International Journal of Modern Research in Engineering & Management (IJMREM) ||Volume|| 1||Issue|| 3 ||Pages|| 16-31 ||March 2018|| ISSN: 2581-4540
Optimisation assessment model for selection of material and assembly for sustainable building projects Liman Alhaji Saba *1,2, Mohd Hamdan Ahmad 1, Roshida Binti Abdul Majid1 and Taki Eddine Seghier1 1
Faculty of Built Environment, Universiti of Teknologi Malaysia johor Bahru, Malaysia. 2 School of Environmental Studies, Federal Polytechnic Bida, Nigeria.
----------------------------------------------------ABSTRACT-----------------------------------------------------Sustainable Selection of Material and Assembly (SMA) constitutes a importants strategy in building design and construction. Current sustainable SMA methods fail to provide adequate solutions for finding the optimum improvement strategies and choosing the best alternative in a decision environment. To assist the decision-making process, this study suggests the Multi objective Optimization (MO) approach utilization. However, process improvements cannot be based only on environmental considerations, other factors like socio-economic must be also being considered in parallel. As well, the study indicates that MO coupled with Life Cycle Assessment (LCA) provides a tool for balancing process environmental and economic performance. The value of this approach in environmental process analysis rests in providing an optimal option for process improvements which may be optimal and suitable for a particular situation. A decision-aid tool – optimum Life Cycle Assessment Performance (OLCAP) – is recommended. OLCAP is tested and demonstrated by application to case studies of an existing traditional construction method and contemporary construction method of low cost housing projects. The MO value in process analysis lies in allowing for an alternative option for process betterments, therefore able the selection of the Best Available Technique not Entailing Excessive Cost (BATEEC) and Best Practicable Environmental Option (BPEO).
KEYWORDS: Selection of material and assembly; Life cycle assessment; multiobjective optimisation; process analysis; environmental impact ----------------------------------------------------------------------------------------------------------------------------- ---------Date of Submission: Date, 19 February 2018 Date of Accepted: 25 March 2018 ----------------------------------------------------------------------------------------------------------------------------- ---------I. INTRODUCTION The construction, fit-out, operation and ultimate demolition of buildings is a huge factor of human impact on the environment both directly (through material and energy consumption and the consequent pollution and waste) and indirectly (through the pressures on often inefficient infrastructure). Building construction practitioners have begun to pay attention to controlling and correcting the environmental damage due to their activities. With regard to important influence of the building sector, the approach of sustainable building possesses a high potential to make a worthful contribution to sustainability. The speed actions towards sustainable usage depends on decisions taken various actors in the construction process: firms. owners, designers, managers, and so on. [1, 2]. An significant decision is the sustainable Selection of Materials and Assemblies (SMA) to be utilized in building construction projects. As careful selection of sustainable materials has been identified as the simplest way for designers to start integrating the principles of sustainability in building construction projects [3]. The selection of building materials is considered as a multi-criteria decision problem [4], which is based on believing experience rather than utilizing numerical approach, as a result of lack of formal and measurement criteria availability [5]. It is a design process area that takes place in the detail design stage where significant decisions are made with respect to building assembly [6]. A lot of the evaluation methods have been faulted for overstressing the aspects of environment [7]. Some other methods like BREEAM and other existing methods for assessing buildings that are restricted to resource efficiency and environmental protection agenda possess small utility for assessing economic and social factors – which are all important indicators involved to sustainability – as fought to environmental sustainability, since they predominantly focused on environment that is one of the four (4) principles of sustainable building. Even against this single principle, they are only able to render relative assessment as opposed to absolute [8]. Also, the majorities of the assessment methods were designed for new construction, and focused on the design of the constructed buildings. To be considered sustainable, the methods of assessment will have to be remodel under the sustainability umbrella – economic, environmental, technical and social [9, 10].
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Optimisation assessment model for selection of material... Increasing the discussion scope outside environmental responsibility as well as adopting the wider sustainability agenda are more and more necessary requirements. In this challenges recognition, in 2011, a new standard BS 8905 was launched that was directed at products manufacturers to aid in initiation and advance their efforts of supply chain sustainability. This standard fail to meet or come short of aligning material selection practices with goals of sustainability at the building design phase. This is a phase where material selection and assessment normally take place. Among the literal effort to reduce the construction impact is by taken into consideration the embodied energy and carbon mitigation, which exist mostly in the building walls and frame as well as the recurring embodied energy and carbon components [11-13]. They also reported that in other to achieve significant minimization in the embodied energy and carbon intensity, replacement of conventional building materials with durable and low energy materials like locally resourced materials as well as innovative construction methods adoption were recommended. Therefore there is a require need for developing a holistic and systematic sustainable material selection process, of evaluating trade-offs between economic, environmental, technical and social criteria [14, 15]. The material selection process features as basically having many problem that will involve varied considerations, in many cases with complex trade-offs between them, which implied suitable solution might be found amongst the multi-criteria decision analysis (MCDA) methods [16-18]. In this regards, more detailed systematic interpretation of the Life Cycle Assessment (LCA) application to process selection and design is given [19]. This exemplifies the usage of system analysis to environmental management problems. However, recent literature suggests that LCA is gaining wider acceptance in many industrial sectors, particularly in the process sectors. While the utilization of LCA has traditionally been adjusted towards bettering the products environmental performance, various studies demonstrated the potential of LCA as a tool for process selection, process design and optimisation. Here, the focus is on the use of LCA for process optimisation. The aim is to demonstrate how the type of analysis adapted from welfare economics and operations systematic investigation can be combined with system analysis in the LCA context to provide a powerful decision-making tool for sustainable performance of process sector. The potential of this method is exemplified by the incorporation of two (2) case studies of an traditional construction method (TCM) and contemporary construction method (CCM) of low cost housing construction projects. Based on this information and the present study lacks, this paper suggests an optimisation method using mathematical programming technique to evaluate building materials and assemblies founded on their sustainability, of which Optimum Life Cycle Assessment Performance (OLCAP) was recommended. The procedures for integrating into the process optimisation framework of the environmental criteria alongside the economic as well as technical criteria are reviewed and discussed. It is indicated that this approach can provide a potentially powerful decision making tool for firms, managers, designers and process engineers.
