Advanced Technologies for Climate Resilient Infrastructures

A special issue of Infrastructures (ISSN 2412-3811).

Deadline for manuscript submissions: 10 March 2026 | Viewed by 436

Special Issue Editors


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Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
Interests: urban resilience; disaster management; transportation sysytem

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Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
Interests: urban planning; sustainable development; energy consumption; artificial intelligence

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Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
Interests: pubic private partnership; construction project management; international project management; climate change and sustainability
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Special Issue Information

Dear Colleagues,

In recent years, the growing frequency and intensity of climate-related hazards—such as floods, heatwaves, storms, and sea-level rise—have posed increasing challenges to the safety, durability, and functionality of urban infrastructure systems. As these climate risks intensify, it will become more urgent to develop and deploy advanced technologies that enhance the climate resilience of our infrastructure networks.

This Special Issue aims to bring together the latest research and practical developments related to the use of advanced technologies in designing, monitoring, and managing climate-resilient infrastructures. We welcome contributions that explore innovative methods and tools that help infrastructure systems withstand, adapt to, and recover from extreme weather events and long-term climate stressors.

Potential topics include, but are not limited to, the following:

  • Intelligent sensing and monitoring: Internet of Things (IoT), wireless sensor networks, and real-time data systems for infrastructure risk detection and early warning.
  • Digital technologies for resilience: Applications of digital twins, building information modeling (BIM), and geographic information systems (GIS) in climate adaptation planning and asset management.
  • AI techniques for resilience: Machine learning, computer vision, and large language models for failure detection, climate risk assessment, and decision support.
  • Optimization for resilience management: Operations research and optimization techniques for planning, resource deployment, and recovery strategies in climate-resilient infrastructure systems.
  • Smart materials and adaptive structures: The use of responsive or sustainable materials and adaptive structures that improve durability, thermal performance, or flood resistance.
  • Infrastructure system modeling and assessment: Modeling and evaluation of climate risks affecting individual or interdependent infrastructure systems (e.g., transport, water, energy), under single- or multiple-hazard scenarios.
  • Urban sustainability and climate-resilient planning: Integrating climate adaptation strategies into urban planning and design (e.g., buildings, transportation, and land use) to support long-term sustainability goals and enhance city-scale resilience.
  • Case studies and real-world applications: Demonstrations of the successful implementation of technologies in infrastructure resilience projects.

We invite original research papers, review articles, and technical notes that showcase emerging ideas, robust methods, and practical insights. Contributions from interdisciplinary teams combining engineering, data science, urban planning, and environmental studies are especially encouraged. All submissions will undergo thorough peer review to ensure high scientific and practical relevance. We hope that this Special Issue will serve as a platform for researchers and practitioners to share solutions that will help make infrastructure systems smarter, stronger, and more adaptable in the face of climate change.

Dr. Renfei He
Dr. Yan Zhang
Dr. Robert Lee Kong Tiong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Infrastructures is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent sensing and monitoring
  • digital technologies for resilience
  • AI techniques for resilience
  • optimization for resilience management
  • smart materials and adaptive structures
  • infrastructure system modeling and assessment
  • urban sustainability and climate-resilient planning
  • case studies and real-world applications

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Published Papers (1 paper)

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Research

18 pages, 4358 KB  
Article
Investigation on Bearing Characteristics for Critical Fittings of Transmission Lines Undergoing Coupled Ice–Wind Loads
by Zhiguo Li, Guoliang Ye, Dongjia Liu, Zhiyi Liu, Xiaohui Zhang and Guizao Huang
Infrastructures 2025, 10(12), 328; https://doi.org/10.3390/infrastructures10120328 - 1 Dec 2025
Viewed by 198
Abstract
The safe and stable operation of ultra-high-voltage (UHV) transmission lines is fundamental to ensuring efficient and large-capacity power delivery. Critical fittings, as essential load-bearing components connecting towers, conductors, and insulator strings, are highly susceptible to damage under complex ice–wind conditions, thereby posing significant [...] Read more.
The safe and stable operation of ultra-high-voltage (UHV) transmission lines is fundamental to ensuring efficient and large-capacity power delivery. Critical fittings, as essential load-bearing components connecting towers, conductors, and insulator strings, are highly susceptible to damage under complex ice–wind conditions, thereby posing significant threats to grid security. To address the prevalent issues of jumper spacer breakage and conductor abrasion observed in field maintenance, a systematic finite element analysis model incorporating bundled conductors, jumper structures, and associated fittings was established. This model enabled comprehensive investigation of the effects of non-uniform ice accretion, wind loading, and ice-shedding impacts on the bearing characteristics of critical fittings. Through high-throughput computational simulations, a large-scale dataset capturing the bearing characteristics of jumper spacers was constructed. Based on this dataset, a damage risk assessment model under complex ice–wind conditions was developed using a multi-layer feedforward deep neural network (MLF-DNN). The results indicated that wind loading had a relatively minor influence on jumper spacers, whereas ice accretion and ice-shedding impacts were the dominant factors leading to damage. In particular, non-uniform ice-shedding readily induced unbalanced forces among sub-conductors, significantly increasing stress levels in jumper spacers and resulting in substantial risk. The proposed risk assessment model demonstrated high predictive accuracy and strong generalization capability, providing effective support for rapid evaluation and early warning of damage to fittings in UHV transmission lines under complex ice–wind environments. Full article
(This article belongs to the Special Issue Advanced Technologies for Climate Resilient Infrastructures)
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