Resources, Conservation and Recycling 105 (2015) 167–176
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Resources, Conservation and Recycling
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ull length article
aste minimisation through deconstruction: A BIM basedeconstructability Assessment Score (BIM-DAS)
lugbenga O. Akinadea, Lukumon O. Oyedelea,∗, Muhammad Bilal a, Saheed O. Ajayia,akeem A. Owolabia, Hafiz A. Alakaa, Sururah A. Bellob
Bristol Enterprise, Research and Innovation Centre (BERIC), University of West of the England, Bristol, United KingdomDepartment of Computer Science and Engineering, Faculty of Technology, Obafemi Awolowo University, Ile-Ife, Nigeria
r t i c l e i n f o
rticle history:eceived 22 July 2015eceived in revised form 11 October 2015ccepted 19 October 2015vailable online 14 November 2015
eywords:uilding information modellinguilding deconstruction
a b s t r a c t
The overall aim of this study is to develop a Building Information Modelling based DeconstructabilityAssessment Score (BIM-DAS) for determining the extent to which a building could be deconstructedright from the design stage. To achieve this, a review of extant literature was carried out to identifycritical design principles influencing effectual building deconstruction and key features for assessingthe performance of Design for Deconstruction (DfD). Thereafter, these key features were used to developBIM-DAS using mathematical modelling approach based on efficient material requirement planning. BIM-DAS was later tested using case study design and the results show that the major contributing factorsto DfD are use of prefabricated assemblies and demountable connections. The results of the evaluation
esign for deconstructionemolition waste minimisationesign performance assessmentcoring scheme
demonstrate the practicality of BIM-DAS as an indicator to measure the deconstructability of buildingdesigns. This could provide a design requirement benchmark for effective building deconstruction. Thisresearch work will benefit all stakeholders in the construction industry especially those interested indesigning for deconstruction. The eventual incorporation of BIM-DAS into existing BIM software willprovide a basis for the comparison of deconstructability of building models during design.
. Introduction
The increasing global urbanisation has resulted in high vol-me of Construction, Demolition and Excavation Waste (CDEW)rom which demolition waste contributes up to 31.8 million met-ic tonnes yearly in the UK alone (WRAP, 2009). With so manyemolitions taking place annually, its environmental and economic
mpacts cannot be ignored because building materials becomenrecoverable and eventually sent to landfills. Tackling this prob-
em calls for a strategic approach to planning for recovery ofuilding materials and components for reuse or recycling. Thisequires dealing with the problem at source, which is usually at theesign stage by designing for deconstruction (DfD) to avoid demo-
ition after the end of life of buildings. Although literature aboundsn causes and management of CDEW, only few studies have been
onducted to mitigate the generation of end of life waste right fromhe early design stages. Even most of these few studies focus on dis-osal cost estimation (Chen et al., 2006; Cheng and Ma, 2011; Yuan
et al., 2011) and waste quantification during demolition (Cochranet al., 2007; Masudi et al., 2012; Wu et al., 2014). Considering thefact that end-of-life activities generate the largest volume of waste(DEFRA, 2012), there is need to plan for the end of buildings rightfrom the design stages.
Evidence shows that up to 50% of CDEW could be divertedfrom landfill through a well-planned deconstruction strategy(Kibert, 2008). This shows that in the UK alone, about 16 mil-lion tonnes of waste could be diverted from landfills (DEFRA,2011), while saving over £1.3 billion in terms of landfill tax andwaste transportation. Despite these opportunities accruable fromdeconstruction, research efforts on design performance assessmenthave been concentrated on buildability and construction wasteassessment. Examples of such systems include Building DesignAppraisal System—BDAS (CIDB, 1995a), Building Waste Assess-ment Score—BWAS (Ekanayake and Ofori, 2004), and ConstructionQuality Assessment System—CONQUAS (CIDB, 1995b). These per-formance assessment tools are concerned with the impact of designon construction stage but not with the end of life of buildings.
Blengini and Carlo (2010) highlighted that it is difficult tocarry out life cycle analysis towards the end of life stage duringdesign stage because information is still scanty. However, con-struction sustainability could be achieved if considerable effort is
ut in design with future benefits in mind (Ajayi et al., 2015). Inhis way, Design for Deconstruction (DfD) will increase the cost-ffectiveness of material recovery and reuse from the early designtages (Davison and Tingley, 2011). Despite the general knowl-dge that design could initiate effective building deconstructionCrowther, 2005; Guy et al., 2006) and the attempts to quantifyhe benefits of DfD, no practicable design tool has been providedo substantiate these claims. Existing design tools for deconstruc-ion have been design guides, such as ICE deconstruction protocol,hat provide no quantifiable measure similar to BDAS, BWAS, andONQUAS. Other tools such as building end of life analysis toolDorsthorst and Kowalczyk, 2002), NetWaste tool (WRAP, 2011b),esign out waste for buildings tool (WRAP, 2011a), and Sakura
Tingley, 2012) focus more on material analysis for investigatingnd of life impact of buildings.
