Structural Design for Adaptability and Growth

CIV4009 Final Report Department of Civil and Structural Engineering, University of Sheffield, 2018

Structural Design for Adaptability and Growth Joshua F Adjodha

Candidate: MEng. Structural Engineering and Architecture (HK21) Supervisor: Dr Mihail Petkovski

Submitted: 18/05/2018

Declaration statement: Joshua F Adjodha certifies that all material contained within this document is his own work except where it is clearly referenced to others.

Signed: ………………………………

Date: …………………………………

Acknowledgements: This dissertation has been carried out under the supervision of Dr Mihail Petkovski, whose support has made the writing of this paper possible.

I greatly appreciate the time that he has taken to help to discuss and develop the concepts within this document. The research question could not have been as greatly addressed without the help and openness of Diana Chen, who kindly gave me access to her research on ‘The Adaptable Growth of Seashells’.

I would finally like to thank my friends and family for their support and also the staff of both the Department of Civil and Structural Engineering and the Department of Architecture.

i

Abstract The built environment appears to have followed the trend in the current consumerist economy. The culture of fast food, fast fashion and fast tech has now spread to the construction industry.

Prefabricated construction and functionally precise design has created (intentionally or unintentionally) the obsolescence of buildings. This gives an expiry date to buildings less than what we would expect of a structure’s design life, thus increasing the economic, environmental and social impact of a building’s lifecycle.

Adaptable design is to provision for changes in the composition or function of a structure, thus reducing the likelihood that a building becomes obsolete. Beyond adaptability some authors have theorized towards a concept of designing for growth. This may take lessons from structures in nature (trees, shells, coral reefs, etc.) called biomimetic design.

The study evaluates the relative sustainability of optimum and growth structural models, over a whole-life-cycle, during varied rates of dwelling density. The results of this study suggests that structures designed for adaptable growth can prove more economically, environmentally and socially sustainable than optimally designed structures at the end of design life, when special demands rise.

ii

Table of Contents 1.0

INTRODUCTION 1.1 Background and Motivation 1.2 Overview of Chapters

1

AIMS AND OBJECTIVES 2.1 Aim 2.2 Objective 2.3 Hypothesis 2.4 General Mythology

2

3.0

LITURATURE REVIEW 3.1 State of the Built Environment 3.2 Current Design Principles 3.3 Structural Obsolescence 3.4 Structural Adaptability 3.5 Structural Biomimicry 3.6 Structural Growth Concept

4

4.0

STRUCTURAL DESIGN FOR GROWTH 4.1 Methodology 4.2 Development of Structural Models 4.3 Design and Appraisal of Model Scenarios

22

5.0

RESULTS 5.1 Findings and scope of study 5.2 Discussion 5.3 Implications

33

2.0

iii

6.0

CONCLUSIONS

42

7.0

RECOMMENDATIONS FOR FUTURE RESEARCH

43

8.0

BIBLIOGRAPHY

44

9.0

APPENDIX 9.1 Structural Calculations

46

List of Tables Table 4.01 Showing Slab Design for Each Module Unit Table 4.02 Showing Beam Design for Each Module Unit Table 4.03 Showing Column Design for Each Module Unit Table 4.04 Showing Raft Foundation Design for Each Module Unit Table 4.05 Showing Shear Wall Design for Each Module Unit Table 4.06 Showing Total Design Volume for each Module Unit Table 4.07 Showing Market and Production Data for Structural Materials Table 4.08 Showing Salary Data for Construction Labour Table 5.01 Evaluation of Model Embodied Energy and Carbon Error Table 5.02 Comparing Models When Density Rises by a Factor of 4 Table 5.03 Comparing Models When Density Rises by a Factor of 3 Table 5.04 Comparing Models When Density Rises by a Factor of 2

iv

List of Figures

Figure 4.05 Growth Model Composition

Figure 3.01- Basic Requirements (BSI, 2010)

Figure 4.06- Conversion Model Composition

Figure 3.02- Indicative Design Working Life (BSI, 2010)

Figure 4.07- Conversion of Columns in Modules

Figure 3.03- Durability (BSI, 2010)

Figure 4.08- Conversion of Shear Wall in Modules

Figure 3.04- Building Layers (Brand, 1997)

Figure 4.09- Conversion of Foundation in Base Modules

Figure 3.05- Types of Adaptability (Schmidt et al. 2010)

Figure 4.10- Plans and Sections of Structural Models

Figure 3.06- Origin and Destination Uses (Kincaid, 2000)

Figure 4.11- Sections of Growth Model Scenarios

Figure 3.07- Effectiveness of Design-Based Adaptability Enablers (Ross et al. 2016)

Figure 5.01- Graphs Showing Model Response to Scenario 4 Figure 5.02- Graphs Showing Model Response to Scenario 3

Figure 3.08- Photograph of Parkhill during Renovation (Levitt, 2010)

Figure 5.03- Graphs Showing Model Response to Scenario 2

Figure 3.09- Structural Engineering Biomimicry (Chen, 2016)

Figure 5.04- Graphs Showing Overall Cost per Dwelling

Figure 3.10- Governing Equations of Systems (Chen, 2016)

Figure 5.05- Graphs Showing Overall Cost per m2

Figure 3.11- Mathematic Modelling of Mollusk Shell (Chen, 2016) Figure 3.12- Structural Growth of Coral (Chamberlain, 1978) Figure 3.13- Palmata Coral Cross-Sections (Chamberlain, 1978) Figure 3.14- Strategies of Growth (Scideri’s, 2015) Figure 3.15- Strategies of Metamorphism (Scideri’s, 2015) Figure 4.01- Methodology Flow Chart Figure 4.02- Structural Model Figure 4.03- Addition of Modules in Response to Dwelling Density Figure 4.04 New Build Model Composition

v

1 INTRODUCTION 1.2 OVERVIEW OF LITERATURE CHAPTERS The literature review explores the broad range of subjects concerning the field of structural design in the built environment.

These topics form the bases of the authors rational for research.

1.1 BACKGROUND AND MOTIVATION Working on the boundary of structural engineering and architecture, this project aims to address the fundamental problems concerning the built environment. The motivation behind this research concerns the development of more sustainable infrastructure through the application of adaptable and biomimetic design.

Chapter 3.1 investigates the key sustainability concerns in the built environment and the relevant solutions. The key sustainability criteria and how to measure the sustainability of buildings over their design life.

Building obsolescence can cause major resource waste and negatively affect the surrounding communities. It occurs when the structural system does not provide for changes in spatial requirements and cannot adapt to technological changes. The current structural engineering industry favours optimum design due to the apparent initial benefits. The literature suggests that optimum designed structures are more likely to become obsolete over their design life causing social, economic and environmental problems.

The relative sustainability of optimum structures and adaptive structures is scarcely evaluated as special requirements change.

Chapter 3.2 interoperates the philosophies behind the structural engineering design of buildings. The extent of how the design life of a structure is interoperated by various design standards and industry is of specific concern.

Chapter 3.3 introduces building obsolescence and identifies the key sustainability concerns. The causes and preventative measures are further discussed.

Chapter 3.4 discusses structural adaptability as a solution to building obsolescence. The effectiveness of specific strategies are identified.

This project aims to evaluate the relative sustainability of structural models using adaptable growth and the optimum design model over a building’s lifetime as special requirements change.

Chapter 3.5 proposes how designing for structural growth can further mitigate against building obsolescence. Biomimetic design procedure is investigated for the potential to develop new construction technologies.

1

2 AIMS AND OBJECTIVES

2.4 GENERAL METHODOLOGY

2.1 AIM

Qualitative analysis of the relevant literature and case studies to identify the key criteria relevant to structural engineering in: The Built Environment; Current Structural Design Principles; Structural Obsolescence; Structural Adaptability; Structural Biomimicry; Structural Growth.

To investigate relationships between obsolescence, adaptability, biomimicry and structural design. A thorough investigation through a qualitative method of collection and analysis should help identify the key social, economic and environmental factors associated with the aim of the study (Denzin N K, Lincoln Y S, 2000). This uses various literature and data resources to develop a critical understanding of the design criteria associated with the brief and the key factors the study aims to evaluate.

A fully qualitative method however can be biased by the personal and subjective aspects of the data. There is a need to gain a full understanding of existing phenomena in their real context (Yin R K, 2014). To do this the case study method will be used to gain a broader and more comprehensive understanding of key factors in the context of the built environment (Yin R K, 2012).

This will fulfil objective (a) to form the basis for objective (b).

Stage 1: Literature Review.

To develop structural concepts using biomimicry and adaptability design principles and compare their economic, environmental and social outcomes to current structural engineering sustainability requirements.

2.2 OBJECTIVES a) To obtain an understanding of how adaptability and biomimicry design principles can increase building design life through qualitative analysis of literature. b) To create structural concepts informed by adaptable and biomimicry design principles. c) To evaluate the total Economic, Environmental and Social impact of the structural concepts and compare to current structural design data.

2.3 HYPOTHESIS If the structural design of housing is designed to accommodate growth as opposed to the optimum requirements, when housing density demands change, there will be major benefits to the economic, social and environmental sustainability of the building over its design life.

Stage 2: Design Method.

Following outcomes identified through the qualitative method, the design method will incorporate the researcher’s experience in architectural and engineering design to develop structural design concepts to test how adaptability and biomimicry design can reduce building obsolescence and a higher sustainability performance.

Adaptability principles identified by authors such as (Schneider T, Till J, 2007) and (Brand S, 1997), have been theorised to reduce 2



building obsolescence via spatial design guidelines. These principles will be incorporated into the objective structural concept.

Investigations of authors such as (Pawlin M, 2011) and (Chen D A, 2016), have identified the biomimicry approach to help inform the built environment. These studies have involved the investigation and modelling of key features natural structures have evolved to avoid extinction. The author will utilize such findings to better inform the design process.



II. To fulfil objective (b) the design method will: 

Stage 3: Analysis



Following the outcomes identified through the Design Method, the quantitative method will draw conclusions on the relative performance of each the structural concept through mathematical, graphical and comparative methods. These methods are based on current market data and do not consider how markets may vary over time. Building obsolescence determined quantifiably when the performance (P=Sj.Dj.t)) of a building drops below the minimum performance (Pf) (Lemer, 1996). To evaluate the total Economic, Environmental and Social impact of the structural concepts and compare to current structural design data the qualitative method will assess solutions performance in factors like: cost, CO2 footprint, social impact, functional diversity, embodied energy, etc.









I. To fulfil objective (a) the qualitative method will:



Define a relevant situation and design brief of a structural frame; Design a structural system to reduce building obsolescence through adaptability and biomimicry principles; Design a structural system based on the minimum structural requirements given by Eurocode standards; Gather the relevant variables of each design to determine their social economic and environmental impact over the defined time period

III. To fulfil objective (c) the quantitative method will:

2.5 METHODS 

Identify the key design principles and theories which are required to reduce building obsolescence; Identify a relevant situation to carryout Method II.



