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<p>In designing eco-buildings, windows play a big part in minimizing the energy load. There has not been any easy-to-use software to speed up the process, even after many recent studies about environment-friendly window size, shading, position, and material. Thus, a single-family house with simple geometry in Kvemelto karti, Georgia, was simulated to introduce an alternative method to manage this gap. A building information model (BIM) was devised for this procedure through Autodesk Revit® due to its simplicity, popularity, interoperability and convenience among its users. Not to mention, the energy analysis tool (The Autodesk Insight 360) in Revit (BEM) displays the total energy load while, in this case, focusing on window size, position, material, and shading executed by Autodesk Green Building Studio®. The early energy analysis (the optimum window-to-wall ratio (WWR), the windows’ location in the wall, material, and shading) suggested by BEM does not give enough information to apply in the early stages of design and create a net-zero-energy building. The aim is to show the gap between data-driven from BEM and design strategies and to display the information required to be more detailed. For this purpose, after using Insight 360 (a web-based tool) for investigating window shades, material, and WWR, it has been concluded that there is a need for a more convenient way to automate the process in more depth. They could help to pick a viable widow shading, size, position, and material. Besides, choosing determined factors using just BEM is not practical because detailed characteristics of window factors as determining elements are not defined. This tool has its limitations.</p>
</abstract>

In designing eco-buildings, windows play a big part in minimizing the energy load. There has not been any easy-to-use software to speed up the process, even after many recent studies about environment-friendly window size, shading, position, and material. Thus, a single-family house with simple geometry in Kvemelto karti, Georgia, was simulated to introduce an alternative method to manage this gap. A building information model (BIM) was devised for this procedure through Autodesk Revit® due to its simplicity, popularity, interoperability and convenience among its users. Not to mention, the energy analysis tool (The Autodesk Insight 360) in Revit (BEM) displays the total energy load while, in this case, focusing on window size, position, material, and shading executed by Autodesk Green Building Studio®. The early energy analysis (the optimum window-to-wall ratio (WWR), the windows’ location in the wall, material, and shading) suggested by BEM does not give enough information to apply in the early stages of design and create a net-zero-energy building. The aim is to show the gap between data-driven from BEM and design strategies and to display the information required to be more detailed. For this purpose, after using Insight 360 (a web-based tool) for investigating window shades, material, and WWR, it has been concluded that there is a need for a more convenient way to automate the process in more depth. They could help to pick a viable widow shading, size, position, and material. Besides, choosing determined factors using just BEM is not practical because detailed characteristics of window factors as determining elements are not defined. This tool has its limitations.

Analyzing the energy analysis tool (The Autodesk Insight 360) of BIM during the early stages of the design process in terms of window factors in a single-family house

Logistics, Supply Chain, Sustainability and Global Challenges

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In designing eco-buildings, windows play a big part in minimizing the energy load. There has not been any easy-to-use software to speed up the process, even...

Analyzing the energy analysis tool (The Autodesk Insight 360) of BIM during the early stages of the design process in terms of window factors in a single-family house

Online veröffentlicht: 10. März 2023

Seitenbereich: 50 - 60

DOI: https://doi.org/10.2478/jlst-2023-0004

© 2022 Fatemeh BOLOORCHI, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.