Apart from the above limitations, increasing adoption of Build-ng Information Modelling (BIM) within Architecture, Engineeringnd Construction (AEC) industry (Arayici et al., 2011) requires aolistic rethink of entire construction activities. This means thatny promising innovation within the AEC industry requires BIMompliance (Ajayi et al., 2014). Laying on this premise, the overallim of this paper is to detail the development of BIM based Decon-tructability Assessment System (BIM-DAS) to provide an objectivend measurable system for building deconstructability during theesign stage. This scoring system forms a basis for comparativenalysis building models to choose the option with the least end ofife impact on the environment. Accordingly, the specific objectivesre:
(i) To identify critical design principles that ensures buildingdeconstructability.
(ii) To develop an objective system, i.e. BIM-DAS, for scoring thedegree of building deconstructability.
iii) To test the performance and usability of BIM-DAS.
While adopting a positivist theoretical framework, this studyses experimental research and case study as research method-logy to achieve its objectives. As such, an in-depth review ofiterature was carried out to identify key features that could besed for assessing the performance of DfD. Thereafter, the key fea-ures were used to develop BIM-DAS using mathematical modellingpproach, which is based on efficient material requirement plan-ing. At the end, BIM-DAS was tested using case study design.
The research paper starts with a discussion of the concept ofesign for deconstruction, key design principles influencing decon-truction, and the role of BIM in achieving effectual deconstruction.fter this, a full discussion of the research methodology precedediscussion of how BIM-DAS was developed. A discussion on thevaluation of BIM-DAS through a case study design is then pre-ented before culminating the paper ends with a conclusion andreas of further research.
. Design for deconstruction as a means to an end
Deconstruction is “the whole or partial disassembly of build-ngs to facilitate component reuse and material recycling” (Kibert,008) to eliminate demolition through the recovery of reusableaterials (Gorgolewski, 2006). This is with the aim of rapid relo-
ation of building, reduced demolition waste, improved flexibilitynd retrofitting, etc. (Addis, 2008). Despite a growing discrepancyf opinion on whether CDEW could be completely eradicated (cf.
uan and Shen, 2011; Zaman and Lehmann, 2013), existing stud-
es shows that effective deconstruction could drive constructionaste eradication initiatives (Guy et al., 2006; Densley Tingley
nd Davison, 2012; Akbarnezhad et al., 2014). Example of such
n and Recycling 105 (2015) 167–176
initiative is the EU target of zero waste to landfill by 2020 (Phillipset al., 2011). Apart from helping to divert waste from landfills,deconstruction also enables other benefits, which include: (a) envi-ronmental benefits: by reducing site disturbance (Lassandro, 2003),harmful emission, health hazard (Chini and Acquaye, 2001) andpreserving the embodied energy (Thormark, 2001) through mate-rial reuse; (b) social and economic benefits: by providing businessopportunities through material recovery, reuse and recycling; andproviding employment to support deconstruction infrastructure.
To enable a well-planned deconstruction, conscious effortsmust be taken by architects and engineers right from the designstages. (Kibert, 2008). As such, the eventual purpose of decon-struction must be identified to guarantee the success of DfD. Thiswill enhance the understanding of relevant design strategies andtools required for deconstruction. This section therefore containsa review of extant literature on types of deconstruction, DfD tech-niques, theory of building layers and BIM as a tool for DfD.
2.1. Types of deconstruction
Two activities are possible at the end of life of buildings, whichinclude demolition and deconstruction as shown in Fig. 1. Demo-lition as a building removal strategy is primarily aimed at disposalto landfill with little consideration for material recovery. On theother hand, deconstruction is carried out to recover toxic materialsfrom buildings for safe disposal or to divert waste from landfillsthrough material recovery. For example, harmful substances suchas asbestos needs to be safely removed through careful deconstruc-tion from old buildings to avoid occupational exposure (Frost et al.,2008). According to Crowther (2005), deconstruction of buildingswithout toxic materials could be for four main purposes, whichinclude (i) relocation of buildings, (ii) component reuse in otherbuildings, (iii) material reprocessing and (iv) material recycling.This is inline with the viewpoint of Kibert (2003) who suggests thatrealisation of effective DfD for multiple purposes will significantlyreduce CDEW and helps to divert waste from landfills.
Deconstruction for building relocation involves the recovery ofall the building materials and components without generation ofwaste. This is only possible if all the building materials and com-ponents are separable and reusable (Crowther, 2005). Although itis impractical to achieve 100% material recovery, McDonough andBraungart (2002) argued that recovery of building components forrelocation and reuse remains the most preferred deconstructionpurpose because it requires the least energy and new resources(Oyedele et al., 2014). This is because other purposes of deconstruc-tion require additional energy and materials to reprocess or recyclerecovered materials (Jaillon and Poon, 2014). The term DfD used inthis study therefore encapsulates design for the purpose of recoveryfor building relocation and component reuse. This takes a cue fromthe fact that it is becoming a common practice to recycle an entirebuilding and that a more significant challenge is designing a build-ing that could be deconstructed for component reuse with minimalreprocessing. This task therefore necessitates the requirement tounderstand the complexity of intertwined processes of buildingdesign practice, DfD techniques and associated factors. As such,next section takes a holistic approach in discussing existing per-spectives on DfD principles and how interplay among them couldensure successful building deconstruction.
