ABSTRACT
The evaluation of the structural response under different environmental conditions has been recognized as a critical factor for structural health monitoring reliability. The actual structural condition and relevant historical data must be accounted for up-to-date representation of the current physical system. Digital Twins (DTs) play a relevant role in continuously updating the construction condition assessment to support maintenance operations. The present chapter proposes a novel framework that integrates the 3D information model methodology and Internet of Things (IoT) systems. A common data platform for the visualization of vibration data is carried out. This platform, tested on a real case study located in Italy, is developed with the integration of IoT sensors and the Revit model. The ESEDRA steel structure at the Capitoline Museum will be analyzed in a two-step procedure: first, the digital 3D-BIM will be generated through the 3D laser scanning procedure (Cloud-To-BIM), using Autodesk Revit®, and Dynamo, a visual programming environment. In the second step, the BIM will be converted into a structural FE model, the so-called mechanical twin model (BIM to FEM), directly derived from the first one. When creating a DT model, an important point is a connection with measures coming from reality which in this case is an acceleration sensors system. Finally, the Particle Swarm Optimization algorithm will be applied to calibrate the FE mechanical model based on the elaboration of the vibration data. The development of a DT of a historical structure combining BIM and element model updating is proposed, pointing out its promising applicative perspectives for structural maintenance.
