the busy melting pot of noise surrounding our site, a number of sources can be

75

whole, we need to identify which of these sources are permenant issues for the site and understand their acoustic properties to design for the prevention of specific frequencies.

WHO recommended 50 noise level (56 dB)

Road traffic is amongst the larger contributors, as the site sits adjacent

Decibel (dB)

found. To be able to combat noise as a

to Mancunian way and Oxford road. Construction and Airplane noise are also

25

large contributors due to Manchester’s Oxford road development plans and air traffic to Manchester Airport respectively.

10

100

1k

10k

100k

0

Frequency (Hz) Key:

Key:

Range of Environmental Noise

Sample A

Prominent Noise Levels

Sample B

Whole Range of Noise on Site

Sample C

Recommended Noise Levels

45dB

55dB

65dB

75dB

85dB


37

4.3

Proposed New Build

CURRENT SITE PROJECTION The New MMU Science & Engineering Building Proposal

Building RenovationInternal ‘strip Relocation of existing uses within the John Dalton West Building

The new building will provide improved

out’ and sewer diversion works

Demolition of the John Dalton West building

Construction of new Science & Engineering building

Refurbishment of John Dalton Tower

Winter 2020-2021

Spring 2021 Summer 2023

Sring 2022

teaching spaces, study areas and catering facilities for the Faculty of Science and Engineering. Sring 2020 Proposed DemolitionSummer 2020

The proposals involve the demolition of the existing John Dalton West building and the construction of a new Science and Engineering building. The new seven storey building will be located adjacent to the Mancunian Way. Access to the site will continue to be from Chester Street, and the existing loading bay

Projected Construction Timeline Relocation of existing uses within the John Dalton West Building

Internal ‘strip out’ and sewer diversion works

Demolition of the John Dalton West building

To Include Construction of new Science & Engineering building

Refurbishment of John Dalton Tower

New teaching spaces:

Laboratories

200-student ‘super lab’

Computer suites

Sustainable travel will be encouraged by

Flexible seminar rooms

increasing cycle storage and reducing car

Research space

and service area for the John Dalton Tower will be reorganised to increase efficiency.

parking spaces.

Sring 2020

Summer 2020

Winter 2020-2021

Spring 2021 Summer 2023

Sring 2022

Offices

Staff Offices

Postgraduate research students

Study areas Social spaces Cafe Technical support areas https://www2.mmu.ac.uk/media/mmuacuk/content/documents/faculty-of-science-andengineering/MMU-Science-Engineering-public-consultation-banners.pdf

MMU Sustainable Approach Incorporating opportunities for biodiversity, including within the green room and ‘Living Labs’

New tree planting across the development site

The use of recycled materials, where possible, as well as sustainably sourced timber

Providing fast charging points for electric vehicles and secure cycle parking

Incoporating high efficiency heating and cooling as well as efficient LED lighting

Generating a proportion of the building’s energy demands using low and zero carbon technologies


38

10.10 4.4

CLIENT PROFILE

Commercial

In Order to Provide and Deliver a Building for MMU an Analysis of Their Future Projections was Required.

Retail

MMU is currently under a large expansion plan in order to keep up with the ever expanding student numbers enrolling to the university. In order to future proof our proposal we have looked at the future projections of student numbers and in what areas these lie. From this we can determine a best fit programme for the John Dalton West site.

MMU Estates

Education

Residential

Research file:///D:/Users/benja/Downloads/16197-Estates_Strategy-Document-201718_V2.pdf


Building layers of change

The Traditional Campus

39

4.5

THE FUTURE CAMPUS Case Study for Collaborative Workspaces This scenario imagines a fictional 2037 campus as a sleek, intensive facility. It’s prime purpose is to encourage peer-to-

Library

Technology

Practical

Eating

Study

Social

emerge, the campus combines these ideas

Lecture

a series of unintended consequences

Office

from outside the university. However,

Teaching

student exposure to partners and audiences

Green space

peer interaction, multidisciplinary work and

in a design that embodies student ‘crosspollination’. Site barriers impose a prominent barrier to

Site

Services

Skin

Space plan

Structure

Stuff

the desire for permeability.