2.2. Design for deconstruction techniques
According to Warszawski (1999), there are various design rules
that should be followed in order to enhance deconstructability ofbuildings. These rules help to maximise the flexibility of designs,thereby enhancing building re-modification and disassembly. Guyet al. (2006) argues that designing for deconstruction requires an
O.O. Akinade et al. / Resources, Conservation and Recycling 105 (2015) 167–176 169
Fig. 1. Types and purpose of
ibtiuabTla
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presented in Table 1.
Fig. 2. Building layers. Adapted from Brand (1994).
n-depth conceptual and theoretical exploration of the make-up ofuilding systems using both holistic and systemic approach. This iso capture the complexity and multiplicity of the makeup of build-ngs as well as interactions among building elements. This ideanderscores the theory of building layers where parts of buildingsre organised into subsystems known as layers. The layers structureuilding elements according to their life expectancy (Habraken andeicher, 2000). Accordingly, Brand (1994) highlighted six buildingayer which are site, structure, skin, services, space plan and stuffs shown in Fig. 2.
The theory of building layer is important to keep building sub-ystems as independent as possible so that components on higherayers could be altered or replaced without affecting lower layers.ccording to Habraken and Teicher (2000), building layers makesfD technically possible because layers’ interfaces become points
f deconstruction. This has led researchers to produce design prin-iples needed for ensuring end of life deconstruction. For example,uy et al. (2006) and Crowther (2005) produced a comprehensive
buildings’ end of life.
list of general design concepts and principles for deconstruction.These research works provide a solid foundation for contemporaryDfD process and are majorly driven by efficient building elementsselection to facilitate easy disassembly (Addis, 2008).
The highlight of building elements selection process include:(i) the specification of durable materials (Tingley, 2012); (ii)using materials with no secondary finishes (Guy and Ciarimboli,2008); (iii) using bolt/nuts joints instead of gluing (Chini andBalachandran, 2002; Webster and Costello, 2005); (iv) avoidingtoxic materials (Guy et al., 2006); and (v) using prefabricatedassemblies (Jaillon et al., 2009). In addition to these, Guy et al.(2006) noted that the types and numbers of building materials,components and connectors must be minimised to simplify dis-assembly and sorting process. The use of recycled and reusedmaterials is also encouraged (Hobbs and Hurley, 2001; Crowther,2005) during design specification to broaden existing supply-demand chain for future deconstructed products. Evidence showsthat reusing concrete components could reduce material cost by56% (Charlson, 2008). These requirements place huge responsibil-ities on architects and engineers at ensuring that design has theleast impact on the ecosystem throughout the building’s lifecycle(Yeang, 1995). Though selecting appropriate building elements thatfacilitate deconstruction may increase the project cost, architectsand engineers must ensure that the cost of DfD does not exceedthe cost of recoverable materials minus the actual cost of disposal(Billatos and Basaly, 1997), i.e.:
(Cost of DfD) < (Value of Recovered Materials)
− (Cost of Disposal) (1)
Meanwhile, DfD principles go beyond building element selec-tion (Crowther, 2005) since other studies have shown that materialhandling (Couto and Couto, 2010), building design methodology(Latham, 1994), and design documentation (Andi and Minato,2003) are all part of DfD principles. This study however is limitedto key DfD principles required in building elements selection as
Focusing on the studies presented in Table 1, through whichthe consciousness of deconstruction is stimulated during mate-rial specification, opens up a genuine foundational requirement for
170 O.O. Akinade et al. / Resources, Conservatio
Table 1Material selection design for deconstruction principles.
No Design principle Reference
1. Use reusable materials Webster and Costello (2005), Guyet al. (2006)
2. Use nut/bolt joints insteadof nails and gluing
Crowther (2005), Webster andCostello (2005), Guy et al. (2006)
Crowther (2005), Webster andCostello (2005), Guy et al. (2006),Guy and Ciarimboli (2008)
5. Minimise number ofbuilding components
Crowther (2005), Webster andCostello (2005), Guy andCiarimboli (2008)
6. Minimise types of buildingcomponents
Chini and Balachandran (2002),Crowther (2005), Webster andCostello (2005), Guy et al. (2006),Guy and Ciarimboli (2008)
7. Avoid toxic and hazardousmaterials
Crowther (2005), Guy et al. (2006)
8. Use of recyclable materials Chini and Bruening (2003),Crowther (2005), Guy et al. (2006)
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4. BIM-DAS model development
This section presents the general characteristics of the math-ematical model developed for assessing the performance of DfD.
Table 2Design characteristics of case study.
Building type: residentialNumber of floors: 3Ground floor area: 492 m2
First floor ground floor area: 351 m2
9. Avoid materials withsecondary finishes
Crowther (2005), Guy andCiarimboli (2008)
fD. Nevertheless, these studies have their challenges. First, the setf studies only offers a conceptual framework by providing factorshat must be considered during design (Tingley, 2012). As such,he studies fail to provide a methodological framework neededo understand how to implement the design principles. Anotherhallenge is that none of the studies provides an objective mea-ure of performance for the principles. These limitations thereforeeveal the need to take a holistic approach to investigating the DfDrinciples empirically and develop a framework for integrating DfDerformance measure into BIM.