II.
LITERATURE REVIEW
To gain insights into how similar studies on optimisation assessment approach in Selection of Materials and Assemblies (SMA) studies might have been conducted around the globe. A systematic search of key peerreviewed papers from renowned databases about SMA analysis was conducted. These searches yielded few results with little relevance. The first overarching outcome was the general agreement among peer-reviewed literature about the importance of optimisation method in assessment of building impacts on the environment [20]. The second outcome was that despite acknowledgement of the need to consider building SMA impact analysis, few quantitative studies have been conducted in this respect. These were discussed under the following sub-sections. Life cycle assessment (LCA) : LCA is a quantitative environmental performance tool, essentially based around mass and energy balances but applied to a complete economic system rather than a single process. While chemical or process engineering is normally concerned with the operations within system boundary 1, LCA considers the whole material and energy supply chains, so that the system of concern becomes everything within system boundary 2. The material and energy flows that enter, exist in or leave the system include material and energy resources and emissions to air, water and land, called environmental burdens and they arise from extraction and refining of raw materials, transportation, production, use and waste disposal of a product or process. The potential effects of the burdens on the environment, i.e. environmental impacts, normally include global warming potential (GWP), acidification, ozone depletion (OD), eutrophication and so on. As a result, in 1990, the Society for Environmental Toxicology and Chemistry (SETAC) initiated activities to define LCA and develop a general methodology for conducting the LCA studies. Soon afterwards, the International Organisation for Standardisation (ISO) started similar work on developing principles and guidelines on the LCA methodology [21]. The LCA methodology is still under development. At present, the methodological framework comprises four phases, namely: Goal and scope definition; Inventory analysis; Impact assessment; Interpretation. However, LCA is based on the kind of thermodynamic and system analyses which are central to process engineering [22]. Thus for these purposes, `the environment' is defined along with the system, by exclusion. The system of interest exists because
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Optimisation assessment model for selection of material... it produces goods and services, which are treated together as outputs. To generate these outputs, inputs of energy and materials are required. In the LCA context, system boundaries are drawn from `cradle to grave' to include all burdens and impacts in the life cycle of a product or a process, so that the inputs into the system become primary resources. The objectives of LCA can be of particular importance to process designers and engineers, because it can inform them on how to modify a system to decrease its environmental impacts. To assist in identification of the optimal options for improved system operation from ‘cradle to grave’, LCA can be coupled with optimisation techniques as discussed in the ensuing section. System optimisation and Life cycle assessment :In order to predict and describe the composite industrial systems behaviour, it is absolutely essemtial to utilize detailed mathematical modelling. In the same manner, the optimum operating conditions identification that will ensure bettered process performance normally renders the utilization of an optimisation technique absolute necessary. Historically, system optimisation in chemical and process engineering usages has focused on maximising the economic performance, subject to the certain constraints in the system. Over the years, environmental performance optimisation has started to be incorporated into system optimisation, beside traditional economic criteria. These methods have primarily been focused on several waste minimisation techniques [23]. An efforts to incorporate environmental considerations into the design and optimisation processes make up the starting of the paradigm shift in the process sector which are adjusted towards the process economic performance. Thus, it is possible for waste reduction methods to minimize the emissions from the plant but to enhance the impacts in or to another place in the life cycle, so that overall environmental impacts are enhanced, for example Bai [24]. Consequently, the need to incorporate Life Cycle Thinking (LCT) into optimisation and process design procedures has been accepted by researchers [25-27]. For exemple, that which establishes a link between the process environmental and economic performance from ‘cradle to grave’ been formulated by [28-30]. This method is known as ‘Optimum Life Cycle Assessment Performance’ (OLCAP). The OLCAP process is exemplified on low cost housing construction projects case study of TCM using stablise clay block and CCM using sand-cement block houses in the ensuing section.
III.
APPLICATION OF OPTIMUM LCA PERFORMANCE – CASE STUDIES’
The process chosen for the exemplification of OLCAP approach is an existing traditional construction method (TCM) using stabilise clay block and contemporary construction method (CCM) using sand-cement block of low income house (LIH) constructed in 2016 in Abuja of Nigeria. A two bedroom apartment house of 69.0m2 floor area with the average headroom of 3.0m was used as the model for the case study. The structural system used was a reinforced concrete columns, beams and roof beams. The external envelope material and the internal partition material were not rendered on both faces with sand-cement mortar, with the following specifications as indicated in Table 1. Figure 1 shows the graphical drawings of stabilise clay block house model.
