Special Track 04 - Bridges, Spatial and High-rise Structures: Dynamic Identification and Modal-based Monitoring
The structural assessment and continuous monitoring of bridges, spatial and high-rise structures play a fundamental role in guaranteeing safety, serviceability, and resilience. Within this framework, Operational Modal Analysis (OMA) and modal-based Structural Health Monitoring (SHM) have emerged as powerful approaches for the dynamic identification of large-scale civil structures, enabling both the characterization of their global dynamic behavior and the long-term tracking of their structural condition under operational conditions.
This session is intended to bring together recent advances, innovative methodologies, and real-world applications related to OMA and modal-based SHM of long-span bridges, high-rise and spatial structures, with particular emphasis on long-term monitoring strategies and dynamic identification in the presence of environmental and operational variability.
Suitable topics include, but are not limited to:
- Finite element model updating based on vibration data for improved structural identification and performance assessment
- Implementation of monitoring-informed digital twins for long-span bridges ,high-rise buildings and spatial structures, supporting dynamic behavior replication, interpretation of monitoring data, and predictive maintenance decisions under variable operating conditions
- Long-term modal parameter tracking and uncertainty quantification under operational conditions
- Novel modal-based damage-sensitive features and indicators for early detection and localization of structural degradation
- Innovative procedures for modal feature identification and decision support
- Data normalization techniques to mitigate the influence of environmental and operational variability on modal parameters.
Keywords: Bridges, High-rise Buildings, Spatial Structures, Structural Identification, Structural Health Monitoring, Machine Learning, Digital Twin
Track chairs
Paolo Borlenghi, Politecnico di Milano
Ilenia Rosati, National Research Council of Italy
Wei-Hua Hu, Harbin Institute of Technology