.3. Roles of BIM in design for deconstruction
BIM, as Integrated Product Delivery (IPD) approach, enablesffective communication and collaboration among stakeholders.his facilitates transparent access to shared information, controlledoordination and monitoring of construction processes (Grilo andardim-Goncalves, 2010). These capabilities encourage the involve-
ent of all stakeholders’ right from the conception of the buildingroject through the entire lifecycle (Eastman et al., 2011) and allowartners across various disciplines to collaborate effectively onuilding projects. According to Eadie et al. (2013), a distinguishingeature that makes BIM applicable to all work stages is the accu-
ulation of building lifecycle information. As such, information onuilding requirements, planning, design, construction and opera-ions related information can be accumulated and accessed at thend of life of buildings.
Another functionality of BIM that aids its wide acceptability ishe ability to simulate building performances such as cost esti-
ation, energy consumption, lighting analysis, etc. According toastman et al. (2011), building performance analysis provides alatform for functional evaluation of building models before theommencement of construction. This allows comparison of designptions to identify potential design errors and to select the mostost-effective and sustainable solution. Despite the benefits ofuilding performance analysis and the environmental/economic
mpacts of end of life waste, none of the existing BIM software hasapabilities for end of life waste performance analysis. This gap
alls for a rethink of BIM functionalities towards capacity for endf life waste analysis and simulation right from early design stages.his will help to capture and address end of life concerns at a stagehere design changes are cheaper.
n and Recycling 105 (2015) 167–176
3. Research methodology
After a review of extant literature, it became clear that a method-ology that drives objectivity is needed for developing a frameworkto realise BIM-DAS. This reveals the need for systemic operational-isation of practices in driving genuine understanding of actions(Gray, 2009). According to Creswell (2014), a study that requiressuch degree of objectivity in driving an acceptable consensus neces-sitates a positivist worldview. This therefore positions the studywithin an objectivist epistemology where a single “real reality”exists (Crotty, 1998). This perspective helps to operationalise con-cepts into measurable entities (Guba and Lincoln, 1994). In linewith positivism, the paper adopts review of literature, mathemat-ical modelling and case study design as research methods. After athorough review of extant literature, key principles for DfD wereidentified and developed into a framework. This framework wasthen used to develop BIM-DAS using mathematical modelling tech-niques. After this, BIM-DAS was tested using case study approachto demonstrate its capabilities and to evaluate its overall perfor-mance.
In deciding the degree of deconstructability of design, architectsand engineers must adopt an automated, but objective, approachwith general acceptability. To accomplish this, design principlesfor deconstruction must be conceptualised, mathematically cap-tured and developed into a model. This will reduce effort andtime required for analysis as well as eliminating human errors.As such, the BIM-DAS model development follows the processesof problem description, formulation of a mathematical modelling,obtaining mathematical solutions to model, simulation with themodel and interpretation of the results. This approach helps to char-acterise building materials and their properties such that given aBIM design, the mathematical model could assess its DfD perfor-mance by assigning a BIM-DAS score to the design. To evaluateBIM-DAS, this study adopts a case study approach using a com-parative analysis of design typologies to evaluate the performanceof BIM-DAS. As such, three case studies of a two-storey residen-tial building located in the UK were developed with a ground floorarea of 492 m2. The floor plan of the case study is shown in Fig. 3and the design characteristics are presented in Table 2. While it isgenerally believed that residential buildings have long serviceablelife, houses built to be deconstructed are becoming more popularto aid future metropolitan planning and relocation (Kibert, 2008).Examples of deconstructable residential buildings include block offlats and condominiums in city centres (Budge, 2013).
Using the design characteristics shown in Table 2, three casestudies were designed with three different major material types,i.e., steel, timber and concrete. This approach was used to assess andcompare the building deconstructability score of the three buildingtypes. The aim of the comparative evaluation is to ascertain whichof the building types has greater deconstructability potential.
O.O. Akinade et al. / Resources, Conservation and Recycling 105 (2015) 167–176 171
Fig. 3. Floor plan of case stu
Table 3Notations and descriptions of variables.
Notation Description
M Set of materials, i.e., M = {M1, M2, . . ., Mn}C Set of components, i.e., C = {C1, C2, . . ., Cn}E Set of connector, i.e., E = {E1 , E2, . . ., En}r1 Is true if specimen is reusabler2 Is true if specimen is recyclableP Is true if specimen is prefabricatedc Connection type; c = {cf , cb , cn , cd}*
n Total number of speciment Material type of specimen; t = {steel, concrete, timber, etc,}x Is true if specimen is toxics Is true if material has secondary finishesv Volume of specimen (mm3)ϕ Spatial position and orientation of specimenp Position of specimen in 3D spacer Rotation of specimen in 3D space
he variables used in the development of the model are presentedn Table 3. Although building parametric models are composed of–D spatial distribution of materials and components, however, the
ocus of the model development is to employ elemental breakdownf material take-off. First, a formal definition of design model foreconstruction based on material specification is presented. Thiselps to identify independent variables contributing to BIM-DAS.econd, deconstruction related variables are incorporated in BIMesign models using Revit software. Lastly, BIM-DAS was developednd evaluated.