Figure 1: The graphical drawings of TCM stablise clay block house Figure 2 showed the construction activities prominent features (extraction, processing, manufacturing and production/construction) for the model TCM stablise clay block house.
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Optimisation assessment model for selection of material...
Figure 2: TCM construction activities prominent features In addition, to the case study, further scenario (CCM using sand-cement block house) was a 3 bedrooms apartment house of 92.0m2 floor area and with average headroom of also 3.0m was modeled to provide a comparison. Figure 3 shows the graphical drawings of CCM sand-cement block house model. The structural system used was a reinforced concrete columns, beams and roof beams. The external envelope material and the internal partition material were rendered on both faces with sand-cement mortar, with the following specifications as indicated in Table 1.
Figure 3: The graphical drawings of CCM sand-cement block house In addition, Figure 4 showed the construction activities prominent features (extraction, processing, manufacturing and production/construction) for the model CCM sand-cement block house.
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Optimisation assessment model for selection of material...
Figure 4: CCM construction activities prominent features Table 1: List of building materials and assemblies Building Stage 1,0 Substructure
2.0 Super structure 2.1 Walls and columns
2.2 Roof Structure and covering
Component
Material
AMC
CMC
Strip foundation Wall in foundation
√ √
√ √
Filling to level Hardcore Ground floor slab
Concrete 230 x 230 x 450 mm hollow sandcement blocks filled with light concrete Laterite soil Broken concrete/stone Concrete
√ √ √
√ √ √
Columns Beams External walls Partition walls External walls Internal walls Wall plate
Reinforced concrete Reinforced concrete 230 x230 x 450 mm hollow blocks 150 x 230 x 450 mm hollow blocks 230 x 150 x 300 mm solid blocks 230 x 150 x 300 mm solid blocks 75 x 100mm hardwood
√ √ x x √ √ √
√ √ √ √ x x √
Tie beam Rafters/struts Purlins Noggins Fascia board Roof covering
50 x 150mm hardwood 50 x 100mm hardwood 50 x 75mm hardwood 50 x 50 mm hardwood 25 x 250mm hardwood 0.55 mm long span aluminium sheets PVC Tiles Plastering and emulsion paint Plastering and emulsion paint Vitrified ceramic tiles Locally steel doors Hardwood panel doors Aluminium/glass casement 20 x 20mm hollow steel pipe
√ √ √ √ √ √
√ √ √ √ √ √
√ x x √ √ √ √ √
√ √ √ √ √ √ √ √
2.3 Finishes
Ceiling Internal walls External walls Floor finishes 2.4 Doors/Windows/Fittings External doors Internal doors Windows Anti-burglary bars Key: √ = Applicable, x = Not applicable
The Methods of Assessment : In this section, the different EE and EC assessment methods are examined. The aim is to establish which method(s) to use. In the literature, three methods of assessment are quite common: the input-output analysis, the process analysis, and the hybrid analysis. Input-output LCA is a top-down method for analyzing the environmental interventions of a product using a combination of national sector-by-sector economic
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Optimisation assessment model for selection of material... interdependent data which quantifies the dependencies between sectors, with sector level environmental effects and resource use data [31]. In process LCA, known environmental inputs and outputs are systematically modelled through the utilisation of a process flow diagram. The process LCA is often called a bottom-up approach. This is because the subjects of analysis in process LCA are individual processing units and the flow rate and composition of streams entering and exiting such units. The above two (2) life cycle methods of assessment have advantages and disadvantages which have been extensively discussed [32-34]. In order to justify the choice of the methods used in this study, a summary of the advantages and disadvantages of the preferred choice is examined. Inputoutput analysis suffers from lack of representativeness being used due to over-aggregation of data. Also, national sector-by-sector economic interdependent data or sectoral matrix is often too old and out of date in developed countries and worse in developing countries. Process-based LCA allows for a detailed analysis of a specific process at a point in time and space. Nonetheless, it is often criticized for its subjectivity in the definition of the processes that should be considered and the data sources to be used, which can be complex if the building has so many different types of materials. Mathematical models : The main reason for using emission or impact factors is to facilitate computation of emissions. By using emission factors, tedious tasks that would have involved chemical equations are avoided. This is because emission factors are expressed as quantity of EE or EC per functional unit. For example, according to Bath ICE, the emission factor of virgin aluminium is 11.46kgCO 2/kg. The functional unit is the “kgâ€? in the denominator as it denotes quantity of virgin aluminium in 1kg. Therefore, to compute the emission from a given quantity of virgin aluminium, a simple multiplication of the total quantity and the emission factor is conducted. If there are several construction materials considered, then the products of the emission from different materials are added. This is modelled mathematically as in equations (1) and (2) [13]. Further details on the research methods are explained subsequently using equations (1) to (8) [35]. đ?‘›
đ??¸đ??¸đ?‘˜ = ∑(1 + đ?‘Šđ?‘˜ ) Ă— đ?‘„đ?‘˜ Ă— đ??źđ?‘˜
(1)
đ?‘˜=1 đ?‘›
đ??¸đ??śđ??ž = ∑(1 + đ?‘Šđ?‘˜ ) Ă— đ?‘„đ?‘˜ Ă— đ??źđ?‘˜
(2)
đ?‘˜=1
