The material selection problem has been treated extensively in current literature through many approaches, such as multi-objective optimization (Ashby, 2000), ranking methods (Jee & Kang, 2000), index-based methods (Shanian & Savadogo, 2006), and other quantitative methods like cost–benefit
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2.6.1 Models integrate environmental goals and budget requirements Castro-Lacouture et al. (2008) developed a material selection model, named the mixed integer linear program (MILP), to improve green construction decision-making through the selection of materials. The model considers both design and budget constraints while maximizing the number of credits reached under LEED.
Figure 2.4 Material selection model (Source: Castro-Lacouture et al., 2008)
The criteria and weight of the criteria in this program are based on LEED rating system. It cannot be directly used for structural material selection since constructability indicators are absent in this model.
Paya-Zaforteza et al. (2009) conducted a case study on 6 frames (four 2-bay frames, 3 bays 4 floors and 4 bays 4 floors) to test whether the embodied emissions and costs were related. The embodied emissions in their study involved emissions at the different stages of production and placement. A methodology to design RC building based on minimum embedded CO2 emission and the economic cost is described as below:
2 objective functions:
……….. (Eq. 2.1) Optimization model for material selection
Design Budget Environmental requirements
To maximizing the score achieve under LEED Estimated cost of materials is
not more than the budget for materials
Set of building system (e.g., floors, walls, roofs)
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……….. (Eq. 2.2) Constraints:
Wherer, Mi is the measurement of materials;
ei is CO2 unit emission (Database BEDEC, 2007, in Spanish) The authors concluded the following results: a) Embedded emissions and costs are closely related; b) The best solution for the environment are at most only 2.77% more expensive than the best cost solutions. c) The best cost solutions increase CO2 emissions by 3.8%.
The limitations of this study are: a) the transportation emission data was not included in this study; b) only CO2 emission is examined as an indicator of environmental impact; c) constructability indicators are absent in this model.
2.6.2 Models integrate environmental goals and constructability requirements
The traditional linear progression of a structural design (as shown in Figure 2.5 ) was summarized by Elnimeiri and Gupta (2008). In addition, they propose that sustainable parameters should be evolved as a circular progression model wherein each component is interrelated to the other.
Figure 2.5 Sustainable approach for structural synthesis (Source: Elnimeiri and Gupta, 2008)
Traditional structural design model
1. Structural geometry 2. Structural properties 3. Loads
4. Analysis 5. Membersizing
Architectural form
Twisted
Morphed
Prismatic Energy strategies
Ventilation
Daylight
IAQ Sustainable parameters
Scale
Materials
Electricity
Final structural system
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Giudice et. al (2005) developed a systematic method which introduced environmental considerations in the selection of the materials used in components, meeting functional and performance requirements while minimizing the environmental impact associated with the product‘s entire life- cycle. The target of this model was to meet functional and performance requirements while minimizing environmental impact.
The limitation of these two models is that economic criteria are absent.
2.6.3 Model(s) integrate budget and constructability requirements Sirisalee et al. (2004) used a multi-objective optimization method to develop a model specifically for structural material selection, which aimed to achieve 3 objectives: minimize thickness, minimize mass of casting and minimize cost.
The result was that economic lightweight design is one of the best solutions (including material choice) that minimize both weight and cost.
The limitations of this study are that: a) the term ―cost‖ used in this model is limited to the initial cost, which excludes the maintenance cost and deposit cost, and b) the environmental objective is absent.
2.6.4 Previous studies focus on methodology of decision on material selection
Ashby (2000) adopted the multi-objective optimization method to help decision-makers select material. It was found that trade-off surfaces give a method to visualize the alternative compromises, and that value functions (or
‗utility‘ functions) identify the part of the surface on which optimal solutions lie. However, the application of this method was not described in Ashby‘s study.
Jee and Kang (2000) utilized the concept of entropy to evaluate the weight factor for each material property or performance index；TOPIS was used to rank the candidate materials. A model to select the optimal material for a flywheel was developed as well. However, a new assessment parameter system is necessary in order to apply the methodology now.
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Granta (2009) introduced the Cambridge Engineer Selector (CES) methodology. This methodology involves two steps: the first step is screening and ranking and second step is to apply supporting information. The limitation of using CES is that the search for supporting information could be difficult, because it was not comprehensive and incomplete. Furthermore, this tool required a huge database for widely used material selection.
By producing a material selection decision matrix and a criteria sensitivity analysis, the Elimination and Choice Expressing the Reality (ELECTRE) model was used to obtain a more precise material selection for particular applications, including logical ranking of considered materials. Shanian and Savadogo (2006) suggested that the entropy idea is useful in the set of objective weights. However, no specific model was provided in their study.
2.6.5 Critique of existing models
The literature review shows that the building domain lacks a standard method that may help the decision-maker select more appropriate materials while taking into account the accomplishment of environmental goals and meeting design and budgetary requirements at the same time (Castro-Lacouture et al., 2009). Castro-Lacouture et al.(2008) and Paya-Zaforteza et al. (2009) developed their models for the selection of structural materials by integrating environmental and cost goals where constructability criteria were absent.
Elnimeiri and Gupta (2008) and Giudice et al. (2005) developed their models for selection of structural materials by integrating environmental and constructability requirements and leaving out economic factors. Sirisalee et al.
(2004) developed their model for the selection of structural materials by integrating the cost and constructability goal while environmental factors are excluded. Thus, there exists a gap in current models, which is that there is no model that integrates the economic, environmental and constructability requirements for structural frame material selection between RC and steel.