.1. Design model for deconstruction (DMD)
Given a 3D building model with a well-defined bill of quantity
f materials (M), components (C) and connectors (E), then a Designodel for Deconstruction (DMD) can be formally defined as three
3) tuple:
MD =⟨
M, C, E⟩
(2)
dy (Source: author).
This definition is restricted to the four main assumptions:
(1) All specimen, i.e., S = (M ∪ C ∪ E) are represented within thebuilding model using a spatial function ϕ that determines theposition p and rotation r of such specimen, i.e.,
M ∪ C ∪ E ={
S|S ∈ M or S ∈ C or S ∈ E}
(3)
ϕ : S ∈ (M ∪ C ∪ E) × (p, r) (4)
(2) A set of specimen Scannot be empty, i.e: S /= ∅(3) A set of specimen S must be composed of tangible object and
properties of all specimen Si ∈ S must be identifiable:
∀Si ∈ S [tangible (Si)] (5)
(4) The boundary of all specimen Si ∈ (M ∪ C ∪ E) must not empty,i.e., a specimen Si cannot be self-interacting. As such, Si must beconnected to one or more specimen Sj ∈ S.
Based on these assumptions and the set of variables defined inTable 3, we can define the properties of a specimen Si using an eight(8) tuple:
Si =⟨
r1, r2, c, P, n, t, x, s⟩
(6)
Eq. (6) identifies specimen Si as an object with a fixed set ofproperties that uniquely describes Si. To facilitate easy access ofrelevant properties of specimen Si, the study adopts an object-oriented notation. For example, the connection type of Si could beassessed using the notation Sic and the type of Si will be Sit. Havingprovided the formal definition of a design model for deconstruc-tion and described the properties of each element, a BIM basedapproach was used to incorporate all the deconstruction relatedparameters into the building model. This is to enable the automatedcomputation of DAS. The process for achieving this is detailed in thefollowing section.
4.2. BIM-based deconstructability assessment system
An important factor that makes BIM relevant in buildingdesign is its ability to capture object parameters automatically for
172 O.O. Akinade et al. / Resources, Conservation and Recycling 105 (2015) 167–176
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of significance of the constituents of DAS. In this study, the same
Fig. 4. Custom parameters in Revit.
imulating building performances. To leverage upon this, currentIM parametric modelling software allows user-specific objectarameters to extend built-in parameters. Accordingly, customarameters were created to capture various aspects of buildingeconstructability. This includes recyclability attributes, reusabil-
ty attributes, expected life of specimen, toxicity of specimen,ssemblage attribute, finishing on specimen and Joint/connectorttributes. Fig. 4 shows a specimen property tab showing the cus-om parameters.
During a deconstruction process, the total End of life waste (Ew),hich is the amount of building elements (measured in tonnes) that
annot be recovered, could be computed as:
w (t) = Bq − Tr + ε (7)
here Bq is the bill of quantity (t), Tr (t) is the total recoverabletems from Bq and ε is the residual. ε is included in Eq. (7) to capture
aste due to transportation, human errors and natural disaster. These of weight metrics here is because materials used on projectsnd CDEW from project site are quantified in weights. The use ofeight of elements may be biased towards heavyweight elementshereas deconstruction is more concerned with the recovery ofigh-embodied impact elements. However, since the associatedmbodied energy (MJ) of an element is directly proportional to itsass (kg), the recoverable end of life energy could be computed as
product of the embodied energy (MJ/kg) and mass. Therefore, theost energy (EE) at the end of life could be calculated from Eq. (7) as
E (MJ) = EC − ED + ε (8)
here EC is the total embodied energy and energy needed for build-ng construction, ED is the total embodied energy plus the energyeeded for building deconstruction. ε remains the residual. The aimf an effective deconstruction activity, especially for building relo-ation, is to make Ew + ε = 0 and EE + ε = 0 i.e. zero waste generationnd zero energy loss. To incline this study towards a metric thatEC practitioners can easily relate to and to simplify the process ofodel development, Eq. (7) becomes:
r = Bq (9)
Eq. (9) shows an ideal situation of a fully reusable building wherell elements with environmental burden are recovered. In realising
DAS score, the higher the score the higher the total recoverabletems with high-embodied impact, i.e.:
r˛DAS (10)
Fig. 5. Parameters for calculating DAS for subsystem.
Since Bq is constant, Tr must be maximised towards the valueof Bq in order to minimise Ew. Therefore, setting the maximumDAS score at 1.0, which reflects the highest level of building decon-structability, will make Eq. (10) to become:
Tr
Bq= DAS = 1.0 (11)
Eq. (11) shows that DAS is a percentage of total recoverablematerial (Tr) to the total quantity of material used in building.Therefore, Tr could be calculated as:
Tr = Bq × DAS (12)
Meanwhile, it is impractical to calculate DAS score for individualconstituent of a building structure because building elements arematrix of interacting objects. As such, DAS score will be calculatedfor the entire building. This is done using a sum of Deconstructabil-ity score (Dscore) and Recovery score (Rscore) as shown in Fig. 5. Dscore
determines the extent to which a building could be disassembledfor reuse or relocation while Rscore represents the ease of mate-rial recovery and reuse after end of life of the building. Althoughthere are certain issues that bothers on the concept of materialsreuse and recyclability. In particular, the area of residual perfor-mance, recertification, and legal warranties of recovered buildingelements after several years of usage (Kibert et al., 2001). For exam-ple, evidence shows that recovered elements such as wood cannotbe regraded and can only be used for low market applications andnon-structural use (Falk, 2002). With this in mind, this study isbased on the presupposition that the reusability and recyclabilityof building elements could be determined during design and thatthe value of building items is retained at the end of life. As imprac-tical as this may be, it provides a grip on achieving the objectivesof the current study.