71%

76% 60% 50%

32%

40%

Innovation

The Future Campus

52%

60%

Job Preformance

Users without choice

Job Satisfaction

Workplace Satisfaction

Users with choice


Primary Secodary Tertiary

4.6

Kitchens, Shopping, Common Spaces, Dining Halls, Computer Rooms, Workshops Corridors, Open Offices, Bathrooms, Toilet Rooms, Reception, Lobbies, Shopping Office, Courtrooms, Private Work Rooms

Size of circle determines size of programme

PROGRAMME

Residential

Living Rooms, Classrooms, Lecture Halls, Conference Rooms Bedrooms, Libraries, Prayer Rooms Theatres, Concert Halls, Recording Studios

Potential adjacencies ) B(A 25-30 d ) ) (A B(A 25-30 d 5 dB 3 0-3

40

Micro Adjacencies

-4

5d

dB(

A)

Commercial

-80

The Future Campus

B(A

and adaptability that allow for high floor-

) 45-55 dB(A) 45-55 dB(A)

to-ceiling space, and large floor slabs.

All To Have Different Acoustic Requirements

Exterior noise from nearby traffic

Education 2

Interior Noise

3

Impact noise

4

Airborne noise

5

Background noise

Corridors, Open Offices, Bathrooms, Toilet Rooms, Reception, Lobbies, Shopping Office, Courtrooms, Private Work Rooms Living Rooms, Classrooms, Lecture Halls, Conference Rooms Bedrooms, Libraries, Prayer Rooms Theatres, Concert Halls, Recording Studios

As suggested in the article by ARUP, the

45

dB

-80

70

increase of digital leraning. 4

dB(

A)

is becoming outdated due to the large (A)

45-55 dB(A) 45-55 dB(A)

In order to combat future scenarios we intend to provide an open plan, adaptive

1 Sources of Environmental noise ranked from most to least harmful to well being

) B(A 25-30 d ) ) (A B(A 25-30 d 5 dB 3 0-3

the Macro and Micro Adjacency diagrams

Meeting Room

Conference

Exterior noise from nearby traffic

3

Seminar

Interior Noise

work

En-Suite

Research Impact noise

Transdiciplinary Workspaces

Dining

Laboratory

Kitchen

75

Education

Background noise

Adaptable Spaces

Private

Commercial Innovation hub Single use space Services Transdisplianry Space Mixed use Space

Communal

functional and adaptive space which will Study

and intake numbers.

Group Study

Library

Quiet Spaces Reception

Exhibition

Student Accomodation

10

100

Communal

25

This however has it’s limits as we must

Meeting Room

Quiet Study

Bicycle Storage

Parking Laundrette

Micro Adjacencies

10

Quiet Spaces

100

Student Accomodation

Lecture Theaters

1k

Collaboratitve workspace

10k

Lecture Theaters

Collaboratitve workspace

Residential

WHO recommended 50 noise level (56Shared dB)

Co-Working

change due to the ever changing curriculum

acoustic seperation.

Kitchen

Bedroom

Airborne Workshop noise

Toilets

5

100

Small Business

environments,

consider spaces that require privacy and

Food & Drink

Cafe/ Servery

Computer Suite

system that encourages collaborative, transdisciplinary

Ground Floor Units

Commercial

4

Mixed Use Space

Quiet Spaces

Office Retail

2

WHO recommende Collaborative noise level (56 dB) Workspaces

125

Lecture Theatres

Teaching

Decibel A [dB(A)]: a filter that adjusts decibels for the frequency range that the human ear is capable of hearing which is 1kHz to 4kHz. Out side this we cannot hear

conventional programme as shown in

0-

Single Use Space Commercial Innovation hub Single use space Services Transdisplianry Space Mixed use Space

150

ensuring maintainability External andTrafficacoustic Kitchens, Shopping, Common Spaces, Dining Halls, Computer Rooms, Workshops comfort” (ARUP, 2018).

Student Accommodation

Services

Macro Adjacencies

Our Adaptation Inspired by The Future Campus

Innovation Hubs

Commercial

Services

Retail

Consider leaving services exposed and including moveable partitions, while also

Sources of Environmental noise ranked from most to least harmful to well being

1

Macro Adjacencies

“Evaluate opportunities to embed flexibility

Research Labs Workshops W.Cs Kitchens Reception

Decibel A [dB(A)]: a filter that adjusts decibels for the frequency range that the human ear is capable of hearing which is 1kHz to 4kHz. Out side this we cannot hear

70

40

External Traffic

100k

0

Our Adaptation Inspired by The Future Campus

1k Lectures Seminars Meeting Spaces Communal Spaces Food & Drink Co-Working

10k

10


THE FUTURE CAMPUS We believe that the future campus will be contained within one building, where students live, work, and rest. This comes as a by-product of the emergence of digital learning, while also focussing on the importance of student contact with tutors.


