Structural Health Monitoring and Safety Evaluation for Dams
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".
Deadline for manuscript submissions: 30 August 2026
Special Issue Editors
2. College of Water Resources & Hydropower, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
Interests: structural health monitoring and intelligent safety assessment for dams
2. College of Water Resources & Hydropower, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
Interests: structural damage monitoring and stability assessment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Structural health monitoring (SHM) and safety evaluation are essential for ensuring the long-term performance and risk control of dam infrastructures under complex environmental and operational conditions. With the rapid development of sensing technologies, data acquisition systems, and computational methods, dam safety assessment is evolving from experience-based analysis toward data-driven, intelligent, and integrated frameworks. However, challenges remain in multi-source data fusion, anomaly identification, uncertainty quantification, and the coupling of physical mechanisms with advanced data analytics.
This Special Issue aims to provide a comprehensive platform for presenting recent advances in SHM technologies, data-driven modeling, and safety evaluation methods for dams. It will focus on innovative sensing techniques, intelligent data processing algorithms, and integrated assessment frameworks that enhance the accuracy, robustness, and interpretability of dam safety analysis. Contributions addressing the integration of artificial intelligence, machine learning, digital twins, and numerical modeling with traditional dam engineering knowledge are particularly encouraged.
Topics of interest include, but are not limited to, multi-source sensing and monitoring systems, deformation and seepage analysis, reservoir bank slope safety and the impacts of slope instability on dam safety, anomaly detection and early warning, reliability- and risk-based safety evaluation, digital twin-enabled dam management, and practical applications in real-world dam projects. By bringing together interdisciplinary research and engineering practices, this Special Issue aims to advance the state of the art in dam safety monitoring and promote the development of intelligent, resilient, and sustainable dam infrastructures.
Dr. Han Zhang
Dr. Jingren Zhou
Guest Editors
Manuscript Submission Information
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Keywords
- structural health monitoring
- dam safety evaluation
- reservoir bank slope safety
- multi-source sensing
- data fusion
- anomaly detection
- artificial intelligence
- monitoring models
- digital twin
- risk analysis
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