Separating DAS score into Dscore and Rscore is because Crowther(2005) highlighted that not all principles that guarantees materialreusability or recyclability contribute towards building decon-structability. In the same way, there are principles that encouragesdeconstructability but do not guarantee that the material recoveredwill be useful. For example, specifying materials without secondarymaterials enables reusability but does not contribute to buildingdeconstructability. Using this approach, the DAS score could becomputed as a weighted sum of Dscore and Rscore, i.e.:
DAS = ˛Dscore + ˇRscore (13)
The maximum value for Dscore and Rscore is also set at 1.0. Param-eters ̨ and ̌ are the weighting function that determines the level
level of significance of 0.5 was assumed for the individual scores,i.e.:
DAS = 0.5Dscore + 0.5Rscore (14)
O.O. Akinade et al. / Resources, Conservation
Table 4Inventory of materials for design options.
Item Specific characteristics
Structural framesystem
A. Prefabricated steel with bolted connectionsB. Hardwood timber post with nailedconnectionsC. Concrete with bolted connections
Foundation system A. H-pile foundationB&C. Concrete ground beam
Wall system A. Curtain walls with bolted connectionsB. Cladded timber cavity walls filled withnailed connectionsC. Concrete wall with paint finishing
Floor system A. Gypframe steel flooring with carpetB. Timber board with I-section timber frameswith ceramic tilesC. Concrete floor with carpet
Ceiling system A. Aluminium strips on prefabricated steelframeB. Pressured-treated timber planks on timberframes free of copper chromium acetateC. Soffit plaster and paint finishing
Roof system floor A. Insulated steel plate flat roof on steel trussB. Insulated slate roofing sheet on timber trussC. Concrete roof with sand and cement screed
Window and doors A. Steel windows and doors with steel frameB. Timber windows and doors with timberframe
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To verify the accuracy of this model, Eq. (20) was validatedagainst the initial case study and the result is presented in Table 7.The nature of the residuals shows that the model performs well inpredicting the value of DAS since the residual is negligible in all
C. Double-glazed glass with aluminium frame
ote: A. is a steel structure; B. is a timber structure; and C. is a concrete structure.
Although, assuming the same weight for the two factors maye impractical as Dscore and Rscore may have varying level of signifi-ance, yet this assumption provides a reference point for computingAS score. Based on the assertion that every object in a buildingodel can be uniquely identified and described, the constituents
f DAS score for subsystems can be computed as follows:
score = tn + dc + RP
3(15)
score = R1 + R2 + Rs̄ + Rx̄
4(16)
here tn is the material type-number ratio for subsystem and it isalculated as:
n = 1.0 −(
t
n
)(17)
c is the ratio of demountable connections, i.e.,
c = Cb + Cd
Cb + Cd + Cn + Cf(18)
here RP is ratio of prefabricated elements, R1 is ratio of reusablelements, R2 is the ratio of recyclable elements, Rs̄ is ratio elementsithout secondary finishing and Rx̄ is ratio of non-toxic elements.
Eq. (14) thus becomes:
AS = 0.5tn + dc + RP
3+ 0.5
R1 + R2 + Rs̄ + Rx̄
4(19)
The mathematical model shown in Eq. (19) represents the finalquation for calculating DAS. This model will thus be used to assesshe performance of DfD using case studies.
. Model evaluation and results
This section presents the results of the evaluation of DAS using
hypothetical case study approach. This was achieved using threease studies of a building model with different material specifica-ions. The case studies include a steel structure, a timber structurend a concrete structure. The building models were developed in
and Recycling 105 (2015) 167–176 173
Revit and the inventory of materials is as shown in Table 4. Accord-ingly, a bill of quantity schedule for each model was estimated todetermine the details of the constituents of the buildings. This wasexported into a Microsoft Excel sheet to aggregate the building con-stituents for the initial analysis. DAS score for each design typologywas then calculated using the mathematical model developed.
At this point, it is important to show how values of parametersneeded for the calculation of DAS score will be derived. This wasdone using a lookup table of possible materials types for build-ing subsystems as shown in Table 5. Accordingly, DAS score ofeach building was calculated based on the design specificationsto achieve the objectives of the study. Table 6 shows the valuesof the parameters and DAS score for the three case studies. Fromthis result, the steel structure building has the highest DAS scoreof 0.935 due to very high demountable connections and prefab-ricated components. In addition, the steel structure has minimalmaterials with secondary finishing, thus contributing to the highRscore. Although the timber structure has no demountable connec-tion and lower prefabricated elements, it has a higher DAS scorethan the concrete structure. This is primarily because the timberstructure has higher recyclable and reusable potentials than con-crete structures.
