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Simulation-Based Life Cycle Assessment for Office Building Façade: a Case Study of the Leadenhall Building in London

EasyChair Preprint no. 8877

8 pagesDate: September 25, 2022

Abstract

High-rise glazing systems are among the most important components affecting energy efficiency. Through the lens of Life Cycle Assessment, glass has always been an unlikely material for large buildings due to its considerable energy consumption throughout the pre-use and post-use phases. Moreover, the use of high-tech materials has a negative impact on the environment. Therefore, the present study aims to assess a comparative life cycle of four different glazing system technologies (BIPV, smart glass, low-E, and double glazing) representing the most used commercial high potential glazing systems. The next step has been optimized for the Leadenhall iconic tower as the case study. In this analysis, energy simulation is combined with life cycle assessment to investigate the environmental impacts. ZEB-COM tool, Rhino®, and Grasshopper® have been used to calculate emissions, 3D modeling, and energy modeling, respectively. The results reveal that BIPV achieved 37% of total energy-saving and stood first. A hybrid solution (two glazing systems) has been proposed to eliminate negative aspects and increase livability. Although it can generate almost 30% less energy than the complete BIPV installation, with a specific design by the authors, it can cover aesthetic concerns in this system and compensates for 27% of the total energy demand of the Leadenhall project.

Keyphrases: comparative analysis, Glazing System, high-rise, Leadenhall building, Life Cycle Assessment

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:8877,
  author = {Tahmineh Akbarinejad Khameneh and Zahir Barahmand and Gamunu Samarakoon},
  title = {Simulation-Based Life Cycle Assessment for Office Building Façade: a Case Study of the Leadenhall Building in London},
  howpublished = {EasyChair Preprint no. 8877},

  year = {EasyChair, 2022}}
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