Submission Deadline: 30 January 2026 View: 635 Submit to Special Issue
Prof. Xinqun Zhu
Email: xinqun.zhu@uts.edu.au
Affiliation: School of Civil and Environmental Engineering, University of Technology Sydney, 81 Broadway, Broadway, NSW, 2007, Australia
Research Interests: structural health monitoring, physics-informed machine learning, advanced signal processing and sensor technology
Prof. Na Yang
Email: nyang@bjtu.edu.cn
Affiliation: School of civil Engineering, Beijing Jiaotong University, Beijing, 100082, China
Research Interests: structural health monitoring, ancient timber structure, ancient masonry structure, structural condition assessment
Civil infrastructures are deteriorating due to aging and continuous operational and environmental loads. Structural condition monitoring and damage identification are critical to prevent catastrophic structure collapse and provide quantitative data for effective and economic lifecycle structural management and maintenance. In recent years, there have been significant advancements in advanced sensing technology and digital signal processing, artificial intelligence, and computational modeling. These technologies are incorporated in the latest developments in structural health monitoring to offer sustainable, reliable, and cost-effective asset management for infrastructure operation and maintenance. This special issue aims to capture the latest research, developments, and practical applications in these fields.
This special issue will cover the latest research and development in all areas of advanced structural condition assessment. Potential topics include, but are not limited to:
·Advanced algorithms for structural identification
·Deep learning for structural damage detection
·Hybrid modeling
·Physics-informed neural networks for dynamic modeling
·Surrogate modeling for numerical simulations
·Advanced signal processing for structural damage detection
·Advanced sensor technology for structural health monitoring
·Internet of Things (IoT) for structural monitoring systems
The special issue will serve as a platform for academics, researchers, and industry professionals to discuss the latest advancements in structural damage detection and explore solutions for enhancing infrastructure safety, resilience, and sustainability.
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