Digital Twins for Civil and Industrial Structures: Data-Physics Fusion-Driven Methods for Hazard Risk Management

Dear Colleagues,

The damage management of aging civil and architectural structures requires innovative approaches that integrate real-world monitoring with virtual simulations. Digital Twin (DT) technology, combining physics-based models with data-driven approaches, offers transformative solutions for in-service structures throughout their lifecycle-from normal operation to disaster response and recovery. This Special Issue explores comprehensive applications of DT technology: (1) 3D shape reconstruction and internal condition detection integrating visible and invisible infrastructure domains using advanced NDT methods including satellite remote sensing, UAV-LiDAR, acoustic techniques, and underwater sensing; (2) physics-based structural simulation and seismic analysis coupled with real situation for performance assessment; (3) hydraulic performance evaluation including flow analysis, leakage detection of pipeline water level management, and flood simulation for pump stations; (4) machine learning and AI for predictive maintenance, anomaly detection, knowledge discovery, and automated decision-making; (5) disaster management systems integrating rapid damage assessment, traffic management for emergency response, and recovery planning. We welcome original research, comprehensive reviews, and case studies demonstrating practical implementations in civil, architectural and industrial structures, such as buildings, bridges, roads, dams, headworks, channels, pipelines, and pump stations, etc. This Special Issue aims to establish DT as an essential framework for sustainable and resilient infrastructure management.

Prof. Dr. Tetsuya Suzuki
Prof. Dr. Ninel Alver
Dr. Kentaro Ohno
Guest Editors

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