Guest Editors
Prof. Yuan Ren
Email: magren@126.com
Affiliation: School of Transportation, Southeast University, Nanjing, 210096, China
Homepage:
Research Interests: large span bridge inspection and monitoring, evaluation and operation and maintenance decision analysis, structural analysis of large-span bridges
Dr. Ziyuan Fan
Email: fanzy1216@163.com
Affiliation: School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou 310018, China
Homepage:
Research Interests: bridge maintenance management, structural service performance analysis, bridge inspection and evaluation, construction monitoring
Prof. Xiaoling Liu
Email: liuxiaoling@nbu.edu.cn
Affiliation: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, PR China
Homepage:
Research Interests: bridge maintenance and evaluation, combined bridge fatigue performance study
Assoc. Prof. Xiang Xu
Email: xxuseu@126.com
Affiliation: School of Transportation, Southeast University, Nanjing 211189, China
Homepage:
Research Interests: condition assessment of large-span cable-loaded bridges, identification of bridge anomalies based on health monitoring data, and decision-making methods for bridge maintenance
Summary
The global bridge infrastructure is facing unprecedented challenges due to aging materials, increasing traffic loads, climate change impacts, and the pressing need for sustainable asset management. The degenerating infrastructure necessitates innovative approaches to ensure the safety, durability, and performance of bridge structures. Recently, intelligent technology, such as AI-driven damage detection, IoT-based structural health monitoring, digital twin, and robotic inspection systems, have been used to promote operation and maintenance for bridge structures. Contributions may cover theoretical developments, computational models, sensor technologies, and case studies demonstrating the integration of smart maintenance strategies. By conducting high-quality research, the resilience and sustainability of bridge structures will be enhanced and lifecycle costs will also be reduced. Researchers are invited to submit work that addresses challenges and opportunities in this rapidly evolving field.
The interested themes include but not limited to:
-Big data analytics for long term monitoring data.
-AI and machine learning for bridge condition assessment.
-Advanced automated inspection techniques.
-Theoretical developments of predictive maintenance.
-Resilience-based maintenance optimization.
-Resilience quantification under extreme events.
-Lifecycle benefit optimization through smart maintenance.
-Field applications of intelligent operation and maintenance.
Keywords
intelligent technique; operation and maintenance; data driven; damage detection; structural health monitoring, digital twin; automated inspection; resilience optimization.
Published Papers
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