Project Details
Projekt
Digital twin as an intermediary between in-situ damage detection and global structural analysis
Applicant
Dr.-Ing. Julian Unglaub
Subject Area
Structural Engineering, Building Informatics and Construction Operation
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 501823987
If structures are monitored from the very beginning (Structural Health Monitoring, SHM), all information on damage prognosis is available. For existing structures, this is not always the case for the past. SHM on real structures aims at determining critical details on the basis of deterministic or probabilistic considerations. Measurements are mainly made with strain gauges, displacement transducers and accelerometers. Especially deterministic considerations require a lot of experience in the selection of measuring points. In addition, degradation of the component must have occurred to a certain extent: cracks, corrosion and spalling, so that these can be detected during visual inspections. The particular difficulty in developing suitable models to describe the condition of the structure is that structures are highly variable in terms of building materials, construction method, support structure, loading, age and condition, and are subject to permanent change. Therefore, the information is scattering, uncertain, and/or also highly time-varying. However, the progression of damage to a critical condition can take several decades. The information that accumulates on a structure over the years has so far had a decentralized character. Linkage has been inadequate, many tasks are performed redundantly, and knowledge already gained can be overlooked. Linking could be done with the methods of Building Information Modeling (BIM), which has been introduced in recent years. So far, however, the special requirements of SHM have only been investigated in rudimentary form, and complete integration has not yet been achieved. Issues related to the handling of complex measurement systems operating at different scales have not yet been sufficiently investigated. Therefore, the aim of this research project is to investigate fundamental questions concerning the digital connection of local in-situ damage detection methods and conventional SHM via digital twin (DT). The concept of DT, consisting of components with reduced order, which is established in aircraft construction, is to be adapted and extended for bridge structures. The digital connection of SHM, in-situ DIC measurements and DT is done via optimal classification trees with hyperplane splits (OCT-H) to ensure comprehensible machine learning. The particular challenge in further developing the method for civil engineering is that the damage processes leading to aging and wear in structures are physical and chemical processes that need to be captured at different scales (material, component, structure level).
DFG Programme
Priority Programmes
