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Infrastructures
Volume 10
Issue 12
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Infrastructures, Volume 10, Issue 12 (December 2025) – 37 articles

Cover Story (view full-size image): Infrastructures (ISSN 2412-3811) is an international scholarly journal covering all aspects of infrastructure engineering. The journal publishes regular research papers, critical reviews, and short communications. There is no restriction on the maximum length of the papers. We aim to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodological details must be provided for research articles.
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35 pages, 3452 KB  
Article
Analyzing Natural Disaster Risk Factors in Engineering Projects: A Social Networks Analysis Approach
by Qiuyan Gu and Jun Wang
Infrastructures 2025, 10(12), 352; https://doi.org/10.3390/infrastructures10120352 - 18 Dec 2025
Viewed by 404
Abstract
Natural disasters pose significant risks to engineering projects, necessitating a systematic analysis of their risk factors. This study focuses on identifying and mapping these factors using a mixed-methods approach that integrates a qualitative literature review with scientometric analysis via Social Network Analysis (SNA). [...] Read more.
Natural disasters pose significant risks to engineering projects, necessitating a systematic analysis of their risk factors. This study focuses on identifying and mapping these factors using a mixed-methods approach that integrates a qualitative literature review with scientometric analysis via Social Network Analysis (SNA). Through a meta-analysis of 81 peer-reviewed articles from Web of Science, Scopus, and ScienceDirect, the qualitative review establishes a comprehensive list and classification of 48 natural disaster risk factors, categorized into geological, climatic, hydrological, topographic, and biological groups, while providing a theoretical foundation. SNA complements this by quantifying co-occurrence frequencies, centrality metrics (degree, betweenness, and eigenvector), and network structures, revealing dynamic interactions, key influential factors, and research gaps—particularly in under-explored areas like hydrological hazards, extreme temperatures, lightning storms, and temperature variations—that qualitative methods alone might miss. This multi-perspective integration highlights discrepancies between theoretical discussions and practical applications, underscoring overlooked cascading effects. Findings emphasize the absence of an integrated model for all 48 factors, urging the development of a holistic predictive framework to bolster disaster resilience. Theoretically, the study offers a novel SNA-based quantification of factor importance and interrelations, addressing literature fragmentation. Practically, it guides project managers in prioritizing risks for optimized design, resource allocation, and prevention strategies. Future research should incorporate real-time data sources to refine this framework for enhanced risk management in engineering projects. Full article
(This article belongs to the Special Issue Earthquake and Multi-Hazard Resilience: Community-Level Insights and AI/ML Applications)
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19 pages, 7234 KB  
Article
Temperature and Speed Corrections for TSD-Measured Deflection Slopes Using 3D Finite Element Simulations
by Nariman Kazemi, Mofreh Saleh and Chin-Long Lee
Infrastructures 2025, 10(12), 351; https://doi.org/10.3390/infrastructures10120351 - 16 Dec 2025
Viewed by 203
Abstract
Traffic Speed Deflectometer (TSD) measures deflection velocities, normalised by travel speed to obtain deflection slopes. Pavement temperature and travel speed can significantly affect deflection slopes. Therefore, correcting deflection slopes for temperature and speed effects is essential. This study employs three-dimensional (3D) finite element [...] Read more.
Traffic Speed Deflectometer (TSD) measures deflection velocities, normalised by travel speed to obtain deflection slopes. Pavement temperature and travel speed can significantly affect deflection slopes. Therefore, correcting deflection slopes for temperature and speed effects is essential. This study employs three-dimensional (3D) finite element simulations of a three-layer flexible pavement system subjected to moving load at travel speeds from 40 km/h to 80 km/h, while varying the Asphalt Concrete (AC) layers’ thickness from 100 mm to 300 mm and the temperature from 5 °C to 45 °C. The results showed that deflection slopes at 100 mm offset distance could be corrected for the effects of temperature and speed using a correction factor comprising the sum of a parabolic function of temperature and a linear function of speed. At 600 mm and 1500 mm offset distances, simpler correction factors could be established using the sum of linear functions of temperature and speed. The Mean Absolute Percentage Error (MAPE) for all predictions was below 3%, indicating high accuracy. Accurate regression-based equations were also proposed to incorporate AC thickness in predicting the correction factors. The results highlight the potential to correct deflection slopes to a reference temperature and speed by evaluating a range of pavement systems. Full article
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23 pages, 2895 KB  
Article
Impact of Pavement Surface Roughness on TSD Backcalculation Outputs and Potential Mitigation Strategies
by Nariman Kazemi, Mofreh Saleh and Chin-Long Lee
Infrastructures 2025, 10(12), 350; https://doi.org/10.3390/infrastructures10120350 - 16 Dec 2025
Viewed by 310
Abstract
Deflection slopes measured by the traffic speed deflectometer (TSD) are being used to backcalculate the moduli of pavement layers. Pavement surface roughness causes variations in tyre load magnitude due to excitation, which affects TSD measurements. In this study, three rough pavement surface profiles [...] Read more.