Where, EEk and ECk are EE and embodied CO2 of material type k with units MJ and kgCO2 respectively; Wk is the waste factor (dimensionless) of material type k; Qk is the total functional quantity of material; Ik is the EE factor or embodied CO2 factor with units’ MJ/functional unit and kgCO2/functional unit of material respectively. However, carbon emission for direct fuel combustion was calculated using the formula: CEF = A x EC (3) Where, CEF = carbon emission from direct fuel consumption, A = activity data (litres of fuel), EC = emission coefficient (kgCO2/litre of fuel). However, given the labour-intensive construction methods prevalent in the study area, manual energy was estimated using the manual energy coefficient for the tropical region as recommended by [36, 37]. Total Embodied Energy: EE = EEM + EET + EEC
(4)
Where, EE= total embodied energy, EEM = embodied energy of material (cradle-to-gate), EET = embodied energy of transportation, and EEC = embodied energy of construction. Material Embodied Energy (Cradle-to-Gate) EEM = QM [EECF]
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(5)
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Optimisation assessment model for selection of material... Where, EEM = cradle-to-gate embodied energy of material, QM = quantity of material (kg), and EECF = embodied energy coefficient of material (MJ/kg) according to ICE database and available local inventory data. Transportation Energy EET = QF [LHV]
(6)
Where, EET = embodied energy of material transportation, QF = quantity of fuel consumed (litres), and LHV = lower heating value of fuel. The study assumed that all building materials were locally produced. Hence local transportation of materials was accounted for. Road haulage is the main mode of material transportation in the study area and the fuel type was found to be predominantly diesel. The quantity of diesel was estimated using 35litres per 100kilometers for heavy duty trucks and 20litres per 100kilometers for light duty trucks [38]. Site Construction Energy This is divided into two parts namely: energy used by site equipment and site installations as well as manual energy. All fabrications were assumed to be carried out on the construction site. Energy and fuel use data were obtained from the records of the contractor that built the reference building. Where electricity is used for site construction activities, the primary energy content of grid electricity was estimated using the formula: E = 3.6[GE] PEF (7) Where, E = primary energy content of electricity use, GE = grid electricity use in kWh, PEF = primary energy factor of grid electricity, and 3.6 = conversion factor from kWh to MJ. The PEF for electricity in the study area was estimated to be 2.83 [39]. Also, if direct fuel combustion is used in the site construction, the primary energy content of direct fuel combustion is estimated using equation (6).
Manual Energy ME = 0.75LT
(8)
Where, ME = manual energy, 0.75MJ/hour = human energy coefficient, L = number of labour workers, and T = number of hours of work. Equation (7) above was derived from earlier work by [40] on agricultural productivity and used in a recent work by [41] on energy assessment of cement production in Nigeria. Because of lack of information about waste data in Nigeria, the waste factor was considered to be zero. Aggregation of Data Aggregation is a straight forward task. First, the emissions from a category are added independently. In other words, emissions from all the different construction materials, equipment, and personnel transport types used are independently computed. Then, the emissions from the three different categories are summed up to obtain a total. These steps were implemented in assessing EE and EC of the two case studies considered. Application of optimum LCA performance framework to the problem : The Optimum Life Cycle Assessment Performance (OLCAP) methodological framework consists of four (4) steps: 1. LCA completion study; 2. Optimisation problem formulation; 3. Multiobjective optimisation (MO); and 4. Selection of the best compromise solution.
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Optimisation assessment model for selection of material... However, there is an important gaps between the theory and practice of sustainability and Sustainable Development (SD) at the project level [42]. The foundations for SD are already encapsulated in the definition given in the seminal Brundtland report [43]. This most quoted definition states that it is, “development that meets the needs of present generation without compromising the ability of future generations to meet their own needs”. However, [42] stated that the all-inclusive definition sounds abstract, and requires hierarchical transformation to operational decision-making variables. There is now wide recognition of the requirement for quantitative transformations, counterpart incorporated holistic approaches in evaluating the sustainability of building material and assembly, as a part of wider SD agenda. Researchers working on the evolving discipline of Sustainability Science presently acknowledge that the implementation success at the project levels depends on various contributors. These include: 1. the criteria development that transform macro-level policies and national sustainability goals to project level decision-making variables; 2. the decision models development, computational frameworks, and assessment methods for building material and assembly sustainability assessment; and 3. the development and incorporated decision support tools implementation to facilitate decision making by various stakeholders. Such a crisp value index would facilitate dissimilar material and assembly alternatives comparison along diverse sustainability envelope dimensions: economy, environment, resource efficiency, performance, waste minimization, and socio benefit. A mathematical model is therefore an essential requirement of the optimisation problem. Such a model is needed for sustainability quantification in decision-making. The detail description of the steps contained in the model formulation is described below and the OLCAP approach represented by diagram as indicated in Figure 5 [30].
Step 1.
LCA
Manual Computation
Burdens
Impacts
Process-based LCA (PBLCA)
Step 2.
