Lifecycle Management of Civil and Structural Engineering: Deterioration Modeling, Climate-Resilient Maintenance and Structural Health Monitoring

Dear Colleagues,

Civil and structural infrastructure systems constitute the backbone of modern society, yet face accelerating deterioration driven by aging, corrosion, and climate-induced environmental stressors. Ensuring their long-term functionality and safety requires integrated approaches that combine deterioration modeling, predictive maintenance strategies, and advanced structural health monitoring.

This Special Issue aims to gather state-of-the-art research addressing the lifecycle management of civil and structural engineering systems, with a particular focus on climate-resilient interventions, probabilistic deterioration assessment, and data-driven inspection frameworks. Contributions are encouraged from both theoretical and applied perspectives, incorporating computational modeling, field monitoring, and decision-oriented engineering strategies.

Research areas may include, but are not limited to, the following topics:

• Lifecycle management of civil and structural systems
• Deterioration and service-life modeling under multi-hazard conditions
• Climate-resilient maintenance and adaptation planning
• Structural reliability analysis and fragility assessment
• AI-empowered structural health monitoring and inspection
• Predictive maintenance supported by Bayesian inference and digital twins
• Sensor technologies and advanced monitoring approaches
• Lifecycle assessment considering uncertainty and climate trajectories
• Sustainability and carbon footprint evaluation in structural rehabilitation

We welcome contributions from multidisciplinary perspectives, including structural engineering, infrastructure resilience, materials science, machine learning, and decision analytics, toward advancing durable, adaptive, and low-risk civil infrastructure systems.

We look forward to receiving your contributions.

Dr. Siyi Jia
Dr. Minghui Liu
Dr. Yurong Zhang
Guest Editors

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