Deflection slopes measured by the traffic speed deflectometer (TSD) are being used to backcalculate the moduli of pavement layers. Pavement surface roughness causes variations in tyre load magnitude due to excitation, which affects TSD measurements. In this study, three rough pavement surface profiles over 150 m longitudinal distances were extracted from the Long-Term Pavement Performance (LTPP) programme database. Utilising finite element method (FEM) simulation of the TSD pass at a travel speed of 80 km/h over a three-layer flexible pavement system containing the rough surface profiles and employing the Greenwood Engineering TSD backcalculation tool, it was found that tyre load excitation can lead to backcalculation errors of up to 48%. By obtaining deflection slopes at equal distance intervals along the 150 m pavement profiles, it was found that averaging the deflection slopes across 9 measurement points reduced backcalculation errors to 10%, while increasing the number of measurement points to 28 further lowered the backcalculation errors to 5%. These findings highlight the potential to mitigate the effects of tyre load excitation on TSD backcalculation outputs without relying on strain gauges, which are mounted on modern TSDs to measure instantaneous tyre load magnitudes but are sensitive to environmental conditions and require calibration. Full article
(This article belongs to the Special Issue Pavement Performance and Maintenance: Smart Technologies and Sustainable Practices)
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25 pages, 5082 KB  
Article
Performance Evaluation of Fixed-Point DFOS Cables for Structural Monitoring of Reinforced Concrete Elements
by Aigerim Buranbayeva, Assel Sarsembayeva, Bun Pin Tee, Iliyas Zhumadilov and Gulizat Orazbekova
Infrastructures 2025, 10(12), 349; https://doi.org/10.3390/infrastructures10120349 - 15 Dec 2025
Viewed by 249
Abstract
Distributed fiber-optic sensing (DFOS) with intentionally spaced mechanical fixity points was experimentally evaluated for the structural health monitoring (SHM) of reinforced concrete (RC) members. A full-scale four-point bending test was conducted on a 12 m RC beam (400 × 400 mm) instrumented with [...] Read more.
Distributed fiber-optic sensing (DFOS) with intentionally spaced mechanical fixity points was experimentally evaluated for the structural health monitoring (SHM) of reinforced concrete (RC) members. A full-scale four-point bending test was conducted on a 12 m RC beam (400 × 400 mm) instrumented with a single-mode DFOS cable incorporating internal anchors at 2 m intervals and bonded externally with structural epoxy. Brillouin time-domain analysis (BOTDA) provided distributed strain measurements at approximately 0.5 m spatial resolution, with all cables calibrated to ±15,000 µε. Under stepwise monotonic loading, the system captured smooth, repeatable strain baselines and clearly resolved localized tensile peaks associated with crack initiation and propagation. Long-gauge averages exhibited a near-linear load–strain response (R2 ≈ 0.99) consistent with discrete foil and vibrating-wire strain gauges. Even after cracking, the DFOS signal remained continuous, while some discrete sensors showed saturation or scatter. Temperature compensation via a parallel fiber ensured thermally stable interpretation during load holds. The fixed-point configuration mitigated local debonding effects and yielded unbiased long-gauge strain data suitable for assessing serviceability and differential settlement. Overall, the results confirm the suitability of fixed-point DFOS as a durable, SHM-ready sensing approach for RC foundation elements and as a dense data source for emerging digital-twin frameworks. Full article
(This article belongs to the Special Issue Advanced Sensing Technologies and Smart Construction Materials for Structural Health Monitoring)
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20 pages, 14411 KB  
Article
An Integrated Framework with SAM and OCR for Pavement Crack Quantification and Geospatial Mapping
by Nut Sovanneth, Asnake Adraro Angelo, Felix Obonguta and Kiyoyuki Kaito
Infrastructures 2025, 10(12), 348; https://doi.org/10.3390/infrastructures10120348 - 15 Dec 2025
Viewed by 379
Abstract
Pavement condition assessment using computer vision has emerged as an efficient alternative to traditional manual surveys, which are often labor-intensive and time-consuming. Leveraging deep learning, pavement distress such as cracks can be automatically detected, segmented, and quantified from high-resolution images captured by survey [...] Read more.