Identify the key social, economic and environmental parameters, which determine the sustainability of a structure.

Consult relevant literature and case studies regarding: Building Obsolescence; Adaptability Design; and Biomimicry Design; 3

Process the resulting design variables to measure how effective each design addresses the social economic and environmental parameters over the defined time period; Compare the outcomes based on the identified social economic and environmental parameters over the defined time period; Draw conclusions based on the discovered findings and which presumptions were proven or disproven; Propose the implications of the study on the current practices of structural engineering design.

3.1 THE STATE OF THE BUILT ENVIRONMENT

3 LITERATURE REVIEW

The built environment continues to expand and consume valuable natural resources to serve the needs of civilisation. The construction and use of buildings is one of the major contributors of mankind’s disruption to global climate and biodiversity. This brings forth an urgency to reduce the carbon emissions throughout the lifecycle of our infrastructure to reduce the permanent damage to planetary processes.

This literature review follows the development of the author’s hypothesis through exploring the relevant literature in: 3.1 The State of the Built Environment; 3.2 Current Structural Engineering Principles; 3.3 Structural Obsolescence; 3.4 Structural Adaptability; 3.5 Structural Biomimicry. Chapter 3.6 aims to synthesis the principles discussed and provide the background data for the author’s structural growth model design and analysis.

Yeang (1991) identifies that high-riseation has developed in city centres worldwide due to increasing land values and economical special demands. New technologies and cheap energy resources have led to the development of high energy buildings and controlled environments, which ignore environmental design, leading to increasing homogeneity in urban environments with flat material surfaces. This causes heat island effects, low biodiversity and flood risks, in the built environment.

Yeang (1991) concludes that designers must return to more ‘ecologically responsive approach’, which means design with the climate and natural environment. This is due to climate being one of the most immutable factors in our landscape. When socio-economic and political aspects of a place can change significantly over say a period of 100 years, as do also style and taste, the location’s climate remains more or less the same (apart from seasonal and long-term climate change). Yeang (1991) proposes that it must be considered at the scales of: the building or city block; the city’s infrastructural and other systems; and at the city’s planning and land use level. This infers the relevance of structural design to respond to climate through more passive methods to reduce energy use. This has led to Yeang’s (1991) proposition of ‘The Green Skyscraper’.

4

Yeang (1999) argues that a decentralised suburban housing configuration is anti-ecological and disrupts the natural ecosystems over a wide land area. This comments on how a suburban sprawl causes damage to global biodiversity and induces long working commutes into cities which increases the carbon emissions from transportation. He gives the solution that cities should be more concentrated with highly efficient building systems and suggests the green skyscraper which incorporates ecosystems into buildings to promote biodiversity, health and food production. Yeang (1999) suggests strategies of vertical planting in high-rise buildings to increase biodiversity, and reduce flood risks and heat island effects.

Kincaid (2000) concludes that designers need to:   

Consider the environmental sustainability criteria of energy transformation, material extraction and eco-system impact.

Consider the social sustainability criteria of supporting the wellbeing and prosperity of our communities.

Consider the economical sustainability criteria of the demand equation in both qualitative and quantitative ways.

In terms of structural design this means that a degree of redundancy, with the use of ambiguity and flexible design principles, promoted by a more appropriate regulatory system can lead to more adaptable and sustainable performance of infrastructure.

Habraken (1972) investigates how we pile up dwellings without sacrificing their independence. He proposed a support and infill concept where the infills structure is independent of ownership, form and function from the support structure, which enables a multilevel urban environment. In this support structures need to fulfil the requirements of a variety of functions and meet the changing social, economic and environmental demands.

Tingley & Davison (2011) investigate a whole life approach to considering the sustainability of buildings. This involves minimising the embodied carbon and energy of structures. They quote Sturgis & Roberts (2010) to define: 

Kincaid (2000) identifies that only 1-2 per cent of building stock in the UK is made of new construction in a typical year. Kincaid (2000) looks at how existing buildings may be adapted to meet new requirements and how new buildings can be designed for sustainable adaptability.



Kincaid (2000) argues that the physical impact of the built environment is the level at which energy transformation, material extraction and eco-system impact occurs. He states that many structures have survived for hundreds and even thousands of years and argues that sustainability is a matter of planning and designing for the long term. This depends on whether a structure can be adapted for a whole range of uses.

Embodied Carbon- carbon dioxide emissions that are generated from the formation of buildings, their refurbishment and subsequent maintenance.

Embodied Energy- energy input processes involved in the formation of buildings, their refurbishment and subsequent maintenance.

Tingley & Davison (2011) look into processes of reducing the embodied energy and carbon over a buildings whole-lifecycle through designing for material reuse and deconstruction. The sector is still working on benchmarks for embodied energy and carbon assessment.

5

De Wolf, (2017) evaluates the literate and design codes embodied energy and carbon standards of buildings. She considers the various methods of embodied energy calculations and argues that there should a comprehensive overview of embodied energy and carbon with reliable dataset in the building standards. She compiles benchmarks of embodied energy and carbon from various literature sources based on construction materials. For the base structure these include:  

3.2 CURRENT STRUCTURAL ENGINEERING DESIGN PRINCIPLES The current Structural Engineering design philosophy prioritises efficiency of design in terms of the materials used in the design of a building brief. This rational insist that the most efficient structural system has the least consumption of materials and cost. BSI (2010) highlights the basic requirements for the structural design of buildings.

1-2 GJ/m2 for Embodied Energy 100-200 kg/m2 Embodied Carbon

Figure 3.01- Basic Requirements (BSI, 2010)

It is indicated that a structure must remain fit for use for what is required.

This means that the engineer must fully understand what the possible uses of the structure will be for its intended design life. This means the structures that engineers design is a prediction of what is structurally and spatially required during a buildings intended use.

6

Figure 3.02- Indicative Design Working Life (BSI, 2010)

Figure 3.03- Durability (BSI, 2010)

BSI (2010) shows the importance of specifying the design working life of a building. It is indicated that the design working life for building structures is from 50 to 120 years. This data seems arbitrary as there is no evidence of where the data came from. Many structures have survived for over hundreds of years.

Apart from the physical attributes of the structure the durability of a structure is also dependent on: ‘the intended or foreseeable use of the structure; the required design criteria; and the intended maintenance during the design working life’.

These are the social and economic considerations that an engineer must predict in the design of a structural system for the design working life of a structure to be uncompromised. BSI (2010) is ambiguous in guiding how to deal with these considerations and most engineers fail to properly interrogate a brief past a client or architect’s superficial indications of building use and longevity.

This brings the questions on the minimum spatial standards and definitions set for required uses of a building. Also if the building design life is intended for more than 15 years, which most concrete structures are, what precautions are there for changes in use, spatial layout, services, envelope and structure?

Moynihan (2014) argues that 1500 million tonnes of steel are produced every year, which accounts for 9% of global carbon dioxide emissions from energy and processes. He identifies that it is necessary to have a 75% reduction of carbon emissions per kilogram of steel produced. To help achieve this it is argued that engineers should prioritise design for minimum material usage over minimum cost to achieve this reduction in global carbon emissions.

This argues to increase the efficiency of the structural design and reduce over designed structures.

7

Webster (2007) suggests the use of Structural Design for Adaptability and Deconstruction (DAFD) to increase the overall sustainability portfolio of a structural design. DFAD benefits include:

This highlights the need to reduce steel used in construction through economizing on structure, to reduce the carbon footprint of construction. This argument is sound if the structural members fulfil their design life or are designed for disassembly and reuse. This however neglects the environmental, economic and social impact of such structures.





The Concrete Centre (2016) identifies that a significant proportion of environmental impact of construction is due to the use of resources: energy; water; and materials. They identify a ‘material resource efficiency’ approach to design and construction, but also consider the design life of structural system. There is also guidance on using adaptability principles to extend the design life of buildings.



This design ethos sets low standards to avoid obsolescent structures. They draw the conclusion that it is the most sustainably and economically viable solution. As long as the minimum requirements of the brief are addressed with an appropriate structural system, buildings are passed for construction.

Such organisations regulate the production of building infrastructure and the consumption of building materials. The need to reduce carbon emissions and natural resource use means that designers must question the philosophy behind the design principles and the construction industry.

Generally extending the useful life of a building over demolishing and rebuilding has environmental and economic benefits.

Reuse of structural components reduces the need for using new material resources and the energy required to manufacture new components. This leads to less waste deposited in landfill. This also enables capital to be recovered from the deconstruction and sale of building components.

The ease of adaption also saves costs when renovating a property and enables the building to be resold in a broader property market.

DFAD Strategies include:            

Webster (2007) argues that the role of structural engineers in considering the sustainability factors associated with building design is often overshadowed by mechanical engineers and architects. However, the sustainability impact of the material and construction footprint of the structure, which is the responsibility of the structural engineer cannot be ignored.

8

Regular plan layout.

Common component shapes and connections Design fewer larger members over many small members Layer building systems so they can be independently changed Use removable fasteners over adhesives and welds at key connections Use salvaged materials where applicable Avoid composite systems unless the system can be reused.

Consider deconstruction processes Label components for future structural considerations.

Consider overdesign to increase adaptability Safeguard design drawings and calculations Use non-hazardous non-toxic and durable materials

Mallach (2006) investigates how the economic and social impact of abandoned buildings affects their surrounding communities. It is found that obsolete and abandoned buildings:

3.3 STRUCTURAL OBSOLESCENCE What happens when the functional requirements of the brief change? The answer is the obsolescence of buildings. Buildings which are not easily able to cope with the dynamic movements in economic, social and environmental requirements of the built environment are abandoned or destroyed.

Lemer (1996) defines obsolescence: “Obsolescence results when there is a change in requirements or expectations regarding the use of a particular object or idea.”

Structural obsolescence is caused when a structural system does not provide for changes in spatial requirements and cannot adapt to technological changes. The issue of infrastructure obsolescence is rarely found in scholarly literature of civil engineering or architecture. Lemer (1996) identifies the factors that can cause structural obsolescence as:    



  

This creates a major waste of resources and land. Cities become mass consumers of land, energy and material resources.

Technological changes influence the scope or levels of services infrastructure is to provide.

Regulatory changes impose new requirements on infrastructure.

Economic changes in the markets within a region can influence infrastructure demands.

Social changes of stakeholder expectations of infrastructure can alter the infrastructures demands.

The city of Detroit boomed with the industrialisation of car manufacture. Many factories and communities were built upon this one industry. As the industry moved overseas the city was left with a plague of obsolete infrastructure with maintenance which was no longer feasible.