1.0 2.0 3.0 4.0

PROBLEM IDENTIFICATION

APPROACH

METHOD

CONTEXT

5.0 6.0 7.0

EVALUATION

PROJECT

DESIGN DEVELOPMENT In this chapter we aim to understand the key ideas behind each aspect of our design: typology, adjacency, geometry, panelisation and facade. The input parameters and performance metrics can allow us to accurately model and measure how successful each design element can be.


A COMPUTATIONAL EXPLORATION The following chapter is an exploration of the theories we discussed in chapter 2 - Approach. The goal is not to optimise or automate the design output, but to create multiple designs which can be evaluated.


44

Input Parameters

5.1

A

B

C

D

E

BOTTOM SCALE

CORNER FILLET

MASS LOCATION

MIDDLE SCALE

TOP SCALE

MASS 02

HEIGHT

CENTER OFFSET

DISTANCE BETWEEN

EDGE ANGLE

MASS 03

CORNER FILLET

MASS LOCATION

HEIGHT

TOP SCALE

XY ROTATION

MASS 04

HEIGHT

DISTANCE BETWEEN BLOCK

MASS THICKNESS

MASS 05-1

CORNER FILLET

MIDDLE SCALE

MASS LOCATION

HEIGHT

TOP SCALE

F

MASSING DESIGN SPACE Creating a Number of Parametric Models for the Search of High Performing Masses in Context

MASS 01

We first created a series of parametric models, which can each produce between 100 and 1000 slightly different iterations. These iterations vary in a number of ways, but are focussed on producing slightly

MASS 02

different results when projecting noise data onto their elevations. The aim of this stage is to create enough variation for the following step to be a thorough enough investigation of what

MASS 03

geometry arrangement on this site allow for greater acoustic comfort within the building. The following mass explorations attempt to focus on key typologies: tower block and perimeter block variations.

MASS 04

MASS 05

YZ ROTATION


45

Input Parameters

5.2

A

B

C

D

E

MASS 05-2

TOP SCALE

MIDDLE SCALE

MASS LOCATION

HEIGHT

MASS 06

END ANGLE

HEIGHT

MASS OFFSET

MASS OVERHANG

WING ROTATION

MASS 07

END ANGLE

HEIGHT

MASS OFFSET

ROOF XZ ROTATION

WING ROTATION

MASS 08

TOP XY ROTATION

X BASE SCALE

Y BASE SCALE

HEIGHT

TOP SCALE

MASSING DESIGN SPACE Creating a Number of Parametric Models for the Search of High Performing Masses in Context

MASS 06

We first created a series of parametric models, which can each produce between 100 and 1000 slightly different iterations. These iterations vary in a number of ways, but are focussed on producing slightly

MASS 07

different results when projecting noise data onto their elevations. The aim of this stage is to create enough variation for the following step to be a thorough enough investigation of what

MASS 08

geometry arrangement on this site allow for greater acoustic comfort within the building. The following mass explorations attempt to focus on key typologies: tower block and perimeter block variations.

MASS 09

F


46

5.3

MASSING ITERATIONS Assessing the Performance of Massing Study This is a very brief overvew of the results from the massing performance study, which produced close to 10000 different designs. The following step will show how we sifted

Typology A Linear

through and evaluated each individual design to produce an output.

A1

A2

A3

A4

A5

A6

A7

A8

A9

A10

B2

B3

B4

B5

B6

B7

B8

B9

B10

C2

C3

C4

C5

C6

C7

C8

C9

C10

D2

D3

D4

D5

D6

D7

D8

D9

D10

Typology B Perimeter

B1 Typology C Atrium

C1 Typology D Tower

D1

dB(A) 40

45

50

55

60

65

70

75

80


47

5.4

BUILDING MASS SELECTION Assessing the Performance of Individual Parametric Models

Corner Height 1

Corner Height 2

Corner Height 3

Corner Height 4

Centre Scale

Centre Angle

Bottom Scale

Building Volume

Surface Area

Decibel Levels at Elevation

MASS 01 Corner Height 1

Corner Height 2

Corner Height 3

Corner Height 4

Centre Scale

Centre Angle

Canyon 1

Canyon 2

Building Volume

Surface Area

Decibel Levels at Elevation

The key goal from this study was to find building geometries which received less noise on their elevation, which would

MASS 02

correlate to less noise transferred through the elevation and greater acoustic comfort within the building.