Pavement condition assessment using computer vision has emerged as an efficient alternative to traditional manual surveys, which are often labor-intensive and time-consuming. Leveraging deep learning, pavement distress such as cracks can be automatically detected, segmented, and quantified from high-resolution images captured by survey vehicles. Although numerous segmentation models have been proposed to generate crack masks, they typically require extensive pixel-level annotations, leading to high labeling costs. To overcome this limitation, this study integrates the Segmentation Anything Model (SAM), which produces accurate segmentation masks from simple bounding box prompts while leveraging its zero-shot capability to generalize to unseen images with minimal retraining. However, since SAM alone is not an end-to-end solution, we incorporate YOLOv8 for automated crack detection, eliminating the need for manual box annotation. Furthermore, the framework applies local refinement techniques to enhance mask precision and employs Optical Character Recognition (OCR) to automatically extract embedded GPS coordinates for geospatial mapping. The proposed framework is empirically validated using open-source pavement images from Yamanashi, demonstrating effective automated detection, classification, quantification, and geospatial mapping of pavement cracks. The results support automated pavement distress mapping onto real-world road networks, facilitating efficient maintenance planning for road agencies. Full article
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22 pages, 2039 KB  
Review
The Impact of Autonomous Vehicles on the Transportation Network with a Focus on the Physical Road Infrastructure
by Ana Čudina Ivančev, Tamara Džambas and Vesna Dragčević
Infrastructures 2025, 10(12), 347; https://doi.org/10.3390/infrastructures10120347 - 14 Dec 2025
Viewed by 554
Abstract
Significant progress in autonomous vehicle (AV) development has been made over the years through advancements in artificial intelligence, sensor technology, and data processing; however, many challenges remain, particularly regarding road safety and the complexity of adapting these vehicles to certain traffic situations. As [...] Read more.
Significant progress in autonomous vehicle (AV) development has been made over the years through advancements in artificial intelligence, sensor technology, and data processing; however, many challenges remain, particularly regarding road safety and the complexity of adapting these vehicles to certain traffic situations. As a result, many European countries are funding research projects and setting targets and strategic plans for autonomous mobility, while scientific research proposes establishing standards and design guidelines for adapting road infrastructure to new transportation trends. This review paper examines physical road infrastructure in the era of AVs and identifies potential modifications, considering the development of AVs during both the early and later stages of their introduction into mixed traffic flow. Accordingly, necessary road infrastructure adaptations and the main design parameters affecting road geometric design for AV operation are presented. The design parameters considered include stopping sight distance, vertical curve radii, straight sections, lanes, and others. Furthermore, potential changes in existing physical infrastructure are illustrated using the example of a deceleration lane. Whether it is new infrastructure or modifications to existing infrastructure, both are analyzed in terms of the proportion of AVs in the traffic flow. Full article
(This article belongs to the Special Issue Sustainable Road Design and Traffic Management)
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23 pages, 2331 KB  
Article
Life Cycle Impacts of Timber and Reinforced Concrete Floor Slabs: A Comparative Assessment
by Honghao Ren, Marita Wallhagen, Alireza Bahrami and Mathias Cehlin
Infrastructures 2025, 10(12), 346; https://doi.org/10.3390/infrastructures10120346 - 13 Dec 2025
Viewed by 246
Abstract
Due to their sustainability, lightweight qualities, and simplicity of installation, wood slab systems have gained increasing attention in the building industry. Cross-laminated timber (CLT), an engineered wood product (EWP), improves structural strength and stability, offering a good alternative to conventional reinforced concrete (RC) [...] Read more.