Arge K, (2005) compared buildings designed by different real estate developer typologies to investigate which group tended towards designing obsolescent buildings. From case study investigation it was found that:

Lemer (1996) identifies ways to mitigating structural obsolescence: 



In a Philadelphia study the presence of one abandoned property reduced the value of other properties on the block by £6500.

Increase general criminal activities in areas of these communities Increase the risk of fire due to the dumping of rubbish and can lead to pest infestation.

Increase government spending due to demolition, security and emergency service costs.



Design and construct to provide flexibility to respond to obsolescence inducing factors and accommodate changes in performance requirements.

Monitor changes during operation and respond to slow degradation or address optimum performance requirements



9

30% of the buildings, from developers who commissioned buildings for their own use, had obsolescence tending designs; 45% of the buildings, from developers who commissioned buildings for rental and management, had obsolescence tending designs;



63% of the buildings, from developers who commissioned buildings sale, had obsolescence tending designs;

3.4 STRUCTURAL ADAPTABILITY Figure 3.04- Building Layers (Brand, 1997)

This shows that developer incentives to maximise profit by reducing construction costs create more obsolescent structures. These incentives should be deterred to reduce the risk of early structural obsolescence.

Current design requirements give developers, especially those who build to sell on, the incentives to construct cheaper mass-produced buildings which are more likely to become obsolete in 15 years.

This means that regulatory bodies must deter incentives to buildings which tend to obsolescence. To implement this a measure of obsolescence must be established as a criterion for design. From an environmental standpoint saving costs on structure in the short term will significantly reduce the design life of buildings and create major waste in terms of material embodied energy. From an economic standpoint this deteriorates the quality of building stock and creates debt bubbles in housing where the value of a unit quickly depreciates in comparison to price at sale; and from a social standpoint creates slums of obsolete districts (Bullen, 2017).

Brand (1997) in his seven S’s, showing the hierarchy of the layers of a buildings composition, identifies the design life of each component. Adaptable design of structure argues that if a component must be replaced, which is not easily allowed by the structural frame, the building will become obsolete and limited to the lifecycle of that component. This dependence on structure frame is elaborated further by Schneider T, Till J (2007):    

10

Changes to the space plan depends on the structural layout and floor to floor heights.

Changes to services depend on accessibility of service voids and floor to ceiling heights Changes to exterior skin depend on the ease of disassembly without structural change Changes to structural layout depend on foundation capacity and ease of construction

Pinder (2017) investigated how different literature and practitioners intemperate ‘adaptability’ in the context of the built environment.

This is done through a comparative literature review on various definitions of adaptability and interviews with practitioners in the build environment including: architects; engineers; project managers; property agents; and planners. Through review of literature on adaptability Pinder (2017) found: 

  

(Schmidt et al. 2010) is the most comprehensive classification of the types of adaptability to be:      

The varied definitions and interpretations of the term adaptability have created many public misconceptions and misuse.

This can cause barriers to the development of adaptable principles and structures.

There is a need to have a unifying and agreed definition of ‘adaptability’ and ‘flexibility’ to dissolve any misconceptions.

This is shown as there is very little understanding about how practitioners comprehend adaptability.

Adjustable when changing the configuration of an individual setting.

Versatile when changing the dimensions of a space.

Retrofit-able when changing the performance of a building.

Convertible when changing the use/function of a building.

Scalable when changing the size of a building.

Movable when changing the location of a building.

Figure 3.05- Types of Adaptability (Schmidt et al. 2010)

Through interview with various practitioners Pinder (2017) found:  

Practitioners had a rich and varied terminology to describe adaptability These meanings varied according to building sector over practitioner discipline

This shows that the definition of adaptability has had a variety of different definitions by various authors which given a level of ambiguity when dealing with specific issues. Most authors do agree that the limiting factor when dealing with the adaptability of a building is the design of the structural frame. Pinder (2017) identifies the need to educate practitioners and clients with an understanding of the effectiveness of adaptability technologies. This will reduce the occurrence of unnecessary overdesign which contributes to a waste of resources. Pinder (2017) suggest

These relate to categories of adaptability and categorise various strategies and design principles that relate to adaptability. The underlying value of building adaptability is the resistance to building obsolescence. It is important to understanding how the key 11

    

principles of adaptability that relate to resisting building obsolescence. Bullen (2017) investigates the sustainability aspects of adaptive reuse of buildings in comparison to demolition and rebuilding. A survey of building owners shows how using the adaptive reuse strategies are perceived. Bullen (2017) identified the sustainability agenda as: economic; environmental; and social sustainability. Bullen (2017) found that:   

 

  

To enable adaptive reuse to be a viable strategy requires adaptable design which:

A clear majority of responders preferred adaption over demolition.

One key decision factor is the comparison of costs and benefits over a lifetime.

Strategies to provide changes in building use and density, to address changes in land use and value, are important in adaptive reuse.

Economically it is generally more viable to improve the building than demolish Adaptability design should be included in the initial feasibility stage of the design process to identify if projected outcomes would meet sustainability benchmarks.

The ease of adaption must be technologically and economically identified.

Environmental, economic and social sustainability were considered important by most responders.

Must overcome industry incentives to favour new builds

    

Shows the viable cost benefits over the life of the building Maintains structural integrity over design life Can effectively respond to changing building use demands Can effectively respond to changing building density demands Can effectively enable changes to services and building envelope

Israelsson (2009), using a questionnaire to 52 real estate and construction companies, identified the factors that influence adaptability. These factors include:      

Bullen Concluded that Adaptive Reuse:     

Enhances existing communities Reduces land consumption and urban sprawl Enhances the aesthetic appeal of neighbourhoods Increases the demand for existing structures Retains historic streetscape, communities sense of place and cultural heritage

Reduces resource consumption, energy use and emissions Extends the design life of buildings Is more cost effective than demolishing and building new Reclaims material embodied energy over time Improves community resources

Material Standard Production Method Design Life Changes Installations Financial Aspects Adaptability Awareness

Adaptability awareness and the financial aspects are identified as being the key factors affecting adaptability. To increase awareness practitioners must advise the key decision makers of the benefits of adaptability design. To do this studies must prove that the financial aspects of adaptability are proven greater than the current status 12

quo.

Isrealsson (2009) also identifies the stakeholders who affect the adaptability of buildings as: architects; Contractors; Authorities; Project Manager; Users; and Clients; whilst Clients and Property Owners are identified as having a key role. This shows that there are clear misconceptions of how the importance of the structural design relates to the adaptability of buildings. Unadaptable structural design is one of the key causes of building obsolescence.

This means industry standard must recognise structural engineers as having a key role in deciding on adaptable design.

Figure 3.06- Origin and Destination Uses (Kincaid, 2000)

Kincaid (2000) studied the building typologies in planning applications, involving changes of use, to determine the fluidity of origin and destination uses. From his study he found that the office typology is the most adapted with 49.4% of change of use planning applications. The Residential typology the majority of destination uses with 56.7% of use planning applications. This is shown in Figure 3.06.

Remøy et al. (2011) evaluated the adaptability of office building case studies to identify specific design characteristics that enhance transformation potential. These features include:      

13

Façade Grid Height- 1.8m fits office and housing Height: 3.6m is standard for office and leaves room for housing Width: 7.2m is the standard office bay width and is suitable for housing Depth: 15-24m depending on massing Horizontal Extendibility: Columns on façade allow for balconies or small addition Vertical Extendibility: Extra capacity to allow for additional floor additions

Ross et al. (2016) identified and evaluated adaptability enabling technologies to combat structural obsolescence. These include:          

Figure 3.08- Photograph of Parkhill during Renovation (Levitt, 2010)

Layering of Building Components and Systems Accurate Structural Information Reserve Capacity Design for Deconstruction Mechanical Connections Access for Assessment Simplicity Commonality Modularity Appropriate Materials Open Plan Layouts

Figure 3.07- Effectiveness of Design-Based Adaptability Enablers (Ross et al. 2016) Park Hill, Sheffield was a social housing scheme which questioned how housing and the street could be stacked through a support structure to reduce the need for suburban sprawl. Adjodha, (2017) assessed the adaptability of Park Hill and how successful Urban Slash’s Phase-I Re-opening in 2011. These units can be accessed by a level deck which runs parallel to the streetscape. This allows for access without the need for independent lifts (Bacon,1985). The module can accommodate a variety of housing and office configurations which allows for changes in use. The adaptable design of its structural frame prevented its obsolescence and enabled its reuse (Adjodha, 2017).

From a survey of professionals with experience in reuse and adaption projects, in Ross et al. (2016) found that the main enablers were: Accurate Information; Reserve Capacity; Layering of Building Components and Systems; and Open Plan Layouts.

Designing for a measure of adaptability enables the durability of the design brief and should be a priority for Clients, Engineers and Architects alike. This creates a need to define relevant standards of

14

adaptability in structural design to manage obsolescence and better predict the design service life of built structure.

3.5 STRUCTURAL BIOMIMICRY Following adaptability is a concept of controlled growth. How can a building be designed to grow and shrink with social, economic and environmental changes?

For designers to ensure further design longevity there is a need to define how a building can expand or contract. This will enable the building to be adjusted to suit changes in the viability of the scale of the building, whilst preserving the qualities of original spaces.

Commercially the ability to upsize and downsize easily to suit market forces is a major advantage. Structurally this is to provision for a controlled amount of expected expansion whilst enabling the disassembly of members.

The limiting factor for a structural designs ability to grow is its foundation capacity and layout. Being the most expensive component and hardest to alter, it requires the most consideration in determining the most suitable design for projected growth (Butcher, et al. 2006).

Chen (2016) investigates how the study of natural structures can inform the design of built structures. Her long term goal is to contribute towards a new design approach. She argues biomimicry design takes inspiration from natural systems to find suitable solution to a problem. Learning from 3.8 billion years’ worth of evolutionary optimization and adaption one can be familiar with nature’s principles.

Chen (2016) investigates how the adaptable growth of natural structures can inform the design of the built structures through quantitative biomimetic design. This is to model biomimetic systems into a quantitative tool for engineers. This involves: 1) The study of natural structure to create: mathematical models; finite element models; and structural analysis data.

2) Parametric Studies to investigate the models to determine 15

how these structures adapt and grow.

3) Application of models to inform the design of built structures.

growth were produced. Experimental analysis of the structural properties of the shell was used to create and validate the structural model. The finite element model was used to study the structural properties which relate to growth and ecological changes.

Figure 3.09- Structural Engineering Biomimicry (Chen, 2016)

From these studies Chen (2016) found: 

  

The organism has evolved to maximize its living space, minimize its cumulative shell mass and resist breaking forces.

