Submission Deadline: 30 April 2027 View: 100 Submit to Special Issue
Assoc. Prof. Qi-Ang Wang
Email: qawang@cumt.edu.cn
Affiliation: School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, China
Research Interests: structural health monitoring, reliability assessment, intelligent sensing, structural safety management and operation & maintenance
Assoc. Prof. Shukui Liu
Email: skliu@cumt.edu.cn
Affiliation: School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, China
Research Interests: structural damage condition perception and intelligent identification, advanced sensing and inspection technologies
Complex engineering infrastructures (e.g., bridges, tunnels, buildings, wind turbines, etc.) face persistent threats from multi-hazard loads, leading to progressive damage and safety risks. Traditional maintenance methods are inefficient and costly, while emerging data-driven and physics-informed approaches offer new pathways to monitor structural health, predict remaining useful life, and optimize operational decisions. This field is critical to ensuring the resilience and sustainability of critical infrastructure, supporting global smart asset management goals. This Special Issue aims to gather cutting-edge advances in structural damage identification and intelligent operation & maintenance decision-making, bridging research and practice. It welcomes contributions on novel damage detection methods, data-physics fusion models, life-cycle prediction, uncertainty-aware maintenance strategies, and real-world applications in large-scale engineering structures, to drive innovation and practical deployment for safer, more sustainable infrastructure.
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