Due to their sustainability, lightweight qualities, and simplicity of installation, wood slab systems have gained increasing attention in the building industry. Cross-laminated timber (CLT), an engineered wood product (EWP), improves structural strength and stability, offering a good alternative to conventional reinforced concrete (RC) slab systems. Conventional CLT, however, contains adhesives that pose environmental and end-of-life (EOL) disposal challenges. Adhesive-free CLT (AFCLT) panels have recently been introduced as a sustainable option, but their environmental performance has not yet been thoroughly investigated. In this study, the environmental impacts of five slab systems are evaluated and compared using the life cycle assessment (LCA) methodology. The investigated slab systems include a standard CLT slab (SCLT), three different AFCLT slabs (AFCLT1, AFCLT2, and AFCLT3), and an RC slab. The assessment considered abiotic depletion potential (ADP), global warming potential (GWP), ozone layer depletion potential (ODP), human toxicity potential (HTP), freshwater aquatic ecotoxicity potential (FAETP), marine aquatic ecotoxicity potential (MAETP), terrestrial ecotoxicity potential (TETP), photochemical oxidation potential (POCP), acidification potential (AP), and eutrophication potential (EP), covering the entire life cycle from production to disposal, excluding part of the use stage (B2-B7). The results highlight the advantages and drawbacks of each slab system, providing insights into selecting sustainable slab solutions. AFCLT2 exhibited the lowest environmental impacts across the assessed categories. On the contrary, the RC slab showed the highest environmental impact among the studied products. For example, the RC slab had the highest GWP of 67.422 kg CO2 eq, which was 1784.3% higher than that of AFCLT2 (3.779 kg CO2 eq). Additionally, the simulation displayed that the analysis results vary depending on the electricity source, which is influenced by geographical location. Using the Norwegian electricity mix resulted in the most sustainable outcomes compared with Sweden, Finland, and Saudi Arabia. This study contributes to the advancement of low-carbon construction techniques and the development of building materials with reduced environmental impacts in the construction sector. Full article
(This article belongs to the Section Sustainable Infrastructures)
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38 pages, 967 KB  
Review
Environmentally Sustainable and Climate-Adapted Bitumen–Composite Materials for Road Construction in Central Asia
by Gulbarshin K. Shambilova, Rinat M. Iskakov, Nurgul K. Shazhdekeyeva, Bayan U. Kuanbayeva, Mikhail S. Kuzin, Ivan Yu. Skvortsov and Igor S. Makarov
Infrastructures 2025, 10(12), 345; https://doi.org/10.3390/infrastructures10120345 - 12 Dec 2025
Viewed by 547
Abstract
This review examines scientific and engineering strategies for adapting bituminous and asphalt concrete materials to the highly diverse climates of Central Asia. The region’s sharp gradients—from arid lowlands to cold mountainous zones—expose pavements to thermal fatigue, photo-oxidative aging, freeze–thaw cycles, and wind abrasion. [...] Read more.
This review examines scientific and engineering strategies for adapting bituminous and asphalt concrete materials to the highly diverse climates of Central Asia. The region’s sharp gradients—from arid lowlands to cold mountainous zones—expose pavements to thermal fatigue, photo-oxidative aging, freeze–thaw cycles, and wind abrasion. Existing climatic classifications and principles for designing thermally and radiatively resilient pavements are summarized. Special emphasis is placed on linking binder morphology, rheology, and climate-induced transformations in composite bituminous systems. Advanced characterization methods—including dynamic shear rheometry (DSR), multiple stress creep recovery (MSCR), bending beam rheometry (BBR), and linear amplitude sweep (LAS), supported by FTIR, SEM, and AFM—enable quantitative correlations between phase composition, oxidative chemistry, and mechanical performance. The influence of polymeric, nanostructured, and biopolymeric modifiers on stability and durability is critically assessed. The review promotes region-specific material design and the use of integrated accelerated aging protocols (RTFOT, PAV, UV, freeze–thaw) that replicate local climatic stresses. A climatic rheological profile is proposed as a unified framework combining climate mapping with microstructural and rheological data to guide the development of sustainable and durable pavements for Central Asia. Key rheological indicators—complex modulus (G*), non-recoverable creep compliance (Jnr), and the BBR m-value—are incorporated into this profile. Full article
(This article belongs to the Special Issue Safer Roads Ahead: Exploring the Latest Innovations and Advancements in Road Design and Safety Technology)
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18 pages, 6540 KB  
Review
Pavements and the Urban Heat Island Effect: A Network Analysis of Research Trends and Knowledge Structure
by Fouzieh Rouzmehr and Saman Jamshidi
Infrastructures 2025, 10(12), 344; https://doi.org/10.3390/infrastructures10120344 - 12 Dec 2025
Viewed by 396
Abstract
The urban heat island (UHI) effect is one of the most pressing challenges associated with rapid urbanization. It arises primarily from the replacement of natural vegetation with impervious surfaces, alterations in surface energy balance, and heat emissions from human activity. Mitigating these drivers [...] Read more.