Footprint Generation

No Floors

Roof Offset

Roof XY Rotation

Roof XZ Rotation

Building Volume Typology A Linear

Fillet

Surface Area

Decibel Levels at Elevation

However, the standalone testing of acoustic quality does not allow for a concise enough

A1

exploration of the design space. In order to

A2

A3

of placing programmatic arrangements, we must also have a building which has

Building Depth

Opening Size

Height 1

Height 2

Height 3

Height 4

Building Volume

a low surface area to volume ratio (less

B1

complex geometry). This makes it easier

A7

A8

A9

A10

Surface Area

B6

B7

B8

B9

B10

Decibel Levels at Elevation

B2

B3

C2

C3

B5

B4

Typology C Atrium

for the placement and post rationalisation of adjacencies.

C1

The five masses to the right show the outputs which have the least noise

A6

MASS 03

Typology B Perimeter

carry a design through to the next stage

A5

A4

Block Scale

Distance Between Blocks

Configuration

Block 1 Height

Block 2 Height

Block 3 Height

Block 4 Height

Top Width

Building Volume 1

Typology D Building Volume 3 Tower

Building Volume 2

Building Volume 4

Surface Area

MASS 04 C4

C5

C6

C7

C8

C9

C10

D4

D5

D6

D7

D8

D9

D10

Decibel Levels at Elevation

reaching their elevation whilst maintaining the lowest surface area to volume ratio of D1

their respective parametric models.

D2

D3

MASS 05

dB(A) 40

45

50

55

60

65

70

75

80


48

5.5

BUILDING MASS SELECTION Assessing the Performance of Individual Parametric Models

Click to View Video

Block 1 Height

Configuration

Block 3 Height

Click to Explore the Design Iterations

Block 4 Height

Configuration

Middle Width

Top Width

Building Volume 1

Building Volume 2

Building Volume 3

Building Volume 4

Surface Area

Decibel Levels at Elevation

The key goal from this study was to find building geometries which received less noise on their elevation, which would

MASS 06

correlate to less noise transferred through the elevation and greater acoustic comfort within the building. Corner Angles

Location Point

Building Depth

No Floors

Typology Surface AreaA Linear

Building Volume

Decibel Levels at Elevation

However, the standalone testing of acoustic quality does not allow for a concise enough

A1

exploration of the design space. In order to

A2

A3

of placing programmatic arrangements, we must also have a building which has

Corner Angles

Building Depth

No Floors

Rotate Floor Plate

Building Volume

Surface Area

a low surface area to volume ratio (less

B1

complex geometry). This makes it easier

A7

A8

A9

A10

B6

B7

B8

B9

B10

Decibel Levels at Elevation

B2

B3

C2

C3

B5

B4

Typology C Atrium

for the placement and post rationalisation of adjacencies.

C1

The five masses to the right show the outputs which have the least noise

A6

MASS 07

Typology B Perimeter

carry a design through to the next stage

A5

A4

Base X Dim

Base Y Dim

Top Scale Factor

Rotation

No Floors

Building Location

Typology D Building Volume 4 Tower

Surface Area

MASS 08 C4

C5

C6

C7

C8

C9

C10

D4

D5

D6

D7

D8

D9

D10

Decibel Levels at Elevation

reaching their elevation whilst maintaining the lowest surface area to volume ratio of D1

their respective parametric models.

D2

D3

MASS 09

dB(A) 40

45

50

55

60

65

70

75

80


High Performing Iterations

- Low Total Elevation Decibel Level - Low Surface Area to Volume Ratio (Higher Chance for Successful Programme Connectivity)


50

5.7

ADJACENCY SYNTAX Assessing the Performance of Adjacency Study Similar to the massing study, this is a brief overview of the results from the adjacency study, which explored different weighting categories and different prioritisation for programmes. 5 of each parametric model was carried through, in an attempt to narrow down the 45 best performing designs into a select few. The following step will show how we sifted through and evaluated each individual design to produce an output.


