Record link: 
http://hdl.handle.net/20.500.12708/222192
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Title: 
Scan2Beams: Moving Towards Automated Modelling and Analysis of Structural Industrial Building Stock
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Citation: 
Reisinger, J., Marin, D., Rufinatscha, P., & Kan, P. (2025). Scan2Beams: Moving Towards Automated Modelling and Analysis of Structural Industrial Building Stock. In Proceedings of the 2025 European Conference on Computing in Construction. 2025 European Conference on Computing in Construction EC3, Porto, Portugal. https://doi.org/10.35490/EC3.2025.194
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Publisher DOI: 
10.35490/EC3.2025.194
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Reisinger, Julia 
Marin, Diana 
Rufinatscha, Philipp 
Kan, Peter 
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Organisational Unit: 
E210-01 - Forschungsbereich Integrale Planung und Industriebau 
E193-03 - Forschungsbereich Virtual and Augmented Reality 
E057-16 - Fachbereich Center for Geometry and Computational Design 
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Published in: 
Proceedings of the 2025 European Conference on Computing in Construction 
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ISBN: 
978-9-083451-31-2
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Volume: 
6
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DOI of the book: 
10.35490/EC3.2025
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Date (published): 
2025
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Event name: 
2025 European Conference on Computing in Construction EC³ 
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Event date: 
14-Jul-2025 - 17-Jul-2025
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Event place: 
Porto, Portugal
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Number of Pages: 
7
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Peer reviewed: 
Yes
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Keywords: 
Scan-to-FEM; industrial building; photogrammetry; structural analysis of building stock
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Abstract: 
Manual creation of as-built models for Finite Element Method (FEM) analysis is labour-intensive and error-prone, hindering effective reuse of building structures. SCAN-to-FEM technology automates the capture and analysis of building stock, lacking efficient methods for converting point cloud or photogrammetry data into analytical FEM models of skeleton structures. This paper introduces Scan2Beams, a framework for transforming 3D photogrammetry data of industrial buildings into parametric structural meshes of the load-bearing structure. Validated through a use case, Scan2Beams enables integration of point cloud data into structural analysis workflows and eliminates manual modelling. Future research includes automated joint behavior recognition and retrofitting suggestions.
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Project title: 
RE:STOCK INDUSTRY - Digitaler Framework zur kreislauforientierten Wiederverwendung von Bestandstragwerken für vertikale Produktionen: 907638 (FFG - Österr. Forschungsförderungs- gesellschaft mbH) 
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Research Areas: 
Modeling and Simulation: 100%
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Science Branch: 
2011 - Bauingenieurwesen: 50%
1020 - Informatik: 50%
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Appears in Collections:
Conference Paper

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