Project Details
Projekt
Lifetime monitoring of structures by means of data assimilation in digital twin with artificial intelligence
Applicant
Professor Dr.-Ing. Yuri S. Petryna
Subject Area
Applied Mechanics, Statics and Dynamics
Structural Engineering, Building Informatics and Construction Operation
Structural Engineering, Building Informatics and Construction Operation
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 501728141
The main objective of the LEMOTRA project is the development of a consistent methodological framework for an intelligent digital representation of engineering structures, which provides permanent monitoring as a basis for predictive condition assessment and service life maintenance. To support the digital Building Information Models (BIM) of engineering structures that unify all existing data in condensed digital form, a Digital Twin for Structural Health Monitoring (SHM-DT) is to be developed here. It automatically merges the extensive and heterogeneous measurement data with physical and mathematical models of various complexity by means of data assimilation and Artificial Intelligence. Thus, SHM-DT will be able to provide a reliable prediction in real time for both the real structural behavior and the critical structural parameters such as stiffness or damage. On this basis, the meaningful condition indicators will be defined, determined and transferred to the digital BIM. Thus, the LEMOTRA project provides an important methodological headstone linking BIM and SHM for the purpose of life management of engineering structures. The most important innovative features of the project are methods for data assimilation in the digital twin and the use of Artificial Intelligence for automated measurement data evaluation and prediction of the structural state.The LEMOTRA project proposes a holistic concept for measurement-based monitoring and condition assessment of real engineering structures, defines interfaces between various subtasks and the relevant data, specifies its own methodological research areas and explains the selected research approaches. The own research objectives for the first phase are:-Methods for extracting physical models of different complexity and dimensionality from the digital Building Information Model,-Development of digital models for loading and environmental impact by means of monitoring and Artificial Intelligence,-Development of a consistent monitoring concept with reliable condition indicators,-Automated measurement data assimilation in the Digital Twin by means of Kalman filters and Artificial Intelligence,-Development of a scientific framework for a Digital Twin SHM-DT and its validation on a scaled representative laboratory structure,-Development of a Digital Twin SHM-DT for the demonstrator structure.
DFG Programme
Priority Programmes
