SPP 2388:  Hundred plus - Extending the Lifetime of Complex Engineering Structures through Intelligent Digitalization

• Subject Area: Construction Engineering and Architecture ; Geosciences ; Computer Science, Systems and Electrical Engineering ; Mathematics
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 461030501

The Priority Programme (SPP) 2388 “Hundred Plus” aims to substantially extend the service life of infrastructure through advanced maintenance strategies. Phase 1 emphasized the automated collection of structural data, the generation of precise 3D models, and the integration of real-time monitoring data into digital twins for continuous structural assessment. These foundational efforts enable early damage detection and the formulation of proactive maintenance measures. Building on the findings from Phase 1, the research in Phase 2 will focus on the development of condition indicators and of predictive models to enable more accurate and holistic structural condition assessments and the prediction of the structural service life. Moreover, methods for deriving specific handling recommendations will be developed to support predictive and prescriptive maintenance approaches. These methodologies will be validated on real-world structures such as the Nibelungen Bridge in Worms, which is the validation building of the SPP 2388, and e.g. the “openLab” bridge in Bautzen.The Coordination Project has essential role in fostering interdisciplinary collaboration and network building. It facilitates national and international cross-disciplinary networking among researchers within and beyond the SPP, supports early-career researchers, and implements targeted measures to promote gender equity. Furthermore, the dissemination of findings to both professional audiences and the public will be prioritized, to raise awareness of the relevance of the topic throughout society and increase the visibility of the SPP. The focus of the accompanying scientific research in the Coordination Project is on the integration of Structural Health Monitoring (SHM) systems developed across both phases into a collaborative framework, taking into account data quality and uncertainty. The data platforms will be further enhanced to improve system interoperability, incorporate automated metadata management, and ensure high data quality. Additionally, an intelligent knowledge management strategy will systematically organize structural records and monitoring data, ensuring their accessibility and utility. The Nibelungen Bridge as the central demonstrator provides a robust platform for the validation and practical application of the developed methodologies. These methods can be transferred to other engineering structures, thereby laying the foundation for sustainable advancements in infrastructure maintenance practices in the future.

• DFG Programme: Priority Programmes
• International Connection: China, USA

Projects

• Automated digital building modelling from heterogeneous as-built data taking into account their quality characteristics - ADIBAMOD-Q (Applicant Neitzel, Frank )
• Automatic data-driven modeling and H2/H-infinity- norm-based dimension reduction of process-oriented and cooperative systems for SHM condition analysis with methods of system identification and machine learning on exposed structures - Phase two (Applicant Lenzen, Armin )
• Coordination Funds (Applicant Marx, Steffen )
• Damage detection and evaluation based on combined multi-property sensor networks and high-fidelity numerical system identification (Applicants Lowke, Dirk ;  Wüchner, Roland )
• Data driven model adaptation for identifying stochastic digital twins of bridges (Applicants Unger, Jörg F. ;  Weiser, Martin )
• Data-informed probabilistic prediction of concrete creep considering the hygral and mechanical history of existing structures (CreepStatus) (Applicant Haist, Michael )
• Design methodology for cross-life structural health monitoring with unknown damage process – Optimized sensor networks (Applicant Marx, Steffen )
• Digital coupling of multiscale analyses in modelling and monitoring (Applicants Könke, Carsten ;  Zabel, Volkmar )
• Digital twin as an intermediary between in-situ damage detection and global structural analysis (Applicant Unglaub, Julian )
• Intelligent resilience analysis for infrastructure considering uncertain real-time data (Applicants Beer, Michael ;  Broggi, Matteo )
• Lifetime monitoring of structures by means of data assimilation in digital twin with artificial intelligence - LEMOTRA (Applicant Petryna, Yuri S. )
• Measurement-based condition assessment, load identification, and service life prediction of prestressed concrete bridges with low shear reinforcement ratios using the 2D-FOS-methode (Applicant Claßen, Martin )
• Method development and evaluation scheme for cross-life linkage of structural health monitoring data and exiting knowledge via deep transfer learning (Applicant Herrmann, Ralf )
• Modeling of civil engineering structures with particular attention to incomplete and uncertain measurement data by using explainable machine learning (MoCES) (Applicant Reiterer, Alexander )
• Monitoring data driven life cycle management based on adaptive, AI-supported corrosion prediction for reinforced concrete structures under combined impacts (Applicants Leusmann, Thorsten ;  Lowke, Dirk ;  Wessels, Henning )
• Optical 3D-bridge-inspect: Innovative inspection of complex infrastructure combining very high-resolution UAV-borne imagery and structured-light scanning (Applicants Bestmann, Ulf ;  Gerke, Markus )
• Optical 3D measurement techniques for generation, revision and monitoring of digital twins of complex building structures (Applicant Maas, Hans-Gerd )
• Pattern detection of internal tendon rupture on concrete surfaces (Applicant Sanio, David )
• Quality assurance of digital twins based on mathematical abstraction and tangle-based blockchain architectures (Applicant Smarsly, Kay )
• Scan2SAM - Data-driven generation of structural systems from 3D point clouds and formalized knowledge for VPINN-based structural forecasting (Applicants Blankenbach, Jörg ;  Klinkel, Sven )
• Spatio-B-RAG - Methods for Knowledge Discovery in Spatially Annotated Heterogeneous Data for Predictive Damage Assessment in Bridge Structures (Applicant Beetz, Ph.D., Jakob )
• SpatioLink: Spatio-temporal links between heterogenous Information Resources in infrastructure (Applicant Beetz, Ph.D., Jakob )
• Stochastic Digital Twins of Bridges for Computing Condition Indicators under Model Form Uncertainty (Applicants Unger, Jörg F. ;  Weiser, Martin )
• Structural Health Information Patterns (SHIPs) for analysing the change in condition of bridges in an automated digital twin - [TwinSHIP] (Applicant Braml, Thomas )
• Structural Health Monitoring with model based damage detection using nonlinear model adaption and Artificial Intelligence methods (Applicant Schnellenbach-Held, Martina )

• Spokesperson: Professor Dr.-Ing. Steffen Marx