Special Issues
Table of Content

Resilient and Sustainable Infrastructure: Monitoring, Safety, and Durability

Submission Deadline: 30 June 2026 View: 302 Submit to Special Issue

Guest Editors

Prof. Dr. Xiaoming Lei

Email: xiaoming.lei@polyu.edu.hk

Affiliation: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong

Homepage:

Research Interests: structural health monitoring, practical machine learning, bridge engineering, intelligent infrastructure management, system resilience

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Prof. Dr. Shi-Zhi Chen

Email: szchen@chd.edu.cn

Affiliation: School of Highway, Chang'an University, Xi'an 710054, China

Homepage:

Research Interests: structural health monitoring, AI-enhanced infrastructure assessment, optimization of strategies for bridge maintenance

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Prof. Dr. Yaohan Li

Email: yahli@hkmu.edu.hk

Affiliation: Department of Construction and Quality Management, Hong Kong Metropolitan University, Kowloon 999077, Hong Kong

Homepage:

Research Interests: climate resilience, life-cycle management, hazard mitigation

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Dr. Xudong Jian

Email: xudong.jian@sec.ethz.ch

Affiliation: Singapore-ETH Centre, Future Resilient Systems Programme, Singapore 138602, Singapore

Homepage:

Research Interests: structural health monitoring, applied artificial intelligence, infrastructure resilience

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Dr. Chuanjie Cui

Email: chuanjie.cui@eng.ox.ac.uk

Affiliation: Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK

Homepage:

Research Interests: structural integrity, materials degradation, life-cycle assessment, physics-informed deep learning

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Summary

Modern infrastructure faces growing challenges from aging systems, extreme weather, and increasing operational demands. Ensuring long-term resilience, safety, and sustainability requires advanced monitoring techniques, robust risk assessment, and innovative durability solutions. This Special Issue focuses on cutting-edge research in structural health monitoring (SHM), risk and resilience assessment, and safety enhancement for civil infrastructures, including bridges, buildings, and transportation networks.


We invite contributions on novel sensor technologies, data-driven condition assessment, predictive maintenance strategies, and damage detection methods. Topics of interest include but are not limited to:
· Smart monitoring systems for real-time infrastructure performance evaluation
· Resilience-based design and life-cycle assessment of structures
· Durability enhancement through advanced materials and repair techniques
· Risk modeling for natural and man-made hazards
· Case studies on sustainable infrastructure rehabilitation and retrofitting


This Special Issue aims to bridge the gap between theoretical advancements and practical applications, fostering innovations that enhance infrastructure longevity and sustainability. Researchers and practitioners are encouraged to submit original research, reviews, and case studies that contribute to safer, more resilient, and sustainable built environments.


Keywords

structural health monitoring, artificial intelligence, infrastructure resilience, risk assessment, condition assessment, life-cycle analysis

Published Papers


  • Open Access

    ARTICLE

    STPEIC: A Swin Transformer-Based Framework for Interpretable Post-Earthquake Structural Classification

    Xinrui Ma, Shizhi Chen
    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1745-1767, 2025, DOI:10.32604/sdhm.2025.071148
    (This article belongs to the Special Issue: Resilient and Sustainable Infrastructure: Monitoring, Safety, and Durability)
    Abstract The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intensive, and prone to human error. To address these challenges, this study proposes STPEIC (Swin Transformer-based Framework for Interpretable Post-Earthquake Structural Classification), an automated deep learning framework designed for analyzing post-earthquake images. STPEIC performs two key tasks: structural components classification and damage level classification. By leveraging the hierarchical attention mechanisms of the Swin Transformer (Shifted Window Transformer), the model achieves 85.4% accuracy in structural component classification and 85.1% More >

  • Open Access

    REVIEW

    Benefits of Artificial Intelligence for Achieving Durable and Sustainable Building Design

    Abdullah Alariyan, Rawand A. Mohammed Amin, Ameen Mokhles Youns, Mahmoud Alhashash, Favzi Ghreivati, Ahed Habib, Maan Habib
    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1387-1410, 2025, DOI:10.32604/sdhm.2025.069821
    (This article belongs to the Special Issue: Resilient and Sustainable Infrastructure: Monitoring, Safety, and Durability)
    Abstract Artificial intelligence (AI) is transforming the building and construction sector, enabling enhanced design strategies for achieving durable and sustainable structures. Traditional methods of design and construction often struggle to adequately predict building longevity, optimize material use, and maintain sustainability throughout a building’s lifecycle. AI technologies, including machine learning, deep learning, and digital twins, present advanced capabilities to overcome these limitations by providing precise predictive analytics, real-time monitoring, and proactive maintenance solutions. This study explores the benefits of integrating AI into building design and construction processes, highlighting key advantages such as improved durability, optimized resource efficiency,… More >

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