Shell growth increases the shells ability to resist shear forces through increased flexural properties As the shell grows the ratio between shell volume and shell mass increases Shells become more capable of resisting lateral loads with age

Chen (2016) identifies that it is difficult to see a direct link between shell growth and built structures. However, through a greater library of numerical biomimetic studies more concepts of natural adaptation and growth can be utilised to inform the built environment.

Chen et al. (2016) studies how natural structures develop in response to physical changes to help inform the design of built structures through quantitative biomimicry. This involves identifying the mathematical functions that govern the resulting structural form to create mathematical models of adaption. These governing equations are made by substituting a system’s constituting relationships, identified from empirical and experimental data, into more general laws of physics.

Chen (2016) tested her proposed design procedure to create models to characterise the growth of a Gastropod seashells. Using samples of shells of varied sizes mathematical models of their

For example, the governing equations of woodpeckers use equations of motion of harmonic oscillators. This simplifies its 16



characteristics as a spring-mas-damper system, which enables the development of mathematical and finite element (FE) models.

Biomimetic studies from this have led to the development of a new damping system for micro-machine devices under large acceleration and high frequencies.

 

Figure 3.10- Governing Equations of Systems (Chen, 2016)



The creation of a FE model is made by integrating the mechanical properties of the system from empirical and experimental studies.

This simplifies complex equations, geometries and phenomenon to be explored at a local level.

The FE model is validated by comparing calculated displacements and strains to those measured in physical experiments.

Parametric Studies can be conducted, once the FE model is validated, to identify the influence of certain parameters on an outcome.

Figure 3.11- Mathematic Modelling of Mollusk Shell (Chen, 2016)

Chen et al. (2016) investigates the governing equations behind the growth of mollusc shells. This quantitative biomimicry method involves:   

The creation of a mathematical model is derived from the series of geometrical equations in the FE model.

The creation of a 3-D model is created from inputting geometric variables into the mathematical model.

The creation of a structural model is made by applying material properties, external loads and boundary conditions.

They hope this simple growth model can be used as a starting point to characterise to adaptability features in structures. So that structural engineers can then use biomimicry models as a tool to design structures can adapt to changing requirements.

17

There is very little investigation into specifically how these studies apply to the build environment and how they can be used to develop a new design process. For this to occur models must be tested in real scenarios against social, environmental and economic factors.

Figure 3.13- Palmata Coral Cross-Sections (Chamberlain, 1978)

Figure 3.12- Structural Growth of Coral (Chamberlain, 1978)

Chamberlain (1978) investigates the mechanical properties of coral skeletons and how this relates to their adaptive features. This was done by measuring the compressive strength and elastic modulus of three Caribbean coral species and interoperating how these vary with colony location and size.

18

Scuderi (2015) investigates how insect’s exoskeletons can inform the way in which we rehabilitate obsolete structures to meet updated performance standards like earthquake resistance. Scuderi (2015) aimed to describe a new biomimetic model for the rehabilitation of social housing. Concepts of structural exoskeletons are found through: a qualitative study of different building systems technologies; and using biomimetic and adaptable design methods.

Chamberlain (1978) found that:  



  

 

The coral’s material properties are anisotropic and fracture similarly to slate The structural anisotropic properties are strongest adjacent to the direction of growth which is similar to bone and timber.

Compared to other skeletal materials coral has similar strength and absorption levels but with less material per unit volume Coral has superior properties to concrete and limestone Coral strength decreases with porosity Coral porosity increases with colony density due to the reduction in mechanical stresses, allowing more living density for organisms.

Coral in dense colonies grow vertically which is similar to trees in a forest and buildings in a city.

Breakages of live coral enable new coral to grow and spread.

Figure 3.14- Strategies of Growth (Scideri’s, 2015)

Scideri’s (2015) strategies of growth include:

The palmata coral species can be taken as a model of vertical structural growth. From the studies of the mechanics of growth the model can be applied and tested in built structures.

    

19

Continuity: An addition of structure using a continuing aesthetic Contrast: An addition of structure using a contrasting aesthetic Completion: An addition of structure which completes the aesthetic Absorption: An addition of structure which absorbs the existing structure Integration: An addition of structure using an integrating aesthetic

  

These conceptual strategies of growth and metamorphism are used to react to obsolescent causing changes to increase the design life of the structure. The concepts need to be testing to compare their sustainability performances to strategies of new construction.

Through innovation of biomimicry principles, a structural engineer can develop systems for the growth of infrastructure. This could utilise the adaptability of a structure to reduce its embodied energy by increasing their lifespan and re-usability.

Contraposition: An addition of structure which counterbalances the existing Stratification: An addition of structure to the existing face Filling: An addition of structure between two existing faces

Figure 3.15- Strategies of Metamorphism (Scideri’s, 2015)

Scideri’s (2015) strategies of metamorphism include:        

Substitution: A substitution of structure for a new element Modification: A modification of the existing structure Cut: A reduction of existing structure to accommodate a new design Selection: A removal of existing elements to accommodate a new design Replacement: A replacement of an existing structure for a new element Adjustment: An adjustment of an existing element to change its characteristics Revision: A revision of existing structural elements to maintain its features Renewal: A renewal of existing structural elements to change its features

20

Natural structures grow to deal with changing environmental and special requirements. Biomimetic studies and modelling of natural structural growth can help inform the design and growth of built structures (Chen, 2016). Scideri (2015) investigates various growth strategies to rehabilitate obsolete structures.

3.6 CONCLUSION The built environment must utilise natural resources effectively to preserve the inheritance of our planet. Yeang (1999) and Habraken (1972) identify the need to decrease urban sprawling and increase dwelling density to reduce transportation and land consumption.

Kincaid (2000) identifies the: economic; environmental; and social sustainability criteria in the built environment. Tingley & Davison (2011) and De Wolf (2017) highlight the importance of considering embodied energy and embodied carbon over the design life of a structure.

The literature fails to evaluate how the life-cycle impact of designing for growth compares to designing for optimum.

BSI (2010) define a structures design life as 50-120 years. Little guidance is given to structural design for the whole life cycle of the structure. The foreseeable uses of the structure is too be questioned by the Structural Engineer in order to prevent structural obsolescence. The industry focuses on structural optimisation and the initial benefits Moynihan (2014). There is little focus on the long term aspects of optimum design.

Optimum design can lead to building obsolescence which results in the premature demolitions of infrastructure (Lemer, 1996). This causes social, economic and environmental problems (Mallach, 2006). Arge, (2006) found that developers who build to sell on favour obsolescence tending designs compared to developers who build for rental or own use.

Adaptable structural design strategies can be utilised to reduce structural obsolescence (Bullen, 2017). The lack of coherence in the literature concerning the terminology and technology of adaptability creates industry misinterpretations (Pinder, 2017) and (Israelsson, 2009). Remøy et al. (2011) and Ross et al. (2016) identify key adaptable design enablers.

21

4 STRUCTURAL DESIGN FOR GROWTH This chapter specifies the methodology used and justifies the model used based on the literature and case studies discussed through: 4.1 Methodology; 4.2 Development of Structural Growth Models; 4.3 Design and Appraisal of Structural Growth Models. The hypothesis can then be tested through the methodology set out to obtain the data required to draw the relevant conclusions.

4.1 METHODOLOGY AIM To develop structural concepts using biomimicry and adaptability design principles and compare their economic, environmental and social outcomes to current structural engineering sustainability requirements.

HYPOTHESIS If the structural design of housing is designed to accommodate growth as opposed to the optimum requirements, when housing density demands change, there will be major benefits to the economic, social and environmental sustainability of the building over its design life.

22

23

The research follows this rational to develop and test ways in which the design process can incorporate a measured level of adaptability by comparing the social, economic and environmental impacts of an adaptably sensitive design against the minimum functional design in a particular scenario. This will incorporate a combination of qualitative, design and quantitative methods.

4.2 DEVELOPMENT OF STRUCTURAL MODELS From carrying out an investigation of relevant literature and case studies the author identified a lack of analysis comparing the sustainability of optimum structural design adaptive structural design, over the design life of a building.

Figure 4.02- Structural Model

This dissertation will therefore aim to compare the social, economic and environmental sustainability of growth adaptable design model to structural optimisation design over the design life of a building in various scenarios of dwelling density rise. This will test if technologies that enable structural growth can greatly improve the sustainability criteria the by reducing the occurrence building obsolescence due to structural design (Lemer, 1996), (Mallach, 2006).

The author has used their experience of Structural Engineering and Architecture to develop and evaluate structural growth concepts.

The structural design is influenced by adaptability enabling factors discussed by: Ross et al. (2016); Kincaid (2000); Arge (2005); and Remøy (2011), and biomimetic design methods indicated by Chen (2016). The author is testing a structural growth strategy inspired by the characteristics of coral growth in dense colonies as to inform the design of structural growth in cities (Chamberlain, 1978).

The scenario looks at a street of structural units which may accommodate housing and office units (Figure 4.02). The 3 storey modules were adapted from the social housing scheme Park Hill (Adjodha, 2017).

The models structural grid uses Remøy’s (2011) guidance on adaptable office buildings:    

24

The Façade Grid Height- 1.8m fits office and housing Height: 3.6m is standard for office and leaves room for housing Width: 7.2m is the standard office bay width and is suitable for housing Depth: 15-24m depending on massing

To test the overall social, environmental and economic impact in response to land value and housing density fluctuation, the module number of the structural unit is varied over a structural design life of 120 years (BSI,2010). The rate of change in dwelling density is varied over the design life to accommodate varied land pressures.

Models of growth were developed by the author to be tested in response to housing density changes (Figure 4.03). These include: 1. New build Model (Optimum Design Model) (Figure 4.05) This model simulates a structural design which priorities the optimum structural solution. As the housing density required rises the structural unit becomes obsolete and a new structure is constructed to meet the new demand. The model assumes there is no ability to reuse structural members or recover cost through disassembly and upcycling. This typology models the current status quo where initial economic gain, from a low initial cost, and ignores the long term effects of building obsolescence.

Figure 4.03- Addition of Modules in Response to Dwelling Density

Figure 4.04 New Build Model Composition

25

2. Redundancy Model (Growth Model) (Figure 4.05)

3. Retrofit Model (Conversion Model) (Figure 4.06)

This model explores planned structural growth or staged construction. The base of the structure is designed to accommodate additional expansion to deal with future density demands. As the density required rises additional modules can be added with minimal disruption to the base structure. This typology is scarcely used due to the high initial cost but its long term benefits mitigate obsolescence.

This model simulates a structural design which allows for conversion of the structural frame to accommodate expansion. As housing density demand rises the structural unit is retrofitted to accommodate expansion but the operations of the base modules must be suspended during conversion. This typology is scarcely used due to structural design ambiguity and technological challenges but provides a low initial cost and long term benefits.

