Optimization of Exterior Wall Cladding Materials for Residential Buildings Using the Non-Dominated Sorting Genetic Algorithm II (NSGAII) Based on the Integration of Building Information Modeling (BIM) and Life Cycle Assessment (LCA) for Energy Consumption: A Case Study

Hossein Atashbar and Esmatullah Noorzai ()
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Hossein Atashbar: Department of Facility Management, Pars University of Architecture and Art, Tehran 1413915361, Iran
Esmatullah Noorzai: Department of Project and Construction Management, School of Architecture, University of Tehran, Tehran 1415564583, Iran

Sustainability, 2023, vol. 15, issue 21, 1-20

Abstract: In today’s construction industry, a topic of paramount importance is reducing energy consumption within buildings. This study endeavors to combine Life Cycle Assessment (LCA) and Building Information Modeling (BIM) through a multi-objective optimization algorithm to enhance the environmental efficiency of buildings. The core objective is the optimization of materials used in the building’s outer shell to effectively curtail operational energy consumption. To achieve this, we employed BIM modeling, parametric simulations with the Energy Plus engine, and Athena to assess the embodied energy in materials. The multi-objective optimization algorithm NSGAII was harnessed to determine the most suitable materials. The results derived from the LCA and BIM analyses illustrate that the selection of optimal materials for residential building facades in Iran can lead to a remarkable 40% reduction in annual average energy consumption. Furthermore, this approach contributes significantly to mitigating global warming potential (GWP). Experts and architects can apply this method to evaluate and select the best materials for various building components, especially in high-rise buildings.

Keywords: Building Information Modeling (BIM); Life Cycle Assessment (LCA); multi-objective optimization; embodied energy; operational energy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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