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A framework for semi-automated creation of Building Information Models for existing buildings

Autor(en):

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Journal of Physics: Conference Series, , n. 19, v. 2600
Seite(n): 192015
DOI: 10.1088/1742-6596/2600/19/192015
Abstrakt:

The environmental impact of the building sector can be significantly mitigated by reusing materials and components from the existing building stock. Building Information Modelling (BIM) methodology can serve as a potent tool for the documentation, management of existing buildings, and foster effective collaboration among different stakeholders in the value chain of the building sector. In addition, by providing information about the building’s structure, materials, and systems, BIM enables more informed decision-making regarding potential renovations, retrofits, and repurposing. However, developing BIM models for existing buildings is a labour and time-intensive task. There is therefore the need to investigate possible ways to automate the data acquisition and the creation of BIM models. By using the extracted alphanumerical information from two databases in a BIM and Visual Programming Language environment, we develop a workflow that can read and transform this information, which is given as input, into a parametric BIM model. We then discuss the data availability and accessibility from those databases and what data requirements are still needed to achieve higher granularity for the BIM models. Finally, we develop a workflow, and we provide suggestions for further research and data integration. A shift into a circular economy model in the building sector could support reducing the environmental impact that the sector is causing. Developing BIM models by using a simpler method, could potentially facilitate informed decision-making for the reuse, recycling, and repurposing of building-materials and elements.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1088/1742-6596/2600/19/192015.
  • Über diese
    Datenseite
  • Reference-ID
    10777652
  • Veröffentlicht am:
    12.05.2024
  • Geändert am:
    12.05.2024
 
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