Optimisation Model Socio-economic, technical, BIM generator legislative and other constraints Economic criteria Environmental criteria REVIT Step 3.
Multiobjective Optimisation (MO)
Linear Programming (LP)
Optimum solutions
Decision- makers
Step 4.
Optimisation Method
Mathematical Programming
Best compromise solution
Improved Process Performance of “Upstream”
Figure 5: Optimum LCA performance (OLCAP) methodological framework Step1: LCA Completion study – It involves conducting a system LCA study, in an accordance to [44] methodology, as showed in Figure 8. An appropriate software of LCA, for example PEMS [19], TEAM [45] or BIM [13], can be utilized to conduct energy and material balances, as well as to quantify the impacts it has
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Optimisation assessment model for selection of material... throughout the life cycle. Because of lack of database and tools, a process-based LCA analysis technique was adopted for this purpose. Step 2: Optimisation problem formulation - Because of LCA nature, with distinct environmental impacts to be taken into consideration, the problems of optimisation is multiobjective. Thus, the problems of conventional single-optimisation involving economic objective function are translated into problems of multiobjective, to consider the environmental objectives. The problem of Multi-Objective (MO) in LCA context can be in this form: Min f(x, y) = [f1 f2 ‌‌‌ fp]
(1)
y ∈ Y đ?œŒ Zq
(2)
s. t. h(x, y) = 0 g(x, y) ≤ 0 x ∈ X đ?œŒ Rn
Where, f is a vector of economic and environmental objective functions; h(x, y) = 0 and g(x, y) ≤ 0 are equality and inequality constraints; and x and y are the vectors of continuous and integer (discrete) variables. For example, the equivalence physical constrained may be defined by energy and material balances; this may depict the material availabilities, capacities, heat requirements and so on. A n vector continuous variables is the energy flows and material, compositions, pressures, units sizes and so on, while a q vector integer variables is option materials or system’s processing paths. If the Z integer is null set and the physical constrained as well as impacts are linear, then Equations (1) and (2) is the problem of Linear Programming (LP); while if the integer variables is not null set and nonlinear terms present in the impacts and physical-constrain, Equations (1) and (2) will be problem of Mixed-Integer Nonlinear Programming (MINLP). The problems of Mixed Integer Linear Programming (MILP) incorporate only linear and integer variables. Typically, an economic objective involves a cost or profit function, which is defined by: F = CT y + f(x)
(3)
Where, c is a cost or profit coefficients vector for integer variables and f(x) is a linear or nonlinear function depicted by continuous variables. In this context, the environmental objectives is the burdens Bj or impacts Ek: đ?‘
đ?‘€đ?‘–đ?‘› đ??ľđ?‘— = ∑ đ?‘?đ?‘—,đ?‘› đ??˝
đ?‘Ľđ?‘›
(4)
đ?‘›=1
đ??¸đ?‘˜ = ∑ đ?‘’đ?‘˜,đ?‘— đ??ľđ?‘—
(5)
đ?‘—=1
Where, đ?‘?đ?‘—,đ?‘› is emission coefficients associated with continuous variables đ?‘Ľđ?‘› xn. In equation (5), đ?‘’đ?‘˜,đ?‘— is the relative contribution of burden Bj to impact Ek, as defined by the ‘problem oriented’ technique to impact assessment [46]. In this approach, for example, GWP factors, đ?‘’đ?‘˜,đ?‘— , for dissimilar greenhouse gases (GHGs) are showed relative to the global warming potential (GWP) of carbon dioxide (CO2), which is thus determined to be unity. In the event of utilization of different impact assessment technique, subsequently equation (5) is given a new definition accordingly. But, presently, it was noted that the LCA technique assumes that environmental impacts as well as burdens functions are linear, that is, are directly proportional to the functional output unit(s) and no synergetic or antagonistic effects. BIM tool – REVIT was adopted for this purpose. Step 3: Multiobjective optimisation - The system is then optimised at the same time on environmental and economic impacts to discover the several aspects or multidimensional noninferior or Pareto surface that maps
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Optimisation assessment model for selection of material... optimal solutions. The choice of environmental objectives for optimisation is contingent upon the Scope and Goal of the study. Therefore, optimisation can be at the impact assessment or inventory levels, in which the environmental objectives are defined as burdens or impacts [28, 30]. One possible approach to optimisation in the context of LCA would be to combine environmental and economic objectives into one function so that the problem may be minimize to one objective optimisation. The significance is on the choices from the noninferior solutions, rather than preferences before analysing all the trade-offs among objectives. The trade-offs amongst the noninferior solutions indicate the gained and lost by selecting the option. The decision makers who know and comprehend the options and trade-offs are potential to understand other parties’ interests and make a compromise. Furthermore, by trade-off incommensurable objectives such as economic requirements and environmental impacts, this technique avoids the well-known problems that may be encountered, e.g., in cost – benefit analysis [47], that is minimizing individual preferences to the value of market or trying to express the environmental quality in financial terms. Cost-benefit analysis (CBA) is maximum net gain idea: this minimizes the combine social welfare to the net economic benefit monetary unit. In the recent past, CBA has been used in environmental decision-making. The widely used technique is known as ‘contingent valuation’ (CV). Its difficulties and limitations have been recognised. The latter [48, 49] have pointed out that CBA has serious difficulties in dealing with intergenerational equity and sustainability problems as well as in valuing the natural environment. Summarily, CBA and related economic techniques to decision-making faced three (3) problems: the individual preferences measurement, the comparison of these preferences, and their combination into a social preference function. But these cannot provide information for decision-making on a ‘local’ level: for example, they cannot advise engineers on how to modify a process to better its environmental performance. Multiobjective optimisation (MO), on the other hand, does exactly this: it can optimize the system operation with environmental, economic technical and other aspects taken into consideration. If used in the context of LCA can be able to optimize the product or process whole life cycle and so provide a more effective approach to environmental management of a system. Linear programming (LP) was adopted for