Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point Clouds
To meet the climate goals of the Paris agreement, the focus on energy efficiency needs to be shifted to increase the retrofitting rate of the existing building stock. Due to the lack of usable information on the existing building stock, reasoning about the retrofitting potential in early design sta...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Stichting OpenAccess
2022-12-01
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| Series: | Journal of Facade Design and Engineering |
| Subjects: | |
| Online Access: | https://jfde.eu/index.php/jfde/article/view/243 |
| _version_ | 1797870213251727360 |
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| author | Edina Selimovic Florian Noichl Kasimir Forth André Borrmann |
| author_facet | Edina Selimovic Florian Noichl Kasimir Forth André Borrmann |
| author_sort | Edina Selimovic |
| collection | DOAJ |
| description |
To meet the climate goals of the Paris agreement, the focus on energy efficiency needs to be shifted to increase the retrofitting rate of the existing building stock. Due to the lack of usable information on the existing building stock, reasoning about the retrofitting potential in early design stages is difficult. Therefore, deconstructing and building new is often regarded as the more reliable and economical option. Digital methods are missing or not robust enough to capture and reconstruct digital models of existing buildings efficiently and automatically derive reliable decision-support about whether demolition and new construction or retrofitting of existing buildings is more suitable. This paper proposes a robust, automated method for calculating existing buildings' life cycle assessments (LCA) using point clouds as input data. The main focus lies in bridging the gap between point clouds and importing semantic 3D models for LCA calculation. Therefore, the automation steps include a geometric transformation from point cloud to 3D surface model, followed by a semantic classification of the surfaces to thermal layers and their materials by assuming the surface elements by building age class.
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| first_indexed | 2024-04-10T00:23:47Z |
| format | Article |
| id | doaj.art-f8d7caeddd444d0d9e670a653f1cdf4c |
| institution | Directory Open Access Journal |
| issn | 2213-302X 2213-3038 |
| language | English |
| last_indexed | 2024-04-10T00:23:47Z |
| publishDate | 2022-12-01 |
| publisher | Stichting OpenAccess |
| record_format | Article |
| series | Journal of Facade Design and Engineering |
| spelling | doaj.art-f8d7caeddd444d0d9e670a653f1cdf4c2023-03-15T13:52:55ZengStichting OpenAccessJournal of Facade Design and Engineering2213-302X2213-30382022-12-0110210.47982/jfde.2022.powerskin.8Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point CloudsEdina Selimovic0Florian Noichl1Kasimir ForthAndré Borrmann2Technical University of Munich Technical University of Munich Technical University of Munich To meet the climate goals of the Paris agreement, the focus on energy efficiency needs to be shifted to increase the retrofitting rate of the existing building stock. Due to the lack of usable information on the existing building stock, reasoning about the retrofitting potential in early design stages is difficult. Therefore, deconstructing and building new is often regarded as the more reliable and economical option. Digital methods are missing or not robust enough to capture and reconstruct digital models of existing buildings efficiently and automatically derive reliable decision-support about whether demolition and new construction or retrofitting of existing buildings is more suitable. This paper proposes a robust, automated method for calculating existing buildings' life cycle assessments (LCA) using point clouds as input data. The main focus lies in bridging the gap between point clouds and importing semantic 3D models for LCA calculation. Therefore, the automation steps include a geometric transformation from point cloud to 3D surface model, followed by a semantic classification of the surfaces to thermal layers and their materials by assuming the surface elements by building age class. https://jfde.eu/index.php/jfde/article/view/243retrofitting potentialLCApoint cloudsemantic enrichment |
| spellingShingle | Edina Selimovic Florian Noichl Kasimir Forth André Borrmann Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point Clouds Journal of Facade Design and Engineering retrofitting potential LCA point cloud semantic enrichment |
| title | Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point Clouds |
| title_full | Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point Clouds |
| title_fullStr | Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point Clouds |
| title_full_unstemmed | Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point Clouds |
| title_short | Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point Clouds |
| title_sort | retrofitting potential of building envelopes based on semantic surface models derived from point clouds |
| topic | retrofitting potential LCA point cloud semantic enrichment |
| url | https://jfde.eu/index.php/jfde/article/view/243 |
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