To understand the resultant effect of individual factors on Dscore,Rscore and DAS, factor selection process was carried out. This wasdone by omitting certain factors in the model to see how the resultsare affected. This will help to identify key factors contributing to thecalculation of Dscore, Rscore and DAS. To achieve this, Mean SquaredError (MSE) between the actual and the new values were calcu-lated using Eq. (20). Where DAS is the actual value and D̂AS is thecalculated value.
MSE =n∑
i=1
(D̂AS − DAS
)2(20)
The result of the factor selection shows that ratio prefabricatedelements (Rp) and ratio of demountable (dc) have the highest sig-nificance as shown in Fig. 6 since removing ‘Rp’ and ‘dc’ results ina high MSE value of 0.13353 and 0.1145, respectively. This thusshows that removing ‘Rp’ and ‘dc’ from the model will considerablyaffect the value of DAS. After this, a simple logistic regression analy-sis was carried out to obtain an equation such that DAS = f
(Rp, dc
).
This yield a mathematical representation of statistical correla-tion between DAS and ratio of prefabricated element and ratio ofdemountable connections given as:
DAS = 0.43 +(
0.605 × Rp
)+ (0.18 × dc) (21)
Fig. 6. Mean squared error from factor analysis.
174 O.O. Akinade et al. / Resources, Conservation and Recycling 105 (2015) 167–176
Table 5Material options for building system.
Systems and options Recyclable (r1) Reusable (r2) Toxic (x) Sec. finish (s) Connection type
1. Structural frame systemSteel with fixed connections
√ √ × × cf
Steel with bolted connections√ √ × × cb
Timber with steel dowels connections√ √ × × cd
Timber with bolted connections√ √ × × cb
Timber with nailed connections√ √ × × cn
Concrete with fixed connections√ × × √
cf
Concrete with bolted connections√ √ × √
cb
2. Structural FoundationsH-Pile foundation
√ √ × × cb
Concrete ground beam√ × × × cf
3. Wall systemDemountable dry internal wall
√ √ × √cb
Curtain wall√ √ × × cb
Brick/block cavity wall√ × × √
cb
Cladded timber cavity wall√ × × √
cn
Steel framed wall√ √ × × cb
Concrete wall with paint finish√ × × √
cf
4. Floor systemConcrete floor with ceramic tiles
√ × × × cf
Concrete floor with carpet√ × × × cf
Timber floor with carpet√ √ × × cn
Timber floor with ceramic tiles√ √ × × cn
5. Ceiling systemGypsum ceiling with steel frame
√ × × √cf
Aluminium strips with steel frame√ √ × × cf
Soffit plaster and paint × × × √cf
Timber planks with timber frame√ √ × √
cn
Ceiling tiles with metal frame√ √ × × cf
6. Roof systemTiled roof on timber beam
√ √ × × cn
Metal panel on steel truss√ √ × × cb
Metal panel on timber truss√ √ × × cf
Slate roofing sheet on timber truss√√ √ × × cn
Concrete roof with sand/cement screed√ × × √
cf
7. Doors and windowsGlass with aluminium frame
√ √ × × cf
Timber with timber frame√ √ × √
cn
Steel with steel frame√ √ × × cb
Table 6DAS score for case studies.
Case study t n tn dc Rp r1 r2 x s Dscore Rscore DAS
ases. The nature of the residuals shows that it is possible to pre-ict DAS with minimal error using two parameters instead of the
nitial set of nine parameters. This result clearly demonstrates thathere exists a strong linear and positive relationship among the DASredicted by the model, ‘P’ and ‘dc’.
. Discussion
Using the approach discussed in this paper, BIM-DAS score of
esign models could be calculated to assist designers in mak-
ng appropriate decisions and compare alternative designs. Thiss towards the delivery of the most sustainable design in termsf building deconstruction. Accordingly, the study shows that the
use of prefabricated assemblies and demountable connections areessential factors that ensure building deconstructability. These twofactors signify several implications for the AEC industry in additionto confirming best practices. First, the use of prefabricated assem-blies helps to reduce on-site waste and material use. Evidenceshows that 84.7% of on-site construction waste could be avoidedby adopting prefabrication. In addition, Jaillon and Poon (2014)highlight other benefits of prefabrication in ensuring design fordeconstruction. These include improved quality control, improvedon-site environment, improved health and safety, and improvedease of construction. Although it is true that the use of prefabrica-tion is limited by the initial high cost (Hsieh, 1997), however, it mustalso be recognised that the benefits outweighs the cost (Baldwinet al., 2008). Several studies (Baldwin et al., 2008; Tam et al., 2005;Lu and Yuan, 2013) have shown that the use of prefabricated ele-ments, such as prefabricated concrete, reduces CDEW. Accordingto Jaillon et al. (2009), the use of precast construction could result
in 52% reduction in CDEW.