this purpose. Step 4: Selection of the best compromise solution - To choose the best compromise solution from optimum alternatives, preferences articulation is essential. One of the possible ways to choose the ‘best’ solution is to consider a graphical representation of the noninferior and then choose the best compromise solution on the basis of the trade-offs. However, this technique is limited to two (2) or three (3) objective functions at most; more than this, graphical representation becomes complex. If all objectives are considered importance, than the best compromise solution might be that which equalises the percentage by which all objectives differ from their optimum values. However, should any of the objectives be considered more important than the others, then other methods that allow preferences ordering and quantification is known as multicriteria decision-making (MCDM) techniques, can be used to identify the best compromise solution. MCDM techniques provide a structured approach to a decision making process. Extensive reviews of MCDM techniques can be found in [50] and [51]. User friendly software with various MCDM methods to aid the decision making process are also available [24]. They enable systematic analysis and modelling of preferences with the aim of providing help and guidance to decision-makers in identifying their most desired solution. The major advantages of these techniques like BIM tool - REVIT is transparent, non-ambiguous and easy to use by non-experts. It is important to note that the attributes and the preferences are always identified on a case by case basis within a bounded decision space, and that they only apply in that particular decision-making context. This avoids the criticism often voiced, in both LCA and CBA, of trying to use general weights or costs to indicate the importance of distinct criteria in different decision-making situations. Optimisation method was adopted using mathematical programming (MP). In sum, the first step in this procedure involves carrying out an LCA study of the process, by following the [44] methodology. As indicated in Figure 8 [30], BIM software can be used to carry out material and energy balances and to quantify the burdens and impacts along the life cycle. The material and energy balances for the process itself (boundary 1 in Figure 7) can also be carried out within existing design operation software and these data can then be fed into the BIM software. The data for the other parts of the system (boundary 2 in Fig. 1) can be sourced from a database which is normally an integral part of the BIM software. A more detailed exposition of the LCA methodology is given elsewhere [44] and is not discussed further here. Instead, the focus of this paper is on steps 2 – 4 of the OLCAP procedure. The environmental burdens and impacts quantified in step 1 represent an input into the optimisation model, which is formulated in step 2. In addition to environmental criteria, the model includes economic, technical, legislative and other constraints within which the system must operate. In step 3, the system is optimised on environmental and socio–economic objectives of interest to the decision-makers, to yield a number of optimum solutions. A suitable optimisation technique and software must be used to generate and solve the optimisation problem. A more detailed account of these two steps of OLCAP is given in step 2 and 3. Finally, step 4 enables the decision-makers to choose the best compromise
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Optimisation assessment model for selection of material... alternative from a range of optimum solutions. Thus, BIM tool – REVIT can be used to facilitate the decisionmaking process. This is discussed in step 4.
IV.
THE TECHNIQUE ADOPTED FOR VALIDATING THE SMA MODEL
According to [52], “the suitable technique for validating a model mainly depend on the real world distinct element and characteristic in a problem being analysed as well as the type of model utilized”. Nevertheless, the various techniques consideration suggests degenerate tests as the only suitable techniques for validating the developed SMA model, mainly because no real-system database available. Also, the aim of this study to validate the model for sector-wide usage also makes this approach more suitable than the others. The objective of degenerated tests validation was to see if it degenerates as expected by modeling such situations in the model using suitable values selection of the input and internal parameters. Therefore, BIM tool - REVIT was adopted for the validation. The ensuing sections describe the detailed procedure of the validation exercise and the findings. Results validation using BIM tool – REVIT : Based on the Embodied Energy (EE) and Embodied Carbon (EC) computation, the challenges encountered in performing the same for the whole building systems cannot be underestimated. This is manual computation fundamental weakness, where everyday computational tasks are repeated for each building material identified. Moreover, the manual process is allergic to errors and the probabilities of naming the errors are lose weight. The come out of BIM can be utilized to increase the processbased approach acuracy in the EE and EC computation. Also, BIM act to fulfill an option to validate the obtained manual computational results. The previous studies such as [53], many BIM software exist and are presently being used to model buildings. Example of such is Revit, which is regarded with great favour in the BIM software market. A main merit of Revit is that its building models can be converted into practical or readily communicated formats without much difficulty that can be processed by other software [54]. However, comma-separated value (CSV) is a comparatively simple file format supported by Microsoft Excel and Revit. Excel can the information in CSV format. Producing or making up building model data in CSV can be interpret by MS Excel or Revit. The MS Excel computational power provide a particular quality of great choice in modelling equations 1 and 2, which are utilized in EE and EC calculation. In addition, MS Excel can be utilized to show calculation results in an accordance to standard formats like the Cahier des Prescriptions Techniques in France and the New Rules of Measurements (NRM) in the United Kingdom (UK), which are These are principles or conditions of output presentation and construction quantity measurements. This was adopted for this study. Since it is usually used in developing countries like Cameroon as well as in developed countries like Singapore. Based on the 2D drawings and Architects specification stabilise clay block house and sand-cement block house were modelled in Revit. The 3D equivalents are presented in Figure 6 and 7.