The urban heat island (UHI) effect is one of the most pressing challenges associated with rapid urbanization. It arises primarily from the replacement of natural vegetation with impervious surfaces, alterations in surface energy balance, and heat emissions from human activity. Mitigating these drivers has become a global priority, particularly in fast-growing cities. Pavements play a central role in UHI intensification due to their large surface coverage, low albedo, and capacity to retain heat. This study adopts a bibliometric approach to systematically map the knowledge structure and research trends in pavement-related UHI studies. A dataset of 834 publications from Web of Science was analyzed using VOSviewer to identify leading countries and journals, central publications, the temporal evolution of research themes, and the thematic structure of the field. The analysis revealed three dominant themes: (1) pavement materials and their properties, (2) mitigation strategies that prevent UHI, and (3) cooling interventions to mitigate UHI. This study attempts to provide a comprehensive overview of the field and to clarify its interdisciplinary connections with climate adaptation and sustainability discourse. Full article
(This article belongs to the Special Issue Advances in Pavement Engineering: Materials, Performance, and Sustainability)
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23 pages, 1798 KB  
Article
Evaluation of Slate Waste as a Sustainable Material for Railway Sub-Ballast Layers: Analysis of Mechanical Behavior and Performance
by Raphael Lúcio Reis dos Santos, Conrado de Souza Rodrigues, Guilherme de Castro Leiva and Armando Belato Pereira
Infrastructures 2025, 10(12), 343; https://doi.org/10.3390/infrastructures10120343 - 11 Dec 2025
Viewed by 218
Abstract
The railway industry is increasingly pressured to adopt sustainable practices, seeking alternatives to virgin natural aggregates that reduce environmental impact and lifecycle costs. The extraction of slate for ornamental purposes generates significant waste, approximately 30% by mass, which is typically disposed of in [...] Read more.
The railway industry is increasingly pressured to adopt sustainable practices, seeking alternatives to virgin natural aggregates that reduce environmental impact and lifecycle costs. The extraction of slate for ornamental purposes generates significant waste, approximately 30% by mass, which is typically disposed of in landfills, causing environmental and economic concerns. This study comprehensively investigates the potential of slate waste as a primary component in sub-ballast layers for railways. Laboratory tests were conducted on mixtures of slate waste and a clayey soil, with granular contents ranging from 60% to 90%. The key geotechnical parameters evaluated included the California Bearing Ratio (CBR), Resilient Modulus (RM), compaction characteristics, granulometry and Atterberg limits. In addition, the DNIT ISF-212 standard was used to verify compliance with the Brazilian requirements for the use of materials in sub-ballast layers. The results indicate that mixtures with slate waste (SLT) exhibit performance comparable to conventional gneiss aggregate mixtures (REF); however, verification against the DNIT ISF-212 standard showed that only the SLT 80/20 and SLT 90/10 mixtures fully meet the requirements for use as railway sub-ballast. The RM and CBR values for the SLT mixtures increased by 48.5% and 38.4%, respectively, when the slate waste content was raised from 60% to 90%. A non-linear relationship was found between RM and CBR for both material types. Furthermore, the study integrates findings from related research on recycled ballast and tropical soils, highlighting the synergistic benefits of using industrial by-products. It concludes that slate waste presents a viable, high-performance, and sustainable solution for railway sub-ballast, contributing to circular economy principles in railway infrastructure. Full article
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25 pages, 1534 KB  
Article
Comparative Analysis of Stated Preference Data for Identifying Driving Behaviour Patterns of Last-Mile Delivery Professionals
by Dimosthenis Pavlou, Panagiotis Papantoniou, Vasiliki Amprasi, Chiara Gruden, Athanasios I. Koukounaris, Eva Michelaraki, Dimitrios Nikolaou and Konstantina Marousi
Infrastructures 2025, 10(12), 342; https://doi.org/10.3390/infrastructures10120342 - 10 Dec 2025
Viewed by 280
Abstract
The role of last-mile delivery professionals is becoming increasingly vital in modern urban logistics, driven by the rapid expansion of e-commerce and rising consumer expectations for fast and reliable services. This study aimed to analyse the decision-making patterns of last-mile delivery professionals through [...] Read more.