Figure 4.05 Growth Model Composition

Figure 4.06- Conversion Model Composition

This model takes influence from the humble tree as it grows from a seed. Its roots (foundation) grow to spread its loads into the ground.

The trunk (core/column) increases in diameter to transfer lateral and longitudinal loads. The branches and leaves (beams/slabs/cladding) change to suit the environment and seasons.

26

Figure 4.07- Conversion of Columns in Modules

Figure 4.08- Conversion of Shear Walls in Modules

The model assumes column strengthening through thickening with an encasement of reinforced concrete (Figure 4.07). This requires special and construction planning to enable an ease of access during construction. The properties of the original member design must be understood to allow for an effective conversion of the member. Other techniques of column confinement can be used to increase the structural properties to an adequate level.

The model assumes shear walls can be lengthened through structural addition (Figure 4.08). This requires spacial planning and structural accessablilty to allow an ease of construction. The properties of the original design must be understood to allow for effective redesign. Utilising Structural damping and additional external bracing can also be utilised to provide adequate structural properties.

27

Figure 4.09- Conversion of Foundation in Base Modules

4.3 DESIGN AND APPRAISAL OF STRUCTURAL GROWTH MODELS To calculate the economic environmental and social sustainability factors associated with each model the volume of reinforced concrete for each module member was calculated using concrete scheme design (Brooker, 2006). The full calculations are shown in Appendix (9.1).

The two-way slab on down stand beams were designed using Table 2.15 of (Brooker, 2006). The members sizing is shown in Tables 4.01-4.02.

The model assumes the foundation design can be strengthened through thickening the existing structure and the soil conditions are able to resist the loads. This requires special planning to allow foundation expansion via an upward addition. Butcher (2006) discusses processes to enable effective reuse of foundations (Figure 4.09).

Table 4.01 Showing Slab Design for Each Module Unit

The resulting concrete frames are based on scheme design requirements in order to estimate material requirements. The material requirements are used to calculate the structures cost, embodied energy and embodied carbon. These values are used to compare the adaptive growth model against building optimisation model over a structures lifespan under varying land demand simulations.

Module

Thickness(m)

Vol (m^3) 13

Slab Number 27

Total Vol (m^3) 351.0

Labour Cost (ÂŁ) 6,973.0

1

0.25

2

0.25

13

27

351.0

6,973.0

3

0.25

13

27

351.0

6,973.0

4

0.25

13

27

351.0

6,973.0

Table 4.02 Showing Beam Design for Each Module Unit

28

Modul e

d (m)

w (m)

Length (m)

Vol (m^3) 1.08

Beam Numbe r 72

Total Vol (m^3) 77.8

Labour Cost (ÂŁ) 2,137.5

1

0.5

0.3

7.2

2

0.5

0.3

3

0.5

0.3

7.2

1.08

72

77.8

2,137.5

7.2

1.08

72

77.8

2,137.5

4

0.5

0.3

7.2

1.08

72

77.8

2,137.5

The two-way slabs on down stand beams were designed using Table 2.23 of (Brooker, 2006). The member sizing is shown in Tables 4.03.

The shear walls were designed using Table 2.24 of (Brooker, 2006).

The member sizing is shown in Tables 4.03.

Table 4.05 Showing Shear Wall Design for Each Module Unit

Table 4.03 Showing Column Design for Each Module Unit b (m)

w (m)

1

0.32

0.32

10.8

1.1

Colum n Numbe r 16.0

2

0.44

0.44

10.8

2.1

16.0

33.5

919.6

3

0.53

0.53

10.8

3.0

16.0

48.5

1,334.3

4

0.6

0.6

10.8

3.9

16.0

62.2

1,710.0

Modul e

Height (m)

Vol (m^3)

Total Vol (m^3)

Labour Cost (£)

17.7

486.4

Module

b (m)

t (m)

Height (m)

Labour Cost (£)

10.8

Total Volume (m^3) 11.7

1

1.8

0.3

2

3.6

3

5.4

0.3

10.8

23.3

495.8

0.3

10.8

35.0

743.6

4

7.2

0.3

10.8

46.7

991.5

247.9

The total volume of reinforced concrete for each module was calculated and is shown in Table 4.06.

The raft foundations were designed using from imposed diagonal tension shear (ACI-05 11.12.2.1.c). The member sizing is shown in Tables 4.04.

Table 4.06 Showing Total Design Volume for each Module Unit Module

Table 4.04 Showing Raft Foundation Design for Each Module Unit Module

Ned (kN)

dav (mm)

Area (m^)

1

1958

0.33

466.6

2

3916

0.94

466.6

1

Module Volume (m^3) 458.1

Foundation Volume (m^3) 200.6

Base Module Volume (m^3) 658.7

Labour Cost (£)

2

485.5

485.2

970.8

3

512.3

587.9

1100.2

0.4

Conc Volume (m^3) 200.6

3985.5

4

537.6

676.5

1214.1

1.0

485.2

9639.4

(1-2)

27.4

284.6

312.0

26.7

102.6

129.4

25.3

88.6

114.0

h (m)

3

5874

1.16

466.6

1.3

587.9

11678.5

(2-3)

4

7832

1.35

466.6

1.5

676.5

13439.6

(3-4)

The market data for concrete and steel reinforcement were sourced from various UK suppliers. This data is shown in table 4.07.

29

Table 4.07 Showing Market and Production Data for Structural Materials Material

Conversion Cost (ÂŁ per m^3) 150

Embodied E (MJ per m^3)

CO2 (Kg per m^3)

Concrete

New Build Cost (ÂŁ per m^3) 100

50

3.75

Steel Rebar

5000

7500

293000

7700

2% Reinforced Concrete

198

297

5909

157.675

were used to determine the outcomes of the test scenarios shown in Figure 4.11. The findings are shown and discussed in chapter 5.

The labour costs were sourced from various UK construction companies. This data is shown in table 4.08.

Table 4.08 Showing Salary Data for Construction Labour Component

Workmen Hours/ Tonne Steel

Workmen Hours/ m^3 Steel

Labour Cost/ m^3 Steel 993.3

New Build Labour Cost/ m^3 reinforced conc 19.9

Conversion Labour Cost/ m^3 reinforced conc 26.5

Slab/ Foundation Column/ Beam Shear Wall

8.6

66.2

11.9

91.6

1,374.5

27.5

36.7

9.2

70.8

1,062.6

21.3

28.3

The resulting module designs are shown in Figure 4.10. These

30

31

32

De Wolf’s (2017) benchmarks for embodied energy can give some indication of the model’s accuracy for calculating embodied energy and carbon. For each three storey module unit of 1400m2 floor area the benchmark gives:

5 RESULTS In this chapter the results of the study are displayed and discussed in: 5.1 Findings and scope of study; 5.2 Discussion; 5.3 Implications.

 

This can be compared to the various module Embodied energies in Table 5.01. A comparison of the Embodied Energy in the models to the benchmark shows that the error is between 5-13%. This shows that the model a gives a good representation of Embodied Energy.

A comparison of the Embodied Carbon in the models to the benchmark shows that the error is between 42-49%. This shows that the model is significantly below the benchmark of Embodied Carbon. This difference may be due to the embodied carbon due to material transportation which is not covered in the model calculation.

5.1 FINDINGS AND SCOPE OF STUDY The three sets of data correspond to the varied scenarios of rising dwelling density:   

3,500,000MJ for Embodied Energy 210,000 kg for Embodied CO2

Scenario 4 (Dwelling density rises by a factor of four) shown in Figure 5.01; Scenario 3 (Dwelling Density rises by a factor of three) shown in Figure 5.02; Scenario 2 (Dwelling Density rises by a factor of two) shown in Figure 5.03.

Table 5.01 Evaluation of Model Embodied Energy and Carbon Error

The three models of growth: O (Optimum); G (Growth); and C (Conversion) are compared with the calculated: Cost; Embodied Energy; and CO2 over a 120-year time period.

Modul e

Embodied E (MJ )

Embodie d Energy Error (%)

CO2 (Kg )

CO2 Benchmar k (Kg)

CO2 Error (%)

2,707,024

Embodied E Benchmark (MJ) 3,499,200

1 2

13

72,234

209,952

49

2,869,068

3,499,200

10

76,558

209,952

47

3

3,027,131

3,499,200

7

80,776

209,952

44

4

3,176,820

3,499,200

5

84,770

209,952

42

The data is based on the assumptions that:      

Errors due to using scheme member design are minimal The Structural cost is reflective of the total building cost Interferences to building operations due to construction are minimal Material costs and labour costs remain constant throughout the buildings design life Housing Density Demand rises linearly Module designs are constant in each growth model

33

Figure 5.01- Graphs Showing Model Response to Scenario 4

4. Growth vs Optimum Embodied Energy

128.6

Dwellings per Hecter

140.0 120.0

Embodied Energy (MJ)

4. Density Demand Rises by Factor of 4 128.6

96.5

100.0 80.0

64.3

60.0 40.0

32.2

20.0

45,000,000 40,000,000 35,000,000 30,000,000 25,000,000 20,000,000 15,000,000 10,000,000 5,000,000 0

0 30 60 90 120 G Embodied E (MJ) 7,174,330 10,201,460 13,070,528 15,777,552 15,777,552 C Embodied E (MJ) 3,892,492 8,443,271 12,076,920 15,777,552 15,777,552 O Embodied E (MJ) 3,892,492 12,335,763 24,412,683 40,190,235 40,190,235

0.0 0

30

60

90

120

Time Period (years)

Time Period (years)

G Embodied E (MJ)

G Cost (£) C Cost (£) O Cost (£)

0 265,651 144,261 144,261

30 378,273 345,931 457,190

60 484,936 497,568 905,103

90 585,488 653,033 1,490,592

120 585,488 653,033 1,490,592

1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 G CO2 (Kg) C CO2 (Kg) O CO2 (Kg)

0 191,439 103,867 103,867

Time Period (years) G Cost (£)

C Cost (£)

O Embodied E (MJ)

4. Growth vs Optimum CO2 Emissions CO2 Emissions (kg)

Cumalative Cost (£)

4. Growth vs Optimum Cumalative Cost 1,600,000 1,400,000 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0

C Embodied E (MJ)

30 272,214 225,299 329,166

60 348,772 322,259 651,425

90 421,006 421,006 1,072,431

Time Period (years)

O Cost (£)

G CO2 (Kg)

34

C CO2 (Kg)

O CO2 (Kg)

120 421,006 421,006 1,072,431

Embodied Energy (MJ)

Figure 5.02- Graphs Showing Model Response to Scenario 3

Density Demand Rises by Factor of 3 Dwellings per Hecter

120.0 96.5

96.5

100.0 80.0

64.3

60.0 40.0

3. Growth vs Optimum Embodied Energy (MJ) 30,000,000 25,000,000 20,000,000 15,000,000 10,000,000 5,000,000 0

G Embodied E (MJ) C Embodied E (MJ) O Embodied E (MJ)