1

51

1

2

3

4

5

6a

6b

7

8

X

Y

5.8

ADJACENCY SYNTAX Assessing the Performance of Individual Adjacency Placements The main goal of this step is to find a programme arrangement which has a greater efficiency of room placement. Each programme has a rating which is

TEST PHASE 1

determined by their placement compared to the optimal placement, and the overall efficiency can be determined by combining each programme efficiency. The focus is

1

2

3

4

5

6a

6b

7

8

X

Y

also on controlling the programme density - by having a health competition of space where there is not too much comprimisation but also where the building isn’t empty. Each process is a slightly different exploration of weighting and prioritisation order. The “best” design was selected because it’s overall efficiency was high as well as the programme density being at a suiable level. 1 - Lecture Efficiency 2 - Collaborative Efficiency 3 - Quiet Study Efficiency 4 - Laboratory Efficiency 5 - Accommodation Efficiency 6a - Office (Open) Efficiency 6b - Office (Closed) Efficiency 7 - Retail Efficiency 8 - Plant Efficiency X - Overall Placement Efficiency Y - Programme/Building Density

TEST PHASE 2


1

52

1

2

3

4

5

6a

7

8

X

Y

5.9

ADJACENCY SYNTAX Assessing the Performance of Individual Adjacency Placements The main goal of this step is to find a programme arrangement which has a greater efficiency of room placement. Each programme has a rating which is

TEST PHASE 3

determined by their placement compared to the optimal placement, and the overall efficiency can be determined by combining each programme efficiency. The focus is also on controlling the programme density - by having a health competition of space where there is not too much comprimisation but also where the building isn’t empty. Each process is a slightly different exploration of weighting and prioritisation order. The “best” design was selected because it’s overall efficiency was high as well as the programme density being at a suiable level. 1 - Lecture Efficiency 2 - Collaborative Efficiency 3 - Quiet Study Efficiency 4 - Laboratory Efficiency 5 - Accommodation Efficiency 6a - Office (Open) Efficiency 6b - Office (Closed) Efficiency 7 - Retail Efficiency 8 - Plant Efficiency X - Overall Placement Efficiency Y - Programme/Building Density

Click to View Video

Click to Explore the Design Iterations


Accommodation

Quiet

Lecture

Collaborative

Retail

Office

Laboratory

Plant

1. PROGRAMME SET UP Physical representation based off spatial requirements.

2. POST RATIONALISED PROGRAMME Physical representation after programme fitted to existing geometry.


Laboratories

Laboratories

Plant

Plant

Collaboration

Collaboration

Accommodation

Accommodation

Mass & Void Trimming Surfaces Office

Office Quiet

Quiet

2. POST RATIONALISATION - Programme arrangement rationalised for integration with mass and void geometries.

Lecture

Lecture Retail

Retail

1. PROGRAMME PLACEMENT - Self-organised by spatial requirements for noise, daylight, privacy, circulation, ventilation, views.

3. OUTPUT - Programme configured for clustering where possible for improved connectivity.


55

5.11

INTERNAL PANELISATION Testing the Static Ceiling Design Space for Better Performing Solutions Using the same method we explored in studio 1, we are able to assess a number of panel systems in how they reverberate sound within a defined space. For the use of non-flexible spaces, such as lecture theatres, and offices, which keep the same acoustic qualities throughout the day; the reverberation should be kept to a minimum, for greater acoustic comfort.


56

5.12

INTERNAL PANELISATION Testing the Kinetic Ceiling Design Space for Better Performing Solutions Building upon methods we explored in studio 1, we are able to assess a number of kinetic systems in how they can absorb and reflect sound within a defined space. For the use of flexible spaces, such as collaborative spaces, retail and offices, where the acoustic qualities throughout the day vary; the better performing outputs can be determined by a higher absorption rate. The test uses a raytracing method which depletes in strength each time it bounces. After the 5th reflection, the trace disappears and can be considered absorbed. The lower the score on each evaluation surface determines a more successful kinetic ceiling.