The role of last-mile delivery professionals is becoming increasingly vital in modern urban logistics, driven by the rapid expansion of e-commerce and rising consumer expectations for fast and reliable services. This study aimed to analyse the decision-making patterns of last-mile delivery professionals through stated preference data. To achieve this, a stated-preference questionnaire was conducted with 333 riders aged 18–65 from Croatia, Cyprus, Greece, Italy and Slovenia. A random parameter logit (RPL) model was applied to evaluate the influence of factors such as driving behaviour, delivery time and salary type on decision-making in hypothetical scenarios. Results showed that driving behaviour, trip duration and salary type significantly affected respondents’ preferences. Participants displayed a strong preference for flat salaries, indicating the importance of income stability over performance-based pay. Driving behaviour was also crucial, as respondents favoured legal and safe practices. Interestingly, while shorter delivery times were generally preferred, several scenarios revealed a tolerance for longer durations, possibly reflecting perceived benefits such as safer routes or reduced stress. Comparative analyses also revealed regional differences in vehicle use, work patterns and safety perceptions. The study highlights the need for tailored training programs on safety compliance, route optimization and time management, alongside hybrid salary structures balancing stability and productivity. Full article
(This article belongs to the Special Issue Safer Roads Ahead: Exploring the Latest Innovations and Advancements in Road Design and Safety Technology)
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28 pages, 8330 KB  
Article
Effects of UAV-Based Image Collection Methodologies on the Quality of Reality Capture and Digital Twins of Bridges
by Rongxin Zhao, Huayong Wu, Feng Wang, Huaying Xu, Shuo Wang, Yuxuan Li, Tianyi Xu, Mingyu Shi and Yasutaka Narazaki
Infrastructures 2025, 10(12), 341; https://doi.org/10.3390/infrastructures10120341 - 10 Dec 2025
Viewed by 246
Abstract
Unmanned Aerial Vehicle (UAV)-based photogrammetric reconstruction is a key step in geometric digital twinning of bridges, but ensuring the quality of the reconstruction data through the planning of measurement configurations is not straightforward. This research investigates an approach for quantitatively evaluating the impact [...] Read more.
Unmanned Aerial Vehicle (UAV)-based photogrammetric reconstruction is a key step in geometric digital twinning of bridges, but ensuring the quality of the reconstruction data through the planning of measurement configurations is not straightforward. This research investigates an approach for quantitatively evaluating the impact of different methodologies and configurations of UAV-based image collection on the quality of the collected images and 3D reconstruction data in the bridge inspection context. For an industry-grade UAV and a consumer-grade UAV, paths for image collection from different Ground Sampling Distance (GSD) and image overlap ratios are considered, followed by the 3D reconstruction with different algorithm configurations. Then, an approach for evaluating these data collection methodologies and configurations is discussed, focusing on trajectory accuracy, point-cloud reconstruction quality, and accuracy of geometric measurements relevant to inspection tasks. Through a case study on short-span road bridges, errors in different steps of the photogrammetric 3D reconstruction workflow are characterized. The results indicate that, for the global dimensional measurements, the consumer-grade UAV works comparably to the industry-grade UAV with different GSDs. In contrast, the local measurement accuracy changes significantly depending on the selected hardware and path-planning parameters. This research provides practical insights into controlling 3D reconstruction data quality in the context of bridge inspection and geometric digital twinning. Full article
(This article belongs to the Section Infrastructures Inspection and Maintenance)
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32 pages, 9737 KB  
Article
Experimental Study on Marly Clay Stabilization Under Short-Term Conditions Using Volcanic Ash and Reactivity-Controlled Lime as Activator
by Roberto Ponce, Svetlana Melentijević, Natalia Montero and Sol López-Andrés
Infrastructures 2025, 10(12), 340; https://doi.org/10.3390/infrastructures10120340 - 10 Dec 2025
Viewed by 280
Abstract
Expansive soils undergo significant volume changes with moisture fluctuations, posing persistent challenges for infrastructure due to heave, settlement, and loss of bearing capacity. Stabilization is a common mitigation strategy, though traditional binders, such as cement and lime, are associated with high energy consumption [...] Read more.