32.2

20.0

0 6,500,828 3,892,492 3,892,492

40 9,369,897 8,443,271 12,335,763

80 12,076,920 12,076,920 24,412,683

120 12,076,920 12,076,920 24,412,683

0.0 0

40

80

Time Period (years)

120 G Embodied E (MJ)

Time Period (years)

1,000,000 800,000 600,000 400,000 200,000 0 G Cost (£) C Cost (£) O Cost (£)

0 240,698 144,261 144,261

40 347,361 345,931 457,190

80 447,914 497,568 905,103

CO2 Emissions (kg)

Cumalative Cost (£)

3. Growth vs Optimum Cumalative Cost

120 447,914 497,568 905,103

C Cost (£)

O Embodied E (MJ)

3. Growth vs Optimum CO2 Emissions 30,000,000 25,000,000 20,000,000 15,000,000 10,000,000 5,000,000 0 G Embodied E (MJ) C Embodied E (MJ) O Embodied E (MJ)

Time Period (years) G Cost (£)

C Embodied E (MJ)

0 6,500,828 3,892,492 3,892,492

40 9,369,897 8,443,271 12,335,763

80 12,076,920 12,076,920 24,412,683

120 12,076,920 12,076,920 24,412,683

Time Period (years)

O Cost (£)

G Embodied E (MJ)

35

C Embodied E (MJ)

O Embodied E (MJ)

Embodied Energy (MJ)

Figure 5.03- Graphs Showing Model Response to Scenario 2

Density Demand Rises by Factor of 2 64.3

Dwellings per Hecter

70.0

64.3

60.0 50.0 40.0

32.2

30.0 20.0 10.0

2. Growth vs Optimum Embodied Energy 14,000,000 12,000,000 10,000,000 8,000,000 6,000,000 4,000,000 2,000,000 0 G Embodied E (MJ) C Embodied E (MJ) O Embodied E (MJ)

0 5,736,247 3,892,492 3,892,492

0

60

120

G Embodied E (MJ)

Time Period (years)

60 312,929 345,931 457,190

CO2 Emissions (kg)

Cumalative Cost(£)

0 212,377 144,261 144,261

120 312,929 345,931 457,190

350,000 300,000 250,000 200,000 150,000 100,000 50,000 0 G CO2 (Kg) C CO2 (Kg) O CO2 (Kg)

0 153,065 103,867 103,867

G CO2 (Kg) C Cost (£)

O Embodied E (MJ)

60 225,299 225,299 329,166

Time Period (years)

Time Period (years) G Cost (£)

C Embodied E (MJ)

2. Growth vs Optimum CO2 Emissions

2. Growth vs Optimum Cumalative Cost

G Cost (£) C Cost (£) O Cost (£)

120 8,443,271 8,443,271 12,335,763

Time Period (years)

0.0

500,000 400,000 300,000 200,000 100,000 0

60 8,443,271 8,443,271 12,335,763

O Cost (£)

36

C CO2 (Kg)

O CO2 (Kg)

120 225,299 225,299 329,166

Table 5.02 Comparing Models When Density Rises by a Factor of 4

5.2 DISCUSSION This dissertation has evaluated three models of structural growth to determine the sustainability aspects of each method over varying rates of growth. It was found that as dwelling density demand rises: 





The total structural cost, embodied carbon and embodied energy of the optimum design was significantly greater than the growth and conversion models.

The initial structural cost, embodied energy and carbon of the growth model was initially much greater than the conversion and the optimum models, but was the lowest at the end of the structures design life.

The conversion model on average provided the lowest structural cost, embodied energy and carbon throughout the buildings lifecycle. Effects from interference to building operations have not been covered by this study.



Cost Proportion of Optimum @ 0 years

Cost Proportion of Optimum @ 120 years

39%

C02/ Embodied Energy Proportion of Optimum @ 0 years 184%

C02/ Embodied Energy Proportion of Optimum @ 120 years 39%

Growth

184%

Conversion

100%

43%

100%

39%

Table 5.03 Comparing Models When Density Rises by a Factor of 3

As the rate of dwelling density rise increases: 

Model

The total structural cost, embodied carbon and embodied energy proportion of optimum for growth and conversion models decreases.

The initial structural cost, embodied energy and carbon proportion of optimum model for the growth model increases and decreases at end of the structures design life.

Model

Cost Proportion of Optimum @ 0 years

Cost Proportion of Optimum @ 120 years

49%

C02/ Embodied Energy Proportion of Optimum @ 0 years 167%

C02/ Embodied Energy Proportion of Optimum @ 120 years 49%

Growth

167%

Conversion

100%

55%

100%

49%

Table 5.04 Comparing Models When Density Rises by a Factor of 2

37

Model

Cost Proportion of Optimum @ 0 years

Cost Proportion of Optimum @ 120 years

68%

C02/ Embodied Energy Proportion of Optimum @ 0 years 147%

C02/ Embodied Energy Proportion of Optimum @ 120 years 68%

Growth

147%

Conversion

100%

75%

100%

68%

Figure 5.05- Graphs Showing Overall Cost per m2

Figure 5.04- Graphs Showing Overall Cost per Dwelling

Structural Cost per m2 per Year

5000

Cost per m^2 per Year

Cost per Dwelling per Year

Structural Cost per Dwelling per Year 4000 3000 2000 1000 0 0

20

40

60

80

Time Period (years)

4. G Cost per dwelling per year 4. O Cost per dwelling per year 3. C Cost per dwelling per year 2. G Cost per dwelling per year 2. O Cost per dwelling per year

100

120

2 0 0

60000 40000 20000 0 30

40

50

20

40

60

80

4. G Cost per m^2 per year 4. O Cost per m^2 per year 3. C Cost per m^2 per year 2. G Cost per m^2 per year 2. O Cost per m^2 per year

Mean Cost per Dwellig (ÂŁ/m^2)

Mean Cost per Dwellig (ÂŁ/Dwelling)

4

4. C Cost per dwelling per year 3. G Cost per dwelling per year 3. O Cost per dwelling per year 2. C Cost per dwelling per year

80000

20

6

100

120

140

Time Period (years)

100000

10

8

140

Mean Cost per Dwelling as a Proportion of Design Life

0

10

60

Proportion of Design Life (%) G Mean Cost per Dwelling C Mean Cost per Dwelling O Mean Cost per Dwelling

Mean Cost per m2 as a Proportion of Design Life 200 150 100 50 0 0

10

20

30

40

50

Proportion of Design Life (%) G Mean Cost per m^2 O Mean Cost perm^2

38

4. C Cost per m^2 per year 3. G Cost per m^2 per year 3. O Cost per m^2 per year 2. C Cost per m^2 per year

C Mean Cost per m^2

60

The author has calculated the structural cost per dwelling (housing) and m2 (office/commercial) of each growth concept. The investment required per year over each models lifetime has been compared.

The study covers changes from every 25% to 50% of the structures design life. From these result it can be seen that: 





was lower for the conversion model than the growth model. The difference between these models should vary depending on the brief, site conditions and structural technologies used. Exploring different structural growth models and making these accessible to clients enables a more informed decision making process to determine the right structural frame for the brief and cost.

Looking at the structural cost per dwelling and per m2 enables the client to plan find which method relates best to rental or sale rates of office or residential units. This enables the client to plan which option best suits their business plan.

The mean cost per dwelling or m2 for the optimum model increases as the rate of dwelling density demand increases (or proportion of design life decreases).

The mean cost per dwelling or m2 for growth and conversion model remain constant as the rate of dwelling density demand increases (or proportion of design life decreases).

The conversion model in this study is shown to have the lowest mean cost per dwelling or m2 as the rate of dwelling density demand increases (or proportion of design life decreases). This may depend on the availability of the technologies for structural conversion and the costs due to construction intrusion.

This study shows that as dwelling density demand rises, despite the initially low structural cost, embodied energy and embodied CO2 of the optimum model, considering the structural cost, embodied energy and embodied CO2 over the design life of a structure, the optimum model proves less sustainable than the growth and conversion models. Designing for deconstruction could enable more a sustainable outcome which is not tested in this study however a significant proportion of the structure must be reusable to reach the levels shown in the growth and conversion model.

The growth and conversion models prove to be the most sustainable solutions due to the reuse of the existing structure as the building grows. The structural cost at the end of the design life was lower for the growth model than the conversion model, but was higher initially. The mean structural cost per dwelling and per m2 39

buildings. This may be due to the low initial cost of the optimum model which enables maximum profit on sale. Developers who build for own use and rental tended to favour less obsolescence tending buildings. This may be due to the prioritisation of the long term cost savings of growth and conversion models. The structural engineer has a key role in identifying how to reduce structural obsolescence and enable developers to invest in lasting structures.

5.3 IMPLICATIONS Considering the sustainability aspects of a structure over its whole life cycle enables designers to make more informed choices when determining the appropriate structural strategy. Yeang (1999) and Habraken (1972) identify the need to increasing housing density to reduce land pressures on global ecosystems. Tingley & Davison (2011) propose that finding the embodied carbon and energy of a structure over its design life is critical in judging the relative sustainability of a structure.

Bullen (2017) investigated the benefits of adaptive reuse strategies. The growth and conversion models corroborate with his conclusions that adaptive reuse:

From evaluating the different structural models, in scenarios of rising dwelling density, the author has found that the design for optimum model has the highest structural cost, embodied energy and embodied carbon over the lifetime of the building. Arguments placed by authors such as Moynihan (2014) where prioritising the optimum design for minimum initial cost C02 and embodied energy saves initially and appears to be the most effective solution.

However, the results show that over a buildings life time in a situation where special demands increase the optimum model which fails to meet demands causes economic, social and environmental damages. The BSI (2010) guidance specifies that the structural design should be fit for the ‘intended or foreseeable use’ of the building. This fails to elaborate on designing for changes in the use or the demands of the brief. Structural obsolescence may arise if these situations are not carefully considered (Lemer, 1996).

     

Reduces resource consumption, energy use and emissions Extends the design life of buildings Is more cost effective than demolishing and building new Reclaims material embodied energy over time Reduces land consumption and urban sprawl Increases the demand for existing structures

Chen (2016) studies how biomimetic studies and modelling of structural growth in natural processes can help inform the design of built structures. The growth and conversion models in the study have taken influence from the growth of coral and trees. Further studies into how structural members can be designed to grow may enable future technologies of structural growth.

Member strengthening technologies like: column confinement; and metal strapping can also be investigated to increase the feasibility of the conversion model Garcia (2013). Biomimicry design can be used to improve structural growth strategies of members.

Parametric studies of how coral and trees increase the thickness of their structural members can also influence these technologies.

