Work

Accelerating circular cities with semi-automatic building information modeling for existing buildings

Year: 2025

Type: article

Abstract: : The lack of high-granularity information on existing building stock impedes efficient material reuse and recycling, which is essential for promoting the circular economy in the building industry. Building Information Modeling (BIM) can fill this gap by offering detailed information about the material composition of buildings. However, creating BIM models for existing buildings remains costly, time-consuming, and labor-intensive. This study proposes a novel method for accelerating the creation of georeferenced BIM models by integrating heterogeneous mass data and domain knowledge about building construction. The method achieves 95% accuracy in estimating material intensities for external load-bearing timber frame walls and roof components. This approach provides valuable insights for stakeholders, facilitating the transition to circular cities by supporting material stock analysis at both macro and micro levels. By expediting the BIM modeling process, this method enhances the granularity of material stock analysis, supports efficient material reuse and recycling, and promotes urban sustainability.

Source: Journal of Cleaner Production

DOI: 10.1016/j.jclepro.2025.145783

Authors: Georgios Triantafyllidis, Daniel Beat Müller, Steffen Wellinger, Lizhen Huang

Institution: Norwegian University of Science and Technology

Language: English

Topic: BIM and Construction Integration

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Responsible consumption and production, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,660