4.7 Article

Toward a national life cycle assessment tool: Generative design for early decision support

Journal

ENERGY AND BUILDINGS
Volume 267, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2022.112144

Keywords

Life Cycle Assessment (LCA); Early design stage; Parametric LCA; Generative design; Algorithms; Streamlined LCA

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This study aims to develop a national life cycle assessment (LCA) tool framework to support sustainable development and decision-making in the early design stage. The proposed implementation method based on generative design focuses on residential building exterior walls as the initial step of the tool, considering both embodied and operational impacts in the context of Egypt.
The life cycle assessment (LCA) has proven to be a reliable methodology for achieving sustainable development. The number of studies and attempts of integration at the building design stage is increasing. This study is aimed at developing a framework for a national LCA tool that considers Egyptian constraints and strikes a balance between embodied and operational impacts to serve as a decision-support tool for early design. This is achieved by first reviewing and analyzing LCA integration methods during the early design stages, emphasizing parametric methods. Second, studying the situation of LCA and energy efficiency in Egypt through publications, building codes, and residential building construction specifications. As a result of these steps, a suggested implementation method based on the generative design was developed as a tool framework that mainly focuses on residential building exterior walls as the first step of the national LCA tool to aid the design process and promote sustainable development. In addition to being the first initiative for a national LCA tool, the novelty of this work is the method of integration compared to other parametric LCA, which aims at optimizing both embodied and operational impact with respect to the Egyptian conditions while offering multiple solutions. (c) 2022 Elsevier B.V. All rights reserved.

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