SPATIAL REQUIREMENTS Flexible Programme (Kinetic Ceiling) - Quiet Space, Collaboration, Office, Retail Non-Flexible Programme (Static Ceiling) - Lecture Theatres, Laboratories

Flexible Programme

Flexible Acoustic Response

Non-Flexible Programme

Non-Flexible Acoustic Response

INTERNAL ARCHITECTURAL RESPONSE

INTEGRATED ACOUSTIC INTERNAL ENVIRONMENT


58

5.14

FACADE Testing for High Performing Facade Types The following shows an exploration of different facade typologies. These facade types vary in structure and function, but all attain a kinetic function, in order to react to the ever changing environment. The test is conducted by placing a sound source in front of the facade (indicated by the red dot), a facade type to be tested, and an evaluation surface on the other side of the facade which counts the number of rays which are able to pass through the facade. This will give an accurate indication of how much environmental noise is able to pass through a reflective facade on site. The results of the experiment give an indication of which facade systems perform better acoustically, and can inform our decision in the design process.


West

South East

North

Glazing Holes Glazing Facade/Void Transition

FACADE SOUTH ELEVATION

Kinetic Panel A Requirement for less adaptable range

Kinetic Panel A

Kinetic Panel B Requirement for some adaptable range

Kinetic Panel B

Kinetic Panel C Requirement for greater adaptable range

Kinetic Panel C

Void

VOID/FACADE CONNECTIVITY

FACADE UNROLLED

GLAZED PANELISATION


COMPLETION OF DESIGN TESTING PHASE Each step of the design process has been carried out. The remaining step of the process is to evaluate the building in it’s entirety, to fundamentally understand if it is a success,


1.0 2.0 3.0 4.0 5.0

PROBLEM IDENTIFICATION

APPROACH

MEHOD

CONTEXT

DESIGN DEVELOPMENT

6.0 7.0

PROJECT

EVALUATION


HOW EFFECTIVE IS THE PROPOSAL? By assessing the building as a whole, rather than assessing individual phases of the design process, we can identify where our method is and isn’t successful.


63

6.1

INTERNAL NOISE EVALUATION How is the Spread of Noise Reduced Internally?

Internal Sound Source

Direct Noise

The strategy of using static ceiling panels allows for the avoidance of noise spreading upwards throughout the building, while the kinetic ceiling panel aims to tackle the spread in all directions, by absorbing sound. Materials used would be chosen for the purpose of reducing the spread of noise. Internal walls and floors would be fitted with sufficient acoustic insulation, so if enough noise was able to be transmitted to these surfaces, then the noise would be diminished.

Deflected Noise Noise deflection Zone

Reduced Decibel transfer Through floors


64

6.2

EXTERNAL NOISE EVALUATION How is External Noise Combatted? By assessing internal spatial requirements for noise levels, the facade can be applied to the elevation which corresponds to areas which require greater noise cancellation. The top image shows how the facade treatment will vary around the entire Programme Rquirments

building and the bottom indicates how that variety is designed to respond to the internal requirements.

23dB

Deflected Noise 30dB

15dB

External sound Source

75dB

23dB

Reduced Decibel Transfer through walls


65

6.3

VENTILATION EVALUATION How can we Implement Natural Ventilation Methods Throughout the Building? Similar to the placement of programme for reduces noise prioritisation, adjacencies took natural ventilation strategies into account when being placed. For example, accommodation and office spaces were placed in regions where access to natural ventilation was less restrictive, whereas the plant room was organised in a space where natural ventilation is more difficult to access. Cool Natural Breeze

The section to the right indicates our overall ventilation strategy, consisting of a crossstack ventilation method in order to draw cool, fresh air in and warm, stagnant air out of the roof light fittings.

Central void allows for stack and cross ventilation combination Small vents allow fresh air into rooms Small vents allow Stale air to be exhausted using cross ventilation


Blue denotes areas with shading control

66

6.4

Red denotes areas with no need for shading control

DAYLIGHT EVALUATION How is Daylight Brought into a Deep Plan Building? By connecting the facade surface to the internal void, we were able to punch holes throughout the building enabling daylight to enter the centre. The void reaches the roof line which allows daylight to spill down throughout the void space. Upon reflection, an improvement on this design would be to panelise the void space with a combination of glass fibre reinforced concrete and glass, rather than just glass fibre reinforced concrete, as shown in the images. This would allow for sufficient daylight from the void space to enter the rooms adjacent to the centre of the building.

