In this project, we propose the fully automated method outlined above and validate it with the help of several complex pilot projects. Existing software tools, including CAALA, are used to calculate the life cycle costs and life cycle assessment of renovation scenarios, thus ensuring practical implementation. The point clouds of the pilot projects are translated and enriched directly into a common data format for Building Energy Models (BEM) without the detour of manual post-modeling. The proposed method should make it possible in future to record existing buildings cost-effectively and time-efficiently and to estimate automated refurbishment scenarios. This will meet the growing demand for refurbishment of existing buildings using innovative digital methods.

The aim of this project is to develop a robust, automated method for the calculation of life cycle analyses (costs and ecology) of existing buildings using point clouds as input data. The focus is neither on the creation of point clouds nor on the definition of renovation scenarios, but rather on bridging the gap that currently exists between point clouds and the import of semantic 3D models for LCA calculations.

The proposed automated processing steps therefore comprise a geometric transformation of the point cloud into a 3D surface model, followed by a semantic classification of the individual surfaces into thermal layers; in addition, the respective materials are to be recorded by assuming the surface elements according to building age classes.

Awards

• Finalist DGNB Sustainability Challenge 2024 (Kategorie Forschung)

In collaboration with:

• Stiftung Bayerisches Baugewerbe

Publications

• Forth, K.; Noichl, F.; Borrmann, A.: LCA Calculation of Retrofitting Scenarios using Geometric Model Reconstruction and Semantic Enrichment of Point Clouds and Images. Proc. of the ASCE International Conference on Computing in Civil Engineering 2023, Corvalis, Orgaon, USA, 2024; DOI: 10.1061/9780784485231.047
• Selimovic, E.; Noichl, F.; Forth, K.; Borrmann, A.: Retrofitting potential of building envelopes based on semantic surface models derived from point clouds, In: Journal of Facade Design and Engineering 10 (2), 2022; DOI: 10.47982/jfde.2022.powerskin.8