Figure 6: 3D TCM of stabilise clay house Revit model
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Optimisation assessment model for selection of material...
Figure 7: 3D CMC of sand-cement block house Revit model Furthermore, the schedules as well as quantities are generated from these models by utilizing the “Modify Schedules/Quantities” function under the “View” tab in Revit 2014. The output is converted to CSV format using the “Export” function in Revit 2014. The CSV format is stored in any preferred location on the computer and read with “MS Excel”. Equations 1 and 2 are modeled in Excel and calculation are conducted in this environment. First results obtained differ slightly from those obtained by utilizing manual calculations. The manual process is reaffirmed to name and also correct the errors. In addition, BIM model is reaffirmed to name the missing components. These exercises were performed several times until common results were obtained, and this results are presented in Tables 2 and 3.
Table 2: Cradle-to-gate performance (TCM of stablise clay block house) Building component Site installation Substructure Walls and frames Roof structure and covering Finishes Doors/windows/fixture/fittings Plumbing installations Electrical installations Waste Total
EE emissions MJ/kg No data 70,154.17 10,255.38 32,298.00 1,217.14 16,010.23 610.96 1,257.19 No data 129,953.82
Percentage (%)
EC emissions (kgCO2)
Percentage (%)
54.0 8.0 24.0 0.4 12.1 0.5 1.0
10,001.89 810.35 1,804.56 76.89 1,127.86 980.37 1,615.51
64.0 5.0 11.5 0.5 7.0 4.0 8.0
100.0
15,689.70
100.0
Table 3: Cradle-to-gate performance (CCM of sand-cement block house) Building component Site installation Substructure Walls and frames Roof structure and covering Finishes Doors/windows/fixture/fittings Plumbing installations Electrical installations Waste Total
EE emissions MJ/kg No data 97,114.99 129,434.25 43,052.68 2,290.04 20,434.85 980.37 1615.51 No data 294,194.96
V.
Percentage (%)
EC emissions (kgCO2)
Percentage (%)
33.2 44.0 14.2 0.8 7.0 0.3 0.5
13,861.97 19,991.51 2,408.00 145,41 1,422.31 1,222.00 2,514.37
33.3 48.0 5.8 0.6 3.4 2.9 6.0
100.0
41,565.57
100.0
DISCUSSION
After clearly identifying the performance of various materials and component elements assemblies, decisionmakers are more knowledgeable in selecting weights that reflect their personal reliability on each analysis.
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Optimisation assessment model for selection of material... This research discovered that a house built using sand-cement block house, produced a building with a 294,194.96MJ of EE and 41,565.57kgCO2 EC emission, with 126% EE and 165% embodied carbon more when compared with stabilise clay block masonry wall for a residential building. However, the minimization in the usage of materials with comparatively high EC, in this case sand blocks, with materials with lower EC, in this case clay, in the wall component was the fundamental reasons or logic behind factor in the difference found. A distinctive for the Nigeria, clay was not only utilized as the principal structural material but also not needing mortar wall finishes, rather than the more traditional mortar for wall plastering finishes (as found in the TCM of stablise clay block house). The mortar displacement for wall plastering finishes gave rise to a carbon saving of 27%. The further factor leading to the low EC of the study case is the efficiency of volume production that is related with stabilise clay block. In spite of ratio of the output to the input in the manufacturing of the TCM of stabilise clay block, onsite waste production in this case study was still an important factor in the overall EC, 5% of the total. However the clay manufacturing does not add to the overall waste associated CO2 produced; barely about 6% of transport associated EC. In addition, this proposes decreases in EC can be made by increasing the quantities of off-site manufacturing and minimization of on-site waste. Because no waste data collected, for both process, was not of sufficient quality to make a robust EE and EC emissions quantification. Thus further study is required so as to quantify the resource efficiency claims from stabilise clay block house processes in comparison with that from onsite construction. In spite of the high clay ratio throughout the structure half of the materials associated embodied carbon was discovered to be related with the foundation, substructure as well as floor slab construction. Hence the comparative importance of these sub structural elements minimizes with the materials CO2 intensive gain in other elements. This proposes that these sub structural components and materials utilized would be appropriate objectives for minimizing the EC further in such stabilize clay house. The sub structural elements were consisted of having the properties of cement rich materials and blocks. The cement in concrete and mortars can possess a high energy input during production as well as relatively high EC, in addition to the already CO 2 release during the chemical changes of manufacture. The embodied carbon quantity that is related with cement manufacturing depends on the primary materials as well as the source of energy utilized in its output. The emissions that are linked with the production of cement can be minimized by the fossil fuels uniform movement with both waste materials and renewable energy as the source of energy. Therefore, any sensible or fair EE minimization should aim the application of steel, cement-based products as well as cement. The policy direction in this regard should be towards replacement of energy-intensive materials with low energy materials. A number of research works on alternative building materials in Nigeria exist, but there is need for proper documentation and a set of rules, principles or laws, especially written ones (or codification) to help and make easier the informed use. In this regard, study on the utilization of more alternative envelope material to sandcement blocks (like recycle and reuse) and the utilization of cement replacement (for example lime, fly ash) is crucial to sustainable materials selection in achieving sustainable development. In addition, since the continue application of cement play significant function in building construction in the study area, uninterrupted change for the better or progress in the production process is suggested. The materials replacement is not the only alternative for sustainable building construction. Efficient as well as effective construction processes also help or make use of sustainability in building construction. Minimizing