Openings in the facade and roof bring daylight into the central void spaces


67

6.5

Higher opening threshold

What are our Strategies for Privacy? Again, privacy holds a specific weighting the self-organising programme arranagement algorithm, and specific rooms require greater levels of privacy than others. The privacy weighting essentially deters spaces from being close to the ground floor and aims to bring rooms which require more privacy in to the centre of the building - for accommodation this is usually counterbalanced for the need for daylight. Rooms which require greater amounts of privacy are generally placed higher up in the building, with lecture halls and retail spaces taking up ground floor space. For added privacy, facade panels are also self-organised over areas which require more privacy, but allow views through it’s constantly opening and closing mechanism.

Privacy level

PRIVACY EVALUATION

Lower opening threshold


68

6.6

CIRCULATION EVALUATION How has the Building been Post Rationalised to Encourage Improved Circulation? The building is connected vertically by three cores, which are an appropriate proximity Horizontal circulation is not bound by walls allowing for a fluid transition from room to room

from one another for fire regulations. Horizontal circulation is dictated by few internal walls, only those which separate programmes.

Where

programmatic

functions vary on the same floor, separate access points are made to the same cores, to avoid a clash in circulation, eg. residential accommodation and offices sharing circulation space.

Cores create verticle circultion

GF void allows for transitions from space to space and from inside to outside fluidly


2.0 3.0 4.0 5.0 6.0

APPROACH

METHOD

CONTEXT

DESIGN DEVELOPMENT

EVALUATION

7.0

PROJECT


L S

70

7.1

Chester Street

ROOF PLAN

Oxford Road


7.2 Retail

GROUND FLOOR PLAN

Retail

Retail

Lift Lecture Office

Lift

Lecture Plant /Services

Entrance Lift

WC

WC

Entrance

v

71

N


7.3 Research

4th FLOOR PLAN

Accommodation

Accommodation

Quiet

Lecture

Collaborative

v

72

N


73

7.4

7th FLOOR PLAN Collaborative

Quiet

Lecture

v

N


74

7.5

SECTIONAL PLANS 1st Floor Plan

2nd Floor Plan

3rd Floor Plan

4th Floor Plan

5th Floor Plan

6th Floor Plan

7th Floor Plan

8th Floor Plan

9th Floor Plan

10th Floor Plan

11th Floor Plan

12th Floor Plan

Click to View Video

Ground Floor Plan


75

7.6

LONG SECTION


7.7

SHORT SECTION

Click to View Video

v

76


7.8

v

77

N

Circle Square Circle Square Development Development

Oxford Road Oxford Road

Proposed Building SiteProposed Building Site

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

NORTH ELEVATION

john Dalton Tower John Dalton Tower


7.9

v

78

N

John Dalton Tower

John Dalton Tower

Proposed Building Site

Proposed Building Site

Sound Source

Sound Source

Sound Source

Sound Source

SOUTH ELEVATION

Oxford Road

Oxford Road

Circle Square Circle Square


7.10

v

79

N

Chester Street Buildings Chester Street Buildings

Proposed Building Site

Mancunian Way Mancunian Way

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

WEST ELEVATION


7.11

v

80

N

Mancunian ChesterWay Street Buildings

Proposed Building Site Building Site Proposed

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

Sound Source

EAST ELEVATION

Chester Street Buildings Mancunian Way


81

7.12

ISOMETRIC VIEW


CONSTRUCTION METHOD


83

7.13

EXPLODED ISOMETRIC


84

7.14 Point load

LOAD PATHS DIAGRAMS

Primary load transfer

Secondary load transfer Primary structure Load transfer through secondary structure

Secondary structure Non-Load bearing structure

Long Section Showing Structural System

UDL (Uniformally distibuted load)