Second, the use of demountable connections ensures decon-struction by allowing building subsystems to be easily discon-nected from each other without damage. Based on this, the use
rvation
objicubebtnsr
esuamcbtbrcs2aIrcc2
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7
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O.O. Akinade et al. / Resources, Conse
f mechanical joints (such as bolts and nuts and dowels) shoulde encouraged instead of chemical joints (adhesives) and fixed
oints (welding and riveting) (Crowther, 2005). Using mechan-cal joints allows the recovery of building elements in primeonditions for reuse. Akbarnezhad et al. (2014) highlighted thatsing mechanical connections engenders environmental sustaina-ility through waste minimisation, resource usage reduction andmbodied energy preservation. Embodied energy is preservedecause demountable connections allow material reuse ratherhan recycling or remanufacture. Accordingly, demountable con-ections should be encouraged in building elements such astructural frames and beams, curtain walls, internal walls, ceilings,oofs etc.
While Gorgolewski (2006) claims that bolted connections areasily achievable in steel structures, it is also possible in othertructures such as timber and concrete. In steel structures, these of demountable H-pile foundation, bolted structural framesnd beams, and bolted curtain walls should be particularly pro-oted to enable prefabrication and easier deconstruction. In the
ase of timber structures, not only the use of prefabricated assem-lies and demountable connections must be considered, but alsohe durability of the wood. This is to enable the reusability of tim-er components because wood has more value in reuse than inecycling. On the other hand, evidence shows that reinforced con-rete structures are not suitable for deconstruction because thetructures are difficult to take apart without any damage (Tingley,012). This makes reuse of concrete structures generally difficultnd inflexible (Davison and Tingley, 2011) but readily recyclable.n this way, recycling concrete elements should be prioritised overeuse. Reinforcement steel must therefore be separated from theoncrete so that it could be recycled and the concrete could berushed and used as a roadbed or as aggregates (Nakajima et al.,005).
Moreover, the use of prefabrication and demountable connec-ions must be considered right from the design brief stage. This iso allow ample time for making right decision in achieving designor deconstruction. As such, BIM-DAS must be fully integratedith existing BIM design software to provide adequate support
n decision-making. Integrating BIM-DAS into BIM software willavour automatic capture of design parameter for building decon-truction analysis to eliminate errors caused by manually enteringesign parameters. In addition, integrating BIM-DAS with BIM soft-are will leverage on current BIM capabilities such as parametricodelling, visualisation, material database, etc. to analyse and visu-
lise the effects of design decisions on deconstruction.BIM-DAS is intended to be adapted by industrial practitioners
o suit their design for deconstruction needs. In this way, BIM-DASill be useful from the concept design stage (RIBA work stage 2) to
he technical design stage (RIBA work stage 4) for measuring theeconstructability of a building. Future research will involve furtherefinement and implementation improvement on the predictionotentials of BIM-DAS. It is anticipated that BIM-DAS will be institu-ionalised with the national BIM implementation programme anduidelines. Achieving this will boost the incorporation of BIM-DASnto the construction practice.
. Conclusion
This study describes the development of BIM-DAS score as anbjective measure of degree of building deconstructability duringesign. This was done using a mathematical modelling approachased on the building design’s bill of quantity. In addition, the study
xamines and compares the BIM-DAS score of three case studies of auilding model with primary material of steel, timber and concretetructures. The results identify the use of prefabricated buildinglements and the use of demountable connection as the key factors
and Recycling 105 (2015) 167–176 175
to be considered in designing for deconstruction. The contribu-tion of this study is therefore three-fold: (i) it creates awarenesson the roles of design in building deconstruction; (ii) it broadensthe understanding of how design factors influence deconstruction;and (iii) it provides BIM-DAS score as an objective measure ofdeconstructability of building models. The BIM-DAS score providesa basis for comparative analysis of building models for selectingthe most deconstructable design among options without affectingbuilding forms or function. In addition, the BIM-DAS score coulddrive a guideline or benchmark for monitoring building construc-tion towards end of life sustainability. The results of this study alsohelp to understand how BIM functionalities could be employed toimprove the effectiveness of existing CDEW management tools andBIM software.
Existing literature shows that design for deconstruction is morecomplex than material specification and that there are other fac-tors that could influence it. However, the procedure demonstratedin this paper shows the practicality of objectively measuring thedegree of building deconstructability. Further studies are neededto consider more categories of factors such as material hand-ling, building design methodology, etc. and to assess the residualperformances of building elements. Further research could alsoinvestigate the correlation between BIM-DAS and other buildingscores such as BDAS, CONQUAS and BWAS. While this study hasbeen focused and biased towards deconstructability, the relation-ship between BIM-DAS and other building performance indicators(such as cost, sustainability, etc.) could be explored by future stud-ies. Lastly, assuming equal weighting for model parameters seemsimpractical. A quantitative survey research is therefore neededto understand the weighting of parameters of BIM-DAS. This willhelp to understand to what extend each of the factors contributestowards the BIM-DAS of a building. To ensure the usability of themodel, further studies are needed to integrate BIM-DAS into exist-ing BIM software such as Autodesk Revit as a plugin to enabledeconstruction performance simulation.
Acknowledgements
The authors would like to express their sincere gratitude to Inno-vate UK and Balfour Beatty PLC for providing the financial supportfor the research through grant (Application) No. 22883-158278 andFile No 101346.
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