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Integrating Parametric Analysis with Building Information Modeling to Improve Energy Performance of Construction Projects

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  • Mohammad K. Najjar

    (Program de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-901, Brazil)

  • Vivian W. Y. Tam

    (School of Computing, Engineering and Mathematics, Western Sydney University, Penrith, NSW 2751, Australia)

  • Leandro Torres Di Gregorio

    (Program de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-901, Brazil)

  • Ana Catarina Jorge Evangelista

    (School of Computing, Engineering and Mathematics, Western Sydney University, Penrith, NSW 2751, Australia)

  • Ahmed W. A. Hammad

    (Faculty of Built Environment, New South Wales University, Sydney, NSW 2052, Australia)

  • Assed Haddad

    (Program de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-901, Brazil)

Abstract

Buildings demand a significant amount of energy during their life cycles, hence, effective design measures need to be adopted to ensure efficient energy usage and management in buildings. This study proposes a framework based on various performance parameters to enable decision-makers utilizing standard procedures and software to empower the process of sustainable energy use and management in buildings, through a parametric analysis in different climatic conditions. Experimental design is adopted within the framework via the use of various performance parameters related to the building design (i.e., construction materials for exterior walls and roofs, as well as a set of window-to-wall ratios). Results indicate that climate data plays a fundamental role in the choice of design factors that are best suited for effective energy consumption in buildings. In particular, sub-type climate classifications, as opposed to the primary climate group, have a minor influence. Around 15% improvement in the energy consumption in buildings is noticed due to changes to the design factor such as the window-to-wall ratio. Insights that can be gleaned from this study include the impact of space area, exterior openings and material thickness and choice for the envelope of the building in all climate classifications, aiding in the design of low-energy buildings.

Suggested Citation

  • Mohammad K. Najjar & Vivian W. Y. Tam & Leandro Torres Di Gregorio & Ana Catarina Jorge Evangelista & Ahmed W. A. Hammad & Assed Haddad, 2019. "Integrating Parametric Analysis with Building Information Modeling to Improve Energy Performance of Construction Projects," Energies, MDPI, vol. 12(8), pages 1-22, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1515-:d:224896
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    References listed on IDEAS

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    Cited by:

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    2. Jitka Mohelníková & Miloslav Novotný & Pavla Mocová, 2020. "Evaluation of School Building Energy Performance and Classroom Indoor Environment," Energies, MDPI, vol. 13(10), pages 1-17, May.
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    5. Aniela Kaminska, 2019. "Impact of Heating Control Strategy and Occupant Behavior on the Energy Consumption in a Building with Natural Ventilation in Poland," Energies, MDPI, vol. 12(22), pages 1-18, November.
    6. Mikhail Demianenko & Carlo Iapige De Gaetani, 2021. "A Procedure for Automating Energy Analyses in the BIM Context Exploiting Artificial Neural Networks and Transfer Learning Technique," Energies, MDPI, vol. 14(10), pages 1-18, May.
    7. Faham Tahmasebinia & Ruifeng Jiang & Samad Sepasgozar & Jinlin Wei & Yilin Ding & Hongyi Ma, 2022. "Using Regression Model to Develop Green Building Energy Simulation by BIM Tools," Sustainability, MDPI, vol. 14(10), pages 1-25, May.

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