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Computational screening-LCA tools for early design stages
https://orcid.org/0000-0003-4479-7392
https://orcid.org/0000-0003-1163-6779
Life Cycle Assessment (LCA) has been widely adopted to identify the Global Warming Potential (GWP) in the construction industry and determine its high environmental impact through Greenhouse Gas (GHG) emissions, energy and resource consumptions. The consideration of LCA in the early stages of design is becoming increasingly important as a means to avoid costly changes at later stages of the project. However, typical LCA-based tools demand very detailed information about structural and material systems and thus become too laborious for designers in the conceptual stages, where such specifications are still loosely defined. In response, this paper presents a workflow for LCA-based evaluation where the selection of the construction system and material is kept open to compare the impacts of alternative design variants. We achieve this through a strict division into support and infill systems and a simplified visualization of a schematic floor layout using a shoebox approach, inspired from the energy modelling domain. The shoeboxes in our case are repeatable modules within a schematic floor plan layout, whose enclosures are defined by parametric 2D surfaces representing total ratios of permanent supports versus infill components. Thus, the assembly of modular surface enclosures simplifies the LCA evaluation process by avoiding the need to accurately specify the physical properties of each building component across the floor plan. The presented workflow facilitates the selection of alternative structural systems and materials for their comparison, and outputs the Global Warming Potential (GWP) in the form of an intuitive visualization output. The workflow for simplified evaluation is illustrated through a case study that compares the GWP for selected combinations of material choice and construction systems.
Computational screening-LCA tools for early design stages
https://orcid.org/0000-0003-4479-7392
https://orcid.org/0000-0003-1163-6779
Life Cycle Assessment (LCA) has been widely adopted to identify the Global Warming Potential (GWP) in the construction industry and determine its high environmental impact through Greenhouse Gas (GHG) emissions, energy and resource consumptions. The consideration of LCA in the early stages of design is becoming increasingly important as a means to avoid costly changes at later stages of the project. However, typical LCA-based tools demand very detailed information about structural and material systems and thus become too laborious for designers in the conceptual stages, where such specifications are still loosely defined. In response, this paper presents a workflow for LCA-based evaluation where the selection of the construction system and material is kept open to compare the impacts of alternative design variants. We achieve this through a strict division into support and infill systems and a simplified visualization of a schematic floor layout using a shoebox approach, inspired from the energy modelling domain. The shoeboxes in our case are repeatable modules within a schematic floor plan layout, whose enclosures are defined by parametric 2D surfaces representing total ratios of permanent supports versus infill components. Thus, the assembly of modular surface enclosures simplifies the LCA evaluation process by avoiding the need to accurately specify the physical properties of each building component across the floor plan. The presented workflow facilitates the selection of alternative structural systems and materials for their comparison, and outputs the Global Warming Potential (GWP) in the form of an intuitive visualization output. The workflow for simplified evaluation is illustrated through a case study that compares the GWP for selected combinations of material choice and construction systems.
Computational screening-LCA tools for early design stages
https://orcid.org/0000-0003-4479-7392
https://orcid.org/0000-0003-1163-6779
Life Cycle Assessment (LCA) has been widely adopted to identify the Global Warming Potential (GWP) in the construction industry and determine its high environmental impact through Greenhouse Gas (GHG) emissions, energy and resource consumptions. The consideration of LCA in the early stages of design is becoming increasingly important as a means to avoid costly changes at later stages of the project. However, typical LCA-based tools demand very detailed information about structural and material systems and thus become too laborious for designers in the conceptual stages, where such specifications are still loosely defined. In response, this paper presents a workflow for LCA-based evaluation where the selection of the construction system and material is kept open to compare the impacts of alternative design variants. We achieve this through a strict division into support and infill systems and a simplified visualization of a schematic floor layout using a shoebox approach, inspired from the energy modelling domain. The shoeboxes in our case are repeatable modules within a schematic floor plan layout, whose enclosures are defined by parametric 2D surfaces representing total ratios of permanent supports versus infill components. Thus, the assembly of modular surface enclosures simplifies the LCA evaluation process by avoiding the need to accurately specify the physical properties of each building component across the floor plan. The presented workflow facilitates the selection of alternative structural systems and materials for their comparison, and outputs the Global Warming Potential (GWP) in the form of an intuitive visualization output. The workflow for simplified evaluation is illustrated through a case study that compares the GWP for selected combinations of material choice and construction systems.
Computational screening-LCA tools for early design stages
Budig, Michael (author) / Heckmann, Oliver (author) / Hudert, Markus (author) / Ng, Amanda Qi Boon (author) / Xuereb Conti, Zack (author) / Lork, Clement Jun Hao (author)
International Journal of Architectural Computing ; 19 ; 6-22
2021-03-01
17 pages
Article (Journal)
Electronic Resource
English
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