Expansive soils undergo significant volume changes with moisture fluctuations, posing persistent challenges for infrastructure due to heave, settlement, and loss of bearing capacity. Stabilization is a common mitigation strategy, though traditional binders, such as cement and lime, are associated with high energy consumption and considerable CO2 emissions. In this context, identifying low-carbon alternatives is essential. This study evaluates the short-term behavior of expansive marly clays from southern Spain stabilized with volcanic ash generated during the 2021 Tajogaite eruption (La Palma, Canary Islands, Spain). Volcanic ash was incorporated in different proportions to assess its performance as a natural pozzolan, while natural hydrated lime was used both as a direct stabilizer and as an activator to enhance ash reactivity. A key methodological contribution of this research is the monitoring of lime reactivity throughout storage, using XRD and TGA to quantify portlandite loss and partial carbonation before mixing—an aspect seldom addressed in stabilization studies. The experimental program included chemical and mineralogical characterization, compaction, Atterberg limits, free swelling, unconfined compressive strength, and direct shear tests on natural and stabilized mixtures. The results show that volcanic ash, particularly when lime-activated, substantially improves volumetric stability. Free swelling decreased from 11.9% in the natural soil to values as low as 1.7%, while dry density increased and plasticity decreased. Strength gains were modest under short-term conditions, consistent with the limited time for pozzolanic reactions to develop. The combined use of volcanic ash and lime reduced the lime demand required to achieve equivalent volumetric control, offering an eco-efficient and technically viable alternative for stabilizing expansive marly clays. Full article
(This article belongs to the Special Issue Civil, Mechanical and Environmental Engineering—Sustainable Development Goals for the 21st Century)
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17 pages, 3088 KB  
Article
Critical Stress Conditions for Foam Glass Aggregate Insulation in a Flexible Pavement Layered System
by Jean Pascal Bilodeau, Erdrick Pérez-González, Di Wang and Pauline Segui
Infrastructures 2025, 10(12), 339; https://doi.org/10.3390/infrastructures10120339 - 9 Dec 2025
Viewed by 324
Abstract
In cold regions, flexible pavements are vulnerable to frost-induced damage, necessitating effective insulation strategies. Foam glass aggregate (FGA) insulation layers, made from recycled glass, offer promising thermal insulation properties but are mechanically fragile and susceptible to permanent deformation under repeated loading. Manufacturers provide [...] Read more.
In cold regions, flexible pavements are vulnerable to frost-induced damage, necessitating effective insulation strategies. Foam glass aggregate (FGA) insulation layers, made from recycled glass, offer promising thermal insulation properties but are mechanically fragile and susceptible to permanent deformation under repeated loading. Manufacturers provide technical recommendations, particularly regarding load limits for installation and the dimensions of the thermal protection layer. These are considered insufficient to assist pavement designers in their work. The definition of critical criteria for permissible loads was deemed necessary to design mechanically durable structures using this alternative technology. This study investigates the critical stress conditions that FGA layers can tolerate within flexible pavement systems to ensure long-term structural integrity. Laboratory cyclic triaxial tests and full-scale accelerated pavement testing using a heavy vehicle simulator were conducted to evaluate the resilient modulus and permanent deformation behavior of FGA. The results show that FGA exhibits stress-dependent elastoplastic behavior, with resilient modulus values ranging from 70 to 200 MPa. Most samples exhibited plastic creep or incremental collapse behavior, underscoring the importance of careful stress management. A strain-hardening model was calibrated using both laboratory and full-scale data, incorporating a reliability level of 95%. This study identifies critical deviatoric stress thresholds (15–25 kPa) to maintain stable deformation behavior (Range A) under realistic confining pressures. FGA performs well as a lightweight, insulating, and draining layer, but design criteria remain to be defined for the design of multi-layer road structures adapted to local materials and traffic conditions. Establishing allowable critical stress levels would help designers mechanically validate the geometry, particularly the adequacy of the overlying layers. These findings support the development of mechanistic design criteria for FGA insulation layers, ensuring their durability and optimal performance in cold climate pavements. Full article
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48 pages, 4690 KB  
Review
Smart Surveillance of Structural Health: A Systematic Review of Deep Learning-Based Visual Inspection of Concrete Bridges Using 2D Images
by Nasrin Lotfi Karkan, Eghbal Shakeri, Naimeh Sadeghi and Saeed Banihashemi
Infrastructures 2025, 10(12), 338; https://doi.org/10.3390/infrastructures10120338 - 8 Dec 2025
Viewed by 573
Abstract
Timely and accurate inspection of concrete bridges is critical to ensuring structural integrity and public safety. Traditional visual inspections conducted by human inspectors are labour-intensive, inconsistent, and often limited in their ability to access all structural components, particularly in hazardous or inaccessible areas. [...] Read more.
