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  4. Intelligente digitale Methoden zur Verlängerung der Nutzungsdauer der Nibelungenbrücke
 
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Intelligente digitale Methoden zur Verlängerung der Nutzungsdauer der Nibelungenbrücke

Publikationstyp
Journal Article
Date Issued
2025
Sprache
German
Author(s)
Kang, Chongjie  
Andrés Arcones, Daniel  
Becks, Henrik  
Beetz, Jakob  
Blankenbach, Jörg  
Classen, Martin  
Degener, Sebastian
Eisermann, Cedric  
Göbels, Anne  
Hegger, Josef  
Hermann, Ralf
Kähler, Philipp  
Peralta Abadia, Patricia  orcid-logo
Digitales und autonomes Bauen B-1  
Petryna, Yuri  
Schnellenbach-Held, Martina  
Schulz, Oliver  
Smarsly, Kay  
Digitales und autonomes Bauen B-1  
Fatih Sönmez, Mehmet
Sprenger, Bjarne  
Unger, Jörg F.  
Vassilev, Hristo  
Weiser, Martin  
Marx, Steffen  
TORE-URI
https://hdl.handle.net/11420/60538
Journal
Beton- und Stahlbetonbau  
Start Page
1
End Page
18
Citation
Beton Und Stahlbetonbau: 1-18 (2025)
Publisher DOI
10.1002/best.70070
Scopus ID
2-s2.0-105025350906
Publisher
Ernst und Sohn
Intelligent digital methods for extending the service life of the Nibelungen Bridge. To extend the service life of structures while maintaining their structural safety and functionality, effective monitoring and maintenance concepts are necessary. Within the scope of the Priority Program 2388 “Hundred Plus – Extending the Service Life of Complex Structures through Intelligent Digitalization” (SPP 100+), funded by the German Research Foundation (DFG), interdisciplinary methods including digital models, digital linkages, and condition indicators, have been investigated and validated on the Nibelungen Bridge in Worms. First, two structural health monitoring systems and their combination are described in detail, with particular focus on the fusion of accelerometer data. Subsequently, innovative data-driven simulation methods are presented to determine the complete temperature field of the bridge superstructure. In addition, various numerical solutions covering different element types and levels of detail are introduced. Finally, methods for managing knowledge about the bridge's condition are presented. The methods were developed relatively independently of each other and validated at the NBW. In the next step, all methods will be integrated to support the maintenance of the NBW.
Subjects
digital twin
FE-model
Nibelungen Bridge Worms
predictive maintenance
recalculation
structural health monitoring
traffic infrastructure
DDC Class
600: Technology
624: Civil Engineering, Environmental Engineering
624.1: Structural Engineering
690: Building, Construction
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