Mallach (2006) highlighted the economic and social impacts of building obsolescence and abandonment. The escalating costs associated with the optimum (new build) model may be the cause of such problems in times of use and demand changes. Arge (2005) looked at the relationships between types of developers and the design of obsolescence tending buildings. He found developers who build to sell on tended to favour more obsolescence tending 40

Considering methods of structural growth in the early consideration of structural design to reduce structural obsolescence through adaptable and biomimetic design principles. Incorporating similar cost and embodied energy forecasting methods into the design procedure can enable structural engineers to show the benefits of adaptive growth methods of construction.

41

6 CONCLUSIONS Evaluating structures over their whole-life cycle gives a better understanding of their sustainability. Purely designing for the optimum structure can lead to more obsolescence causing tendencies and limit the design life of a structure. Structural Engineers are responsible for the mitigating structural obsolescence prevent economic, social and environmental damages.

The literature suggests that incorporating adaptable design can reduce the occurrence of structural obsolescence by provisioning for a change in use or special demand. No studies were found to show the extent that adaptable design can increase the relative sustainability of a structure over a whole life cycle.

This author set out to compare models of optimum designed structure and adaptable growth designed structure over a whole building life cycle when special demands change. The study found that designing for adaptable growth in scenarios of rising dwelling density or land demand can significantly reduce the structural cost, embodied energy and embodied carbon over the whole life cycle of the building.

Technologies that enable the easy modification of structural components can further improve the applicability of adaptable growth to the design scenario. Structural growth is not uncommon in the natural world. Parametric studies of how natural structures grow can help enable adaptive reuse strategies. Awareness about preventing structural obsolescence through structural adaptability is needed in Structural Engineering education and the construction industry.

42

7 FUTURE RESEARCH POSSIBILITIES 



  

Investigating the relative sustainability of structural disassembly and reuse models, over a whole life cycle, as special density demand falls and for end of life recovery of building.

Investigating composite reinforced concrete slab, beams and column connection design to increase the applicability of structural disassembly and reuse.

Investigating the relative sustainability of structural growth models for high-rise buildings and skyscrapers.

Structural design and technologies for strengthening existing columns, shear walls and foundations.

Biomimetic parametric studies of structural growth in coral and trees to inform structural growth models of build structures.

43

Chena D A., Klotza L E, and Rossa B E. (2016). Mathematically characterizing natural systems for adaptable, biomimetic design.

Procedia Engineering. 145 (1), 497 – 503.

8 BIBLIOGRAPHY Adjodha J, (2017) “Audit of the Adaptability of Parkhill and Urban Slash’s Phase-I Reopening in 2011, Sheffield”, SSOA, p4-6

Chen D A (2016). THE ADAPTABLE GROWTH OF SEASHELLS: INFORMING THE DESIGN OF THE BUILT ENVIRONMENT THROUGH QUANTITATIVE BIOMIMICRY. Michigan: ProQuest. 110.

Arge K, (2005) "Adaptable office buildings: theory and practice", Facilities, Vol. 23 Issue: 3/4, pp.119-127, https://doi.org/10.1108/02632770510578494

De Wolf C, Pomponi F, Moncaster A. (2017). Measuring embodied carbon dioxide equivalent of buildings: A review and critique of current industry practice. Energy and Buildings. 140 (1), 68-78.

Bacon C (1985). Park Hill in its Social Context. Sheffield: University of Sheffield.

Brand S (1997). HOW BUILDINGS LEARN- What happens after they're built. 2nd ed. London: Phoenix Illustrated. 2-12

Denzin N K, Lincoln Y S (2000). Handbook of qualitative research.

London: Thousand Oaks. 1-29.

British Standards Institution. (2010) BS 1990:2002. Eurocode Basis of structural design. London, British Standards Institution.2129

Garcia R, Hajirasouliha I, Guadagnimi M et al.. (2013). Full-scale shaking table tests on a substandard RC building repaired and strengthened with Post-Tensioned Metal Straps. Journal of Earthquake Engineering. 18 (2), p1-45.

Brooker, O (2006). Concrete Buildings Scheme Design Manual.

Camberley, Surrey: The Concrete Centre. 1-128.

Habraken N J (1972). Supports: an alternative to mass housing.

Bedford: Architectural Press. p59.

Bullen P A . (2017). Adaptive Reuse and Sustainability of Commercial Buildings. Facilities. 25 (1/2), 20-31.

Israelsson N, Hansson B, (2009) "Factors influencing flexibility in buildings", Structural Survey, Vol. 27 Issue: 2, pp.138-147, https://doi.org/10.1108/02630800910956461

BUTCHER P, POWELL J J M, SKINNER H D (2006). REUSE OF FOUNDATIONS FOR URBAN SITES. Watford: IHS BRE Press. 110.

Kincaid D, (2000) "Adaptability potentials for buildings and infrastructure in sustainable cities", Facilities, Vol. 18 Issue: 3/4, pp.155-161, https://doi.org/10.1108/02632770010315724

Chamberlain J A. (1978). Mechanical Properties of Coral Skeleton: Compressive Strength and its Adaptive Significance. Paleobiology.

4 (4), 419-435

Lemer A C. (1996). INFRASTRUCTURE OBSOLESCENCE AND DESIGN SERVICE LIFE. JOURNAL OF INFRASTRUCTURE SYSTEMS. 2 (4), 153-161.

Chen D A, Ross B E & Klotz L E. (2015). LESSONS FROM A CORAL REEF: BIOMIMICRY FOR STRUCTURAL ENGINEERS. Journal of Structural Engineering. 141 (4), 1-7.

44

Mallach, Alan. (2006). Bringing Buildings Back: From Abandoned Properties to Community Assets : A Guidebook for Policymakers and Practitioners. Rutgers University Press.

Tingley D D, Davison B (2011). Design for deconstruction and material reuse. London: ICE Publishing. 195-202.

Moynihan M C, Allwood J M. (2014) Utilization of structural steel in buildings. Proc.R.Soc.A470:20140170. http://dx.doi.org/10.1098/rspa.2014.0170

Webster M D, Gumpertz S & Heger, Inc., Waltham, MA,. (2007).

Structural Design for Adaptability and Deconstruction: A Strategy for Closing the Materials Loop and Increasing Building Value.

Structures Congress: New Horizons and Better Practices. 1 (1), 1-6.

MPA, The Concrete Centre (2016). Material Efficiency. 2nd ed.

London: MPA The Concrete Centre. 2-19.

Yeang K (1991). Designing the Green Skyscraper. London: Pergamon Pres plc. P149-166

Pawlin M (2011). Biomimicry in Architecture. London: RIBA Publishing.

Yeang K (1999). The Green Skyscraper. London: Prestel.

Yin R K (2012). Applications of case study research. 3rd ed.

London: SAGE.

Pinder J A, Schmidt R, Austin S A, Gibb A, Saker J, (2017) "What is meant by adaptability in buildings?", Facilities, Vol. 35 Issue: 1/2, pp.2-20, https://doi.org/10.1108/ F-07-2015-0053

Yin R K (2014). Case study research: design and methods. 5th ed.

London: SAGE.

Remøy H, Jong P de, Schenk W, (2011) "Adaptable office buildings", Property Management, Vol. 29 Issue: 5, pp.443-453, https://doi.org/10.1108/02637471111178128 Ross B, Chen D, Conejobs S, Amin K (2016). Enabling adaptable buildings: Results of a preliminary expert survey. Procedia Engineering. 145 (1), 420 – 427.

Saari A, Kruus M, Hämälainen A, Kiiras J, (2007) "Flexibuild – a systematic flexibility management procedure for building projects", Facilities, Vol. 25 Issue: 3/4, pp.104-114, https:// doi.org/10.1108/02632770710729692 Schneider T, Till J (2007). Flexible Housing. Oxford: Elsevier.

Scuderi G. (2015). Adaptable Building Exoskeletons: A biomimetic model for the rehabilitation of social housing. Archnet-IJAR. 9 (1), 134-143.

45

9 APPENDIX 9.1 STRUCTURAL MODEL CALCULATIONS Loads Superimposed load Factors -

0.5 kN/m2

- Office: - Partitions: Dead Loads

4kN/m2

Floor Slab: 25 *0.250

= 6.25 kN/m2

Slab Number

1 2 3 4

0.25 0.25 0.25 0.25

13 13 13 13

27 27 27 27

-

1kN/m2

=4.0kN/m2),

Two-Way Spanning Slab, Office Floor (qk partitions (qk =1.0kN/m2) - Span = 7.2m - Imposed Load, qk = 5kN/m2 - Table 2.17: Span-to-depth ratios for two-way spanning slabs Slab Sizing: ds =7200 ÷ 32 Assume ds: Vc: 0.250*7.2*7.2

Vol (m^3)

Total Vol (m^3) 351.0 351.0 351.0 351.0

Labour Cost (£) 6,973.0 6,973.0 6,973.0 6,973.0

Beam Sizing:

Floor Slabs

-

Thickness( m)

Table Showing Slab Design for Each Module Unit

Floor Finishes: Imposed Load Factors

-

Module

db =7200 ÷ 15 Assume db: Assume bb: Vc: 0.5*0.3*7.2

= 480mm = 500mm = 300mm = 1.08m3

Modu le

d (m)

w (m)

Length (m)

Vol (m^3)

Total Vol (m^3) 77.8

Labour Cost (£)

1.08

Beam Numb er 72

1

0.5

0.3

7.2

2

0.5

0.3

7.2

1.08

72

77.8

2,137.5

3

0.5

4

0.5

0.3

7.2

1.08

72

77.8

2,137.5

0.3

7.2

1.08

72

77.8

2,137.5

Table Showing Beam Design for Each Module Unit

= 225mm = 250mm = 13.0m3

46

2,137.5

3. bxh: Ac: As: Vc: 0.53*0.53*10.8 4. bxh: Ac: As: Vc: 0.6*0.6*10.8

Columns Design Loads fd = 1.35*gk + 1.5*qk - gk : 6.25+ 0.5 - qk: 1.0 + 4.0 fd : 1.35*6.75 + 1.5*5.0

= 6.75kN/m2 = 5.0kN/m2 = 12.6kN/m2

530x530mm 280900mm2 5618mm2 =3.0m3 600x600mm 360000mm2 7200mm2 =3.9m3

Column Loads Ned = Af * fd*ns - Af: 7.2*7.2 Module:

= 51.8m2

1. Ned: 51.8*12.6*3 2. Ned: 51.8*12.6*6 3. Ned: 51.8*12.6*9 4. Ned: 51.8*12.6*12 Column Sizing

= 1958kN = 3916kN = 5874kN = 7832kN

Modu le

b (m)

w (m)

Height (m)

Vol (m^3)

Total Vol (m^3)

Labour Cost (£)

