A geometry-based decomposition method for energy prediction in early design stages of residential buildings

Purpose The purpose of the study is to develop a geometry-based energy estimation method for surrogate and metamodels to be used in the early design phase of buildings. Design/methodology/approach Optimizing building form and design variables in the early stages of the architectural design process, particularly during the conceptual phase, can significantly enhance overall design performance and energy efficiency at minimal cost. This study introduces a novel decomposition method for evaluating building energy performance by simplifying complex building forms into basic geometric shapes. Findings The developed method is applied to certain cases of design variation under specified boundary conditions, and the accuracy of heating and cooling energy loads is calculated with simulated energy models of these cases. As a result of the calculation, accuracy rates between 84.30 and 99.98% were founded. Originality/value This paper proposes a prediction model with a geometric identification method for an innovative geometry-based surrogate modeling method. This method also provides a way for artificial intelligence-based prediction models used in surrogate models to create a dataset and can be used in the training in future works.

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Institutions

Publication Details

Journal
Open House International
Published
2024-12-30
DOI
https://doi.org/10.1108/ohi-05-2024-0178
Citations
1
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
0.27
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article

A geometry-based decomposition method for energy prediction in early design stages of residential buildings

İbrahim Agah Taştemir, Enes Yaşa, Erdem Köymen
1 citations
Open House International
Building Energy and Comfort Optimization
0.27
article

A geometry-based decomposition method for energy prediction in early design stages of residential buildings

İbrahim Agah Taştemir, Enes Yaşa, Erdem Köymen
article en
1 citations

Abstract

Purpose The purpose of the study is to develop a geometry-based energy estimation method for surrogate and metamodels to be used in the early design phase of buildings. Design/methodology/approach Optimizing building form and design variables in the early stages of the architectural design process, particularly during the conceptual phase, can significantly enhance overall design performance and energy efficiency at minimal cost. This study introduces a novel decomposition method for evaluating building energy performance by simplifying complex building forms into basic geometric shapes. Findings The developed method is applied to certain cases of design variation under specified boundary conditions, and the accuracy of heating and cooling energy loads is calculated with simulated energy models of these cases. As a result of the calculation, accuracy rates between 84.30 and 99.98% were founded. Originality/value This paper proposes a prediction model with a geometric identification method for an innovative geometry-based surrogate modeling method. This method also provides a way for artificial intelligence-based prediction models used in surrogate models to create a dataset and can be used in the training in future works.

Open House International
İstanbul Sabahattin Zaim Üniversitesi (TR), Istanbul Technical University (TR)
Affordable and clean energy
Openalex Percentile: Top 40%
Building Energy and Comfort Optimization
0.27
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