Automatic integration of building data into large-scale numerical simulations

The integration of reliable and accurate building information into large-scale numerical simulations of infrastructure and its interactions with the environment under human and nature-induced stressors is crucial for achieving a realistic and comprehensive understanding of mutual effects. Traditionally, building data is generated manually from the as-built drawings, which are often either not readily available or difficult to obtain at a large scale. Moreover, the resolution and the accuracy of the building data are inherently limited by the manual transfer process, introducing potential errors and inefficiencies. This work proposes a practical, automated approach to streamline the pre-processing workflow by generating the building models directly from a public cloud data source. The proposed process significantly reduces errors, enhances productivity, and provides users with precise control over the resolution of building discretization. This methodology has been successfully applied to a coupled tunnel simulation model, which incorporates detailed building meshes and is analyzed using the finite element method with the CutFEM framework. In the second example, the workflow is demonstrated for generating simulations of the wind flow around the buildings. Finally, large-scale seismic analysis using the city model is conducted to further demonstrate the robustness of the proposed approach. By implementing the proposed automatic framework, the modeling process, which traditionally takes several days with a manual, human-involved approach, can be reduced to just a few minutes. The proposed approach is general and can be applied to accurately incorporate buildings into any large-scale numerical simulation of interactions between buildings and the environment. • A novel automatic method to generate building models from public data source. • Significantly reduces errors and boosts modeling productivity. • Applicable for accurate integration into large-scale building-environment simulations.