Long Section Showing Load Paths


85

7.15

CONSTRUCTION SEQUENCE The 10-Phase Process of Construction

1

2

Create site entrances and establish site compound

Install Herras fencing

6

Connect beams to cores and primaray structural columns

3

Excavate and install pile and raft foundations

7

Install floor slabs, ceiling connections and void connections for GFRC panels

8

Install GFRC panels

5

4

Install load bearing cores

Lift primary structural columns into place

9

Install Glazing and roof slab to create a water tight box

10

Internal and external finishes install adaptive facade and interior walls


86

7.16

DETAIL OVERVIEW


87

7.17

FACADE TO ROOF CONNECTION

1

2 1. Parapet capping 2. Glazing mullian 3. Aluminium C channel

19

3 4

4. Aluminium C column 5. 12.5mm Glazing panels 6. Aluminium column connection

5 6

7. 180mm hollow steel column

18

8. Aluminium support frame

17

9. Fixing bolts 10. Adaptive facade

16

11. Servies boxing

15

12. Services pipes

14

13. Rigid Acoustic insulation 14. 150mm concrete slab 15. 12.5mm MDF board 16. 50x50mm aluminium rails

13

17. Steel I beam 18. Roof deck

7

12 11

8 9

10


88

7.18

1

FACADE BUILD UP 2

9

3

10

1. Concrete slab 2. Steel I beam

4

3. 50x50mm Aluminium rail 11

4. Column connections 5. 12mm Double glazing 6. Aluminium support frame

5

7. Adaptive facade

12

8. Fixing bolt 9. Services boxing

6

10. Services

13

11. Rigid Acoustic insulation 12. 12mm GFRC ceiling panel 13. 180mm hollow steel column 14. 12mm GFRC ceiling panel 7

8 14


89

7.19

8

8

9

9

10

10

11

11

12

12

13

13

14

14

15

15

16. 75mm Sand binding

16

16

17. 150mm Hardcore

17

17

19. Steel column base

18

18

20. Concrete pad

19

19

20

20

21

21

FACADE TO FLOOR CONNECTION 1

1

2. 180mm hollow steel column

2

2

3. 50mm Aluminium mullian

3

3

1. Column connection

4. 12mm double glazing 5. Fixing bolt

4

4

5

5

6

6

7

7

6. Aluminium support frame 7. Adaptive facade 8. Concrete slab 9. Steel I beam 10. Services boxing 11. Services 12. 12mm GFRC ceiling Panel 13. Rigid Acoustic insualtion 14. Concrete slab 15. 10mm DPC

18 Steel fixing plate

21. Pile foundation


90

7.20

1

FACADE DETAIL 2 3 1. 12mm Glazing panel 2. Aluminium mullian

4

3. Fixing bolt 4. Aluminium Support frame 5. Rotation rod

5

6. Rotating hinge 7. Adaptive facade panel

6

7


91

7.21

VOID TO ROOF CONNECTION

1

2

1. 12mm glazing panel

3

2. Aluminium mullian 3. Concrete floor slab 4. Steel I beam 5. 25mm GFRC panel 6. Aluminium support frame 7. Acoustic insulation gap

4

5

6 7


7.22

8

VOID DETAIL

9

92

10

1. Concrete floor slab 2. 12.5 MDF board 3. Steel I beam 4. Services boxing

11 1

1

13

5. Services

2

2

8. Steel I column

3

3

9. Column joining connection

4

4

11. 50x50 Aluminium fixing rail

5

5

12. Acoustic insulation panel

6

6

7

7

6. 50x50mm Aluminium rail 7. 12mm GFRC ceiling panel

12

14

10. Fixing bolt

13. Aluminium Support frame 14. 25mm GFRC Wall panel 15. Aluminium mullian 16. 12mm Glazing panel

15 16


93

7.23

10

11

VOID TO GROUND CONNECTION

12 13

1. Concrete floor Slab 2. 10mm DPC

14

3. 75mm Sand binding 4. 150mm Hardcore 5. Fixing bolt 6. Steel fixing pad 7. Steel column connector 8. Concrete Pad

1

1

2

2

13. GFRC support frame

3

3

14. 25mm GFRC panel

4

4

9. Pile foundation 10. Directional Steel column 11. Steel column connector 12. Insulation panel

15

15. Aluminium Door frame

5

5

6

6

7

7

8

8

9

9






CONCLUSION With the development of our project from Studio 2, our computational skill set has continued to grow on a steep learning curve. This has been absolutely essential in order to produce the outcome we have been able to produce, with the amount of iterations and evaluative studies we have been able to undertake. Similarly to previous semesters, we are not sound engineers nor do we have the correct tools to create optimal acoustic environments, so the project was always going to have limitations with that respect. However, our improved knowledge of certain softwares has allowed us to develop acoustic manipulation methods more effectively than we were able to in our last project. Our main focus this semester was to learn as much as possible to prepare us for work in industry. We’ve each tried to spend more time on the things we’re least comfortable with which may have slowed our progress slightly but we’re all in a more confident position to move into practice.


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