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

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 458

Special Issue Editors

Dr. Siyi Jia

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Waseda University, Tokyo 169-8050, Japan
Interests: Bayesian inference; structural health monitoring; life cycle assessment; few-shot learning; seismic resilience
Dr. Minghui Liu

E-Mail Website
Guest Editor
School of Civil and Engineering, Beijing Jiaotong University, Beijing 100044, China
Interests: sustainable transport infrastructure; carbon footprint; life cycle assessment; underground structures; concrete structures
Special Issues, Collections and Topics in MDPI journals
Dr. Yurong Zhang

E-Mail Website
Guest Editor
College of Civil Engineering, Zhejiang University of Technology, Hangzhou 310014, China
Interests: concrete structure; life cycle assessment; chloride transport; repair and rehabilitation; long-term reliability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

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

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. Buildings is an international peer-reviewed open access semimonthly 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 2600 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

  • structural health monitoring
  • structural deterioration modeling
  • Bayesian inference
  • digital twins
  • climate change
  • multi-hazards

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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Research

29 pages, 13121 KB  
Article
Interpretable Optimization Design of Polygonal Pretensioned Concrete Bulb-T Girders Considering Tendon Section Coordination and Performance Cost Efficiency
by Hongzhi Xu, Qingfei Gao, Bowen Ruan, Shuo Zhang, Yao Song and Yan Song
Buildings 2026, 16(11), 2121; https://doi.org/10.3390/buildings16112121 - 26 May 2026
Viewed by 186
Abstract
The design of polygonal pretensioned concrete girders involves a practical conflict among load-carrying capacity, stiffness, ductility, damage control, and material cost. In conventional design, these characteristics are strongly coupled: increasing web thickness may improve stiffness but reduce ductility, while modifying tendon inclination or [...] Read more.
The design of polygonal pretensioned concrete girders involves a practical conflict among load-carrying capacity, stiffness, ductility, damage control, and material cost. In conventional design, these characteristics are strongly coupled: increasing web thickness may improve stiffness but reduce ductility, while modifying tendon inclination or inflection-point position may improve prestress efficiency but may also induce local stress concentration near tendon-deviation regions. This coupling makes it difficult to identify rational design solutions through trial-and-error procedures alone. To address this problem, this study proposes a mechanism-informed and interpretable design framework for 30 m polygonal pretensioned concrete Bulb-T girders by integrating nonlinear finite-element analysis, surrogate-assisted modeling, multi-objective trade-off evaluation, and SHAP-based feature-attribution analysis. The scientific problem addressed in this study is the insufficient understanding of how tendon geometry and sectional parameters interact to govern structural response, while the applied problem is the lack of transparent design guidance for balancing performance and cost in polygonal pretensioned girders. The results show that girder behavior is controlled by coordinated parameter interactions rather than isolated parameter changes. Tendon inclination, inflection-point location, and web thickness are identified as the dominant variables affecting load-carrying capacity, damage evolution, stiffness–ductility balance, and cost-effectiveness. Compared with the conventional design, the representative optimized design increased the ultimate load-carrying capacity by approximately 26%, reduced the peak concrete damage index by approximately 24%, and increased the structural performance index by approximately 8.5%, lowered the normalized material–cost indicator by approximately 5%, and improved the performance–cost index by approximately 14–15%. These findings indicate that the proposed framework is not a fundamentally new girder form, but an improved interpretable design methodology that converts numerical optimization results into transferable engineering design principles for polygonal pretensioned concrete girders. Full article
(This article belongs to the Special Issue Lifecycle Management of Civil and Structural Engineering: Deterioration Modeling, Climate-Resilient Maintenance and Structural Health Monitoring)
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