Image Integration in IFC Models: Leveraging Texture Mapping for Structural Data Visualization

Not all data derived from structural analysis or experimental testing can be effectively encoded using Industry Foundation Classes (IFC) properties or attributes, even if custom-made. In many cases, visual outputs—such as images—represent the only practical means of conveying complex analytical results. However, the current literature provides limited guidance on systematically integrating images within IFC models, with practitioners often relying on external formats or auxiliary technologies. This study investigates how the IFC standard supports the visualization of textures applied to geometric entities, focusing on the relevant classes and their interrelationships. Building on this theoretical framework, a prototype is developed within the Bonsai environment, leveraging Blender 4.5 and its add-on architecture. The prototype enables the creation of planar geometries in 3D space and the application of image-based textures, enabling visual information to be associated with IFC geometry through standard texture-mapping entities and an external image reference. A case study involving the visualization of structural testing results demonstrates the approach. By keeping the visual output registered to the model geometry, the approach has the potential to enhance analytical interpretation, communication among stakeholders, and data visualization within the built environment domain.