Timely and accurate inspection of concrete bridges is critical to ensuring structural integrity and public safety. Traditional visual inspections conducted by human inspectors are labour-intensive, inconsistent, and often limited in their ability to access all structural components, particularly in hazardous or inaccessible areas. Image-based inspection techniques have emerged as a safer and more efficient alternative, and recent advancements in deep learning have significantly enhanced their diagnostic capabilities. This systematic review critically evaluates 77 studies that applied deep learning approaches to the detection and classification of surface defects in concrete bridges using 2D images. Relevant publications were retrieved from major scientific databases, screened for eligibility, and analyzed in terms of model type, training strategies, and evaluation metrics. The reviewed works encompass a wide spectrum of algorithms—spanning classification, object detection, and image segmentation models—highlighting their architectural features, strengths, and trade-offs in terms of accuracy, computational complexity, and real-time applicability. Key findings reveal that transfer learning, data augmentation, and careful dataset composition are pivotal in improving model performance. Moreover, the review identifies emerging research trajectories, such as integrating deep learning with Building Information Modeling (BIM), leveraging edge computing for real-time monitoring, and developing rich annotated datasets to enhance model generalizability. By mapping the current state of knowledge and outlining future research directions, this study provides a foundational reference for researchers and practitioners aiming to deploy deep learning technologies in bridge inspection and infrastructure monitoring. Full article
(This article belongs to the Special Issue Modern Digital Technologies for the Built Environment of the Future)
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14 pages, 1783 KB  
Article
Embankment Fires on Railways—Where and How to Mitigate?
by Lars Symmank, Shahriar Mohammadzadeh and Sonja Szymczak
Infrastructures 2025, 10(12), 337; https://doi.org/10.3390/infrastructures10120337 - 8 Dec 2025
Viewed by 259
Abstract
As climate change increases the frequency and unpredictability of natural hazards, adapting critical infrastructure is crucial for long-term resilience. Among these hazards, embankment fires pose a growing threat to railway systems, particularly under rising temperatures and prolonged drought conditions. As part of the [...] Read more.
As climate change increases the frequency and unpredictability of natural hazards, adapting critical infrastructure is crucial for long-term resilience. Among these hazards, embankment fires pose a growing threat to railway systems, particularly under rising temperatures and prolonged drought conditions. As part of the Horizon Europe project NATURE-DEMO, this study helps identify fire-prone rail segments and explore nature-based solutions, such as vegetation barriers, that can reduce ignition risk and enhance infrastructure resilience. In a case study, we analysed the risk of embankment fires for a section of the German railway network in detail. Based on an embankment-fire hazard indication map available for the entire German railway network, five hotspots within the study area were identified. Embankments with high fire susceptibility occur in both rural and urban areas, covering 1.1% of the study area. On the basis of published research on technical and nature-based solutions for reducing embankment fire susceptibility, we derived site-specific recommendations for the appropriate implementation of mitigation measures. Full article
(This article belongs to the Special Issue Nature-Based Solutions and Resilience of Infrastructure Systems)
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18 pages, 3855 KB  
Article
Effect of Bonding Characteristics on Rutting Resistance and Moisture Susceptibility of Rubberized Reclaimed Asphalt Pavement
by Ling Xu, Zifeng Zhao, Yuanwen Lai, Yan Yuan, Shuyi Wang, Junjie Lin, Laura Moretti and Giuseppe Loprencipe
Infrastructures 2025, 10(12), 336; https://doi.org/10.3390/infrastructures10120336 - 7 Dec 2025
Viewed by 276
Abstract
Asphalt pavements incorporating recycled and sustainable materials have become a widely adopted strategy in road construction, particularly with the use of reclaimed asphalt pavement (RAP) and crumb rubber (CR) derived from waste tires. However, the adhesion and cohesion characteristics of rubberized RAP mixtures [...] Read more.
Asphalt pavements incorporating recycled and sustainable materials have become a widely adopted strategy in road construction, particularly with the use of reclaimed asphalt pavement (RAP) and crumb rubber (CR) derived from waste tires. However, the adhesion and cohesion characteristics of rubberized RAP mixtures remain insufficiently understood. This study investigates how interfacial bonding affects the rutting resistance and moisture susceptibility of rubberized RAP asphalt mixtures. Two RAP sources with different aging levels and two CR particle sizes (250 μm and 380 μm) were evaluated. Binder bond strength (BBS) tests showed that pull-off strength increased with the use of smaller CR particles and more highly aged RAP, while rotational viscosity and penetration tests confirmed the corresponding increase in binder stiffness. Hamburg wheel track (HWT) tests with high-temperature viscoplastic deformation analysis demonstrated improved rutting resistance