1.1

Colu mn Numb er 16.0

1

0.32

0.32

10.8

17.7

486.4

2

0.44

0.44

10.8

2.1

16.0

33.5

919.6

3

0.53

4

0.6

0.53

10.8

3.0

16.0

48.5

1,334.3

0.6

10.8

3.9

16.0

62.2

1,710.0

Table Showing Column Design for Each Module Unit - Assume 2% Reinforcement - (Table 2.23: Initial sizing for square columns) Module: 1. bxh: Ac: As: Vc: 0.32*0.32*10.8 2. bxh: Ac: As: Vc: 0.44*0.44*10.8

320x320mm 102400mm2 2048mm2 =1.1m3 440x440mm 193600mm2 3872mm2 =2.1m3 47

2. Cover: dpilecap: 3*500 Lpilecap: 5*500+2*150 Vc: 1.5*3.1*3.1 3. Cover: dpilecap: 3*600 Lpilecap: 5*600+2*150 Vc: 1.8*3.6*3.6 4. Cover: dpilecap: 3*750 Lpilecap: 5*750+2*150 Vc: 2.25*4.33*4.33

Pile Foundation and Pile Cap Column Pile Sizing: Assume soil/rock resists pile loads CBDSM tables 3.49 Module: 1. Fd: 2048kN Pile load: 2048/4 =512kN Try 4 * 0.3m CFA Piles @ 30m depth Vc/column: 4*0.152*đ?œ‹*30 =8.5m3 2. Fd: 3916kN Pile load: 3916/4 =979kN Try 4 * 0.5m CFA Piles @ 30m depth Vc/column: 4*0.252*đ?œ‹*30 =23.6m3 3. Fd: 5874kN Pile load: 5874/4 =1469kN Try 4 * 0.6m CFA Piles @ 30m depth Vc/column: 4*0.32*đ?œ‹*30 =33.9m3 4. Fd: 7832kN Pile load: 7832/4 =1958kN Try 4 * 0.75m CFA Piles @ 30m depth Vc/column: 4*0.3752*đ?œ‹*30 =53.0m3 Pile Cap Sizing

D (m)

Hieght (m)

Pile Vol (m^3)

1

0.3

30

8.5

2

0.5

30

3

0.6

4

0.75

Cap Vol (m^3)

Total Vol (m^3)

Labour Cost (ÂŁ)

4.0

Colu mn Numb er 16.0

199.7

3967.6

23.6

14.4

16.0

607.4

30

33.9

23.3

16.0

915.7

30

53.0

42.2

16.0

1523.4

12066.

4 18190.

6 30264.

5

Table Showing Pile Foundation Design for Each Module Unit

Module: 1. Cover: dpilecap: 3*300 Lpilecap: 5*300+2*150 Vc: 0.9*2.1*2.1

Modu le

=150mm =1500mm =3100mm =14.4m3 =150mm =1800mm =3600mm =23.3m3 =150mm =2250mm =4330mm =42.2m3

=150mm =900mm =2100mm =4.0m3 48

dav: h: dav+.025+.075 Vc: 9*7.22*1.04 3. U: (b0)(dav)(θ)(0.34)( √fc): =(4*0.53+4* dav)(dav)(1.40) =(2.12dav +4* dav2)(1.40) Quadratic solved for dav: 0=4dav2+ 2.12dav- (3.916/1.4) dav: h: dav+.025+.075 Vc: 9*7.22*1.26 4. U: (b0)(dav)(θ)(0.34)( √fc): =(4*0.6+4* dav)(dav)(1.40) =(2.4dav +4* dav2)(1.40) Quadratic solved for dav: 0=4dav2+ 2.4dav- (7.832/1.4) dav: h: dav+.025+.075 Vc: 9*7.22*1.45

Raft Foundation Raft Sizing Raft thickness determined from imposed diagonal tension shear.

(ACI-05 11.12.2.1.c) U=(b0)(dav)(θ)(0.34)( √fc) Where, U= factored column load Θ= Reduction factor (0.75) b0= Control Perimeter (4*b+4* dav) dav= Effective depth of raft fc= Concrete Strength (30N/mm^2) Assume soil/rock resists raft loading loads Module: 1. U: (b0)(dav)(θ)(0.34)( √fc): =(4*0.32+4* dav)(dav)(1.40) =(1.28dav +4* dav2)(1.40) Quadratic solved for dav: 0=4 dav2+1.28 dav -(2.048/1.4) dav: h: dav+.025+.075 Vc: 9*7.22*0.43 2. U: (b0)(dav)(θ)(0.34)( √fc): =(4*0.44+4* dav)(dav)(1.40) =(1.56dav +4* dav2)(1.40) Quadratic solved for dav: 0=4 dav2+1.56 dav -(3.916/1.4)

2.048MN

0.33m 0.43m =200.6m3 3.916MN

0.94m 1.04m =485.2m3 5.874MN

1.16m 1.26m =587.9m3 7.832MN

1.35m 1.45m =676.5m3

Modul e

Ned (kN)

dav (mm)

Area (m^)

h (m)

Labour Cost (£)

0.4

Conc Volume (m^3) 200.6

1

1958

0.33

466.6

2

3916

0.94

466.6

1.0

485.2

9639.4

3

5874

1.16

466.6

1.3

587.9

11678.5

4

7832

1.35

466.6

1.5

676.5

13439.6

3985.5

Table Showing Raft Foundation Design for Each Module Unit 49

Shear Walls Shear Wall Sizing Module: 1. bshearwall: 10.8/7 Assume: tshearwall: Vc: 2*1.8*0.3*10.8 2. bshearwall: 21.6/7 Assume: tshearwall: Vc: 2*3.6*0.3*10.8 3. bshearwall: 32.4/7 Assume: tshearwall: Vc: 2*5.4*0.3*10.8 4. bshearwall: 43.2/7 Assume: tshearwall: Vc: 2*7.2*0.3*10.8

=1.54m 1.8m 300mm =11.7m3 =3.1m 3.6m 300mm =23.3m3 =4.7m 5.4m 300mm =35.0m3 =6.17m 7.2m 300mm =46.7m3

-

= 506.3m2 250mm =45m 1000mm 7200mm 77.8m2

-

Afloor: 22.5*22.5 dslab : Cladperimeter: 2 * 22.5 tshearwall : wshearwall : Awall/floor : 3.6*7.2*3

Module

b (m)

t (m)

Height (m)

Labour Cost (£)

10.8

Total Volume (m^3) 11.7

1

1.8

0.3

2

3.6

0.3

10.8

23.3

495.8

3

5.4

0.3

10.8

35.0

743.6

4

7.2

0.3

10.8

46.7

991.5

Table Showing Shear Wall Design for Each Module Unit

50

247.9

Component

Total Module

Module 1

Module Volume (m^3) 458.1

Foundation Volume (m^3) 200.6

Base Module Volume (m^3) 658.7

2

485.5

485.2

970.8

3

512.3

587.9

1100.2

4

537.6

676.5

1214.1

(1-2)

27.4

284.6

312.0

(2-3)

26.7

102.6

129.4

(3-4)

25.3

88.6

114.0

Slab/ Foundatio n Column/ Beam Shear Wall

Market Data

Concrete Steel Rebar 2% Reinforce d Concrete

Workme n Hours/ m^3 Steel

Labour Cost/ m^3 Steel

New Build Labour Cost/ m^3 reinforced conc

8.6

66.2

993.3

19.9

Conversion Labour Cost/ m^3 reinforced conc 26.5

11.9

91.6

1,374.5

27.5

36.7

9.2

70.8

1,062.6

21.3

28.3

Table Showing Salary Data for Construction Labour

Table Showing Design for Each Module Unit

Material

Workme n Hours/ Tonne Steel

New Build Cost (ÂŁ per m^3) 100

Conversion Cost (ÂŁ per m^3) 150

Embodied E (MJ per m^3)

CO2 (Kg per m^3)

50

3.75

5000

7500

293000

7700

198

297

5909

157.675

Table Showing Market and Production Data for Structural Materials

51

Density Demand Rises by Factor of 4 128.6

128.6

140000 120000

120.0

96.5

Cost ~(£)

Dwellings per Hecter

140.0

Cost per Dwelling

100.0 80.0

64.3

60.0 40.0

32.2

100000 80000 60000 40000 20000 0

20.0

0

30

0.0 0

30

60

90

120 G Cost (£)/Dwelling

Time Period (years)

90

120

C Cost (£)/Dwelling

O Cost (£)/Dwelling

Cost per m^2

4. Growth vs Optimum Cumalative Cost 1,600,000 1,400,000 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0

300 250

Cost ~(£)

Cumalative Cost (£)

60

Time Period (years)

200 150 100 50

0

30

60

90

0

120

0

C Cost (£)

60

90

Time Period (years)

Time Period (years) G Cost (£)

30

O Cost (£)

G Cost (£)/ m^2

52

C Cost (£)/m^2

O Cost (£)/m^2

120

Density Demand Rises by Factor of 3

Cost per Dwelling 120,000

96.5

100.0 80.0

96.5

100,000

Cost ~(£)

Dwellings per Hecter

120.0

64.3

60.0 32.2

40.0

80,000 60,000 40,000 20,000

20.0

0 0

0.0 0

40

80

80

120

Time Period (years)

120 G Cost (£)/Dwelling

Time Period (years)

3. Growth vs Optimum Cumalative Cost

C Cost (£)/Dwelling

O Cost (£)/Dwelling

Cost per m^2

1,000,000

250

800,000

200

Cost ~(£)

Cumalative Cost (£)

40

600,000 400,000 200,000

150 100 50

0 0

40

80

0

120

0

40

80

120

Time Period (years) Time Period (years) G Cost (£)

C Cost (£)

O Cost (£)

G Cost (£)/ m^2

53

C Cost (£)/m^2

O Cost (£)/m^2

Density Demand Rises by Factor of 2 64.3

64.3

60.0 50.0 40.0

Cost ~(£)

Dwellings per Hecter

70.0

Cost per Dwelling

32.2

30.0 20.0 10.0

90000 80000 70000 60000 50000 40000 30000 20000 10000 0 0

0.0 0

60

G Cost (£)/Dwelling

C Cost (£)

O Cost (£)/Dwelling

120

180 160 140 120 100 80 60 40 20 0 0

Time Period (years) G Cost (£)

C Cost (£)/Dwelling

Cost per m^2

500,000 450,000 400,000 350,000 300,000 250,000 200,000 150,000 100,000 50,000 0

Cost ~(£)

Cumalative Cost(£)

2. Growth vs Optimum Cumalative Cost

60

120

Time Period (years)

120

Time Period (years)

0

60

60

120

Time Period (years)

O Cost (£)

G Cost (£)/ m^2

54

C Cost (£)/m^2

O Cost (£)/m^2