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Multi-objective optimization of building envelope design for life cycle environmental performance

Abstract The building envelope incorporates significant amount of construction materials and is a key determinant of the embodied energy and environmental impacts in buildings. It is also a mediator between indoor and outdoor environmental conditions and has significant impacts on operational energy use in many types of buildings. The present article utilizes a multi-objective optimization algorithm to explore optimum building envelope design with respect to energy use and life cycle contribution to the impacts on the environment in a low-rise office building in Seattle, Washington. Design inputs of interest include insulation material, window type, window frame material, wall thermal resistance, and south and north window-to-wall ratios (WWR). The simulation tool eQuest 3.65 is used to assess the operational energy use, while Life Cycle Assessment (LCA) methodology and Athena IE are used to estimate the environmental impacts. Also, a hybrid artificial neural network and genetic algorithm approach is used as the optimization technique. The environmental impact categories of interest within the LCA include: global warming, acidification, eutrophication, smog formation, and ozone depletion. The results reveal that the optimum design scenario incorporates fiberglass-framed triple-glazed window, about 60% south WWR, 10% north WWR, and R-17 insulation.
- Islamic Azad University of Falavarjan Iran (Islamic Republic of)
- Research Institute of Petroleum Industry Iran (Islamic Republic of)
- Islamic Azad University Central Tehran Branch Iran (Islamic Republic of)
- Islamic Azad University Central Tehran Branch Iran (Islamic Republic of)
- The University of Texas at San Antonio United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).159 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
