Associated Partner

The research of the Institute of Steel Construction at TU Braunschweig focuses, within the field of Structural Health Monitoring (SHM), in particular on identifying fatigue damage in steel bridges based on strain and deformation measurements. In addition to using various measurement methods (including strain gauges, distributed fiber-optic sensors, and digital image correlation), different simulation approaches for determining the remaining service life are investigated. With its focus on the material steel, this research complements SPP100+, which focuses on concrete/massive structures, in an ideal way. Furthermore, cross-material exchange on measurement technology is carried out within Cluster A Schadensdetektions-gestützte Zustandsbewertung.
 

The team of the Institute for Digital and Autonomous Construction (IDAC) conducts interdisciplinary research on digitalization in engineering. By integrating sensing, control, and information technologies, we work at the interfaces between civil/environmental engineering and computer science, robotics, mathematics, materials science, and electrical engineering. Application areas include, among others, cyber-physical systems, intelligent structures, smart sensing and actuation, cognitive buildings, additive manufacturing, construction robotics, as well as information modeling and AI methods for Industry 4.0 and IoT applications. Content-related focal points relevant to SPP100+ include, among others, digital twins; AI-enabled structural health monitoring (SHM) including sensor fault management; AIoT architectures and scalable data platforms; and robotics-assisted inspection and construction progress tracking up to facility information modeling. In this way, we provide robust, explainable, and scalable monitoring and decision-making approaches across the entire life cycle of civil engineering structures, thereby making a direct contribution to the objectives of SPP100+.

Relevant Projects

• Digitalization of earth-based construction processes, Deutsche Forschungsgemeinschaft (DFG), https://www.tuhh.de/idac/research/decentralized-digital-twins
• Multi-robot collaboration for monitoring and inspection of civil engineering structures, Deutsche Forschungsgemeinschaft (DFG), https://www.tuhh.de/idac/research/multi-robot-collaboration
• Coupling climate models and indoor climate models for climate-informed engineering, Deutsche Forschungsgemeinschaft (DFG), https://www.tuhh.de/idac/research/climate-imformed-engineering
• Security issues in the transmission of structural health monitoring data from energy networks in an explainable AI environment, North Atlantic Treaty Organization (NATO), https://www.tuhh.de/idac/research/secure-data-transmission
• Robot-based inspection of civil infrastructure using frame semantics and linguistic metamodels, Deutsche Forschungsgemeinschaft (DFG), https://www.tuhh.de/idac/research/frame-semantics
• Generating and using digital twins of sewer infrastructure for increased operational availability and resilience ("KaSyTwin"), Bundesministerium für Digitales und Verkehr (BMDV): mFund, https://www.tuhh.de/idac/research/kasytwin
• Modeling and design concepts for digital roads, Deutsche Forschungsgemeinschaft (DFG), https://www.tuhh.de/idac/research/digital-roads

The Institute of Geodesy and Photogrammetry (IGP) and the Institute of Flight Guidance (IFF) at TU Braunschweig have been cooperating for a long time in projects on drone-based optical surveying of infrastructure structures. IGP, led by Prof. Markus Gerke, is responsible for data processing and analysis, while Dr.-Ing. habil. Ulf Bestmann and the IFF Navigation working group handle drone operations. In addition to millimeter-accurate geometric acquisition, another key focus is automated damage detection in orthomosaic images.

In Phase I of the SPP, we developed methods for area-wide deformation measurement of bridges and for crack detection, and demonstrated them in several experiments.

Relevant Projects: Optische 3D-Brücken-Inspektion: Innovative Inspektion komplexer Infrastruktur durch die Kombination von hochaufgelösten UAV-gestützten Bildern und Streifenlicht-Aufnahmen – SPP 100+ Phase I. https://www.tu-braunschweig.de/igp/projekte/3d-bridgeinspect