the environmental loads from stabilise clay block to a more advance stage which could be achieved in two (2) ways [55]. Firstly, by minimize the cement usage by replacing with lower embodied carbon alternatives such as ground granulated blast furnace slag, fly ash and other pozzolanic materials or lime based materials as mentioned in foregoing paragraph. Secondly, which is not associated with this study case is by utilizing the design strategies so as to minimize the cement volumes needed, for example, removing the oversite concrete ‘raft’, utilizing isolated point foundations instead of strip foundations or utilizing steel helical screw piles. Although a relatively high embodied energy product steel helical screw piles are both reusable and recyclable. Therefore, both the two strategies would minimize the application of carbon intensive materials where no additional benefit to the application is possible in lightweight construction. Nevertheless, in the study case, distinctive of majority clay construction, the most of its practicable mass is separated or detached within the building structure or under other material finishes and, accordingly, not available for the practicable thermal storage that could compensate for or counterbalance the environmental loads of its extraction and production. The full lifecycle, be made up of occupation, maintenance and demolition as well as disposal requires to be considered. EC consideration requires to be incorporated at the earliest stage of design. If environmental loads are to be reduced reasonably even though reducing further benefits there requires being general well-informed thought in design of building.
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Optimisation assessment model for selection of material... The above scenario for building construction materials emphasizes the significant function built environment practitioners participated in building construction materials selection or specification as well as in the process of construction. Frequently, selection of alternative building construction materials has been hindered by the deficiency of adequate technical information concerning the materials which makes built environment practitioners bind to conventional building construction materials with widely known technical information. This entails that cooperative attempts should be made to identify, codify as well as integrate into option or alternative, low energy material and building codes that are dependent on context applicable to the area of study. In this regard, the applicable government agencies together with the built environment stakeholders as well as professionals should make cooperative attempts to address the challenge. With the performance scores of each assembly type, the present study is not aiming at normalizing and ranking the different combinations. This study attempts to incorporate the whole building system, in order to begin setting benchmarks for the industry. This would transform the way the sector performs environmental assessment on building SMA and perhaps enhance research in more simplified tools and methods to conduct LCA. It is interesting to note that there is no support on the effect of EE and CO2. When observed, it can be found that sand-cement block house is responsible for a difference about 1256MJ/m2 of EE and 217.37kgCO2/m2 of EC.
V. CONCLUSION MO process can be combined with LCA successfully as an aid in building construction process environmental management. The results exposes that the process can be simultaneously optimised on an environmental objective functions to identify the best compromise solution for bettering the performance of a process. The results indicate that the process environmental performance can be improved by up to 26% EE and 65% EC emissions in comparison with the existing contemporary construction method process. Since process improvements cannot be carried out on the basis of environmental LCA only, it is also shown in this study that the compromise between environmental and economic performance can be found on the TCM obtained by process optimisation. The merit of MO in environmental process management in the context of LCA lies in offering alternative options for process improvements that enables the choice of the BATNEEC and BPEO. Furthermore, multiobjective process optimisation can successfully be combined with LCA as an aid in environmental management of a building construction process. The process is simultaneously optimized on a number of environmental objective functions to identify the best compromise solution for bettering the performance of the process. MO utilized in this approach provides a more effective approach to environmental management process by offering alternative optimal solutions and enabling decision-makers to identify and choose the BIM tool - REVIT. The process-based approach was manual and because of susceptibility of such an approach to errors, BIM software was used to validate the computational results. It is important to note that this is an emerging field and knowledge in this field is gradually being explored. Hence, emissions from whole process construction were assessed but emissions from site installation and was waste are not included, due to lack of data. The results obtained were converted to per unit m2 so as to ease the comparison. Furthermore, when compared to other studies, the calculational results were in the same range, although significantly lower than values obtained in the developed countries. The comparison revealed sand-cement block house consumed more embodied energy and carbon than stablise clay house. The approach suggested in this research can allow for assessment of the other civil infrastructures. The authors are convinced that this research can assist building stakeholders in making critical decisions during the selection of sustainable material and assembly alternatives. Novelty : The mathematical methodology could also be extended with the other optimisationn techniques in solving material and assembly selection problems. Finally, the evaluation model and results can provide a valuable reference for building professionals seeking to enhance the sustainability of construction projects.
ACKNOWLEDGEMENT The authors would like to thank the Universiti Teknologi Malaysia and Federal Polytechnic Bida, Nigeria for their facilities, conducive-environment and support for the study as well as the project manager of MS Cornerstone Engineering Construction and Company Limited in Nigeria who contributed to this study.
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