4.8 Article

Integrated optimization with building information modeling and life cycle assessment for generating energy efficient buildings

Journal

APPLIED ENERGY
Volume 250, Issue -, Pages 1366-1382

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2019.05.101

Keywords

Building information modeling; Life cycle assessment; Energy consumption; Sustainable construction; Environmental impacts

Funding

  1. Coordination for the Improvement of Higher Education Personnel (CAPES) [001]
  2. CNPq (Brazilian National Council for Scientific and Technological Development)

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Energy consumption in buildings is a very important issue, where the operational demand is considered to be one of the highest amongst all other sectors of an economy. Moving towards energy efficient buildings is a key factor to achieve sustainability. A novel framework for integrating mathematical optimization, Building Information Modeling, and Life Cycle Assessment to enhance the operating energy efficiency of the resulting building designs adopted, along with reducing the difficulties associated with the construction of the building, in terms of cost of construction, is developed. The framework accommodates various parameters, via integrating mathematical optimization programming, Building Information Modeling, and Life Cycle Assessment to improve the building performance, identify alternative sustainable designs, and empower the decision-making process and sustainability in the construction sector. Through the developed optimization model, the examination of various alternatives for building components that make up the envelope of a residential building is undertaken. Insights gained from the results show that all components of building envelopes influence the energy consumption in buildings, particularly, exterior walls and windows. Impacts in terms of annual energy use intensity can be reduced by about 45%, life cycle energy use and cost can be enhanced by more than 50%, and environmental impacts such as acidification and global warming potential can be reduced by more than 30%, due to use of the proposed framework. This work indicates that sustainable building decisions can be achieved by optimizing the material selection and assessment of environmental impact via Building Information Modeling and life cycle assessment.

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