Calculation of the Green Building Index (GBI) for commercial buildings during the design phase by taking advantage of quantitative factors


Abstract views: 488 / PDF downloads: 165

Authors

  • Sattar Obayes Khafif Alkaraawi Student in Iran University of Science and Technology
  • Khanzadi, Mostafa Professor in a School of Civil Engineering, Iran University of Science and Technology, Narmak
  • Mohammed Assi Ahmed AL-DUJAIL Professor at Department of Ceramics Engineering and Building Materials - College of Materials Engineering/University of Babylon – Iraq

Keywords:

ASHRAE, green building index, BIM vision, IFC, BIM

Abstract

The evaluation of green building is very important to obtain a sustainable building that meets the requirements of agreed-upon evaluation systems and classification of building to accredited, silver, gold, or platinum. As we know, sustainable construction plays a major role in providing for current needs and securing the needs of future generations. This study aims to increase the number of evaluation points for the green building indicators during the design phase through some quantitative indicators to support the evaluation process and to increase the building evaluation points. In our results we have achieved about 13.552536 evaluation points out of a total of 15.17305 evaluation points, for five indicators, which are the cooling load index, the energy efficiency index, the water consumption index, the building transparency index, and the percentage of green coverage. These results will support the evaluation team in improving the classification of buildings, obtaining the approved building, and enhancing the accredited certificate according to the required specifications.

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Published

2023-06-11 — Updated on 2023-07-31

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How to Cite

Sattar Obayes Khafif Alkaraawi, Khanzadi, Mostafa, & Mohammed Assi Ahmed AL-DUJAIL. (2023). Calculation of the Green Building Index (GBI) for commercial buildings during the design phase by taking advantage of quantitative factors. Results in Nonlinear Analysis, 6(2), 18–52. Retrieved from https://nonlinear-analysis.com/index.php/pub/article/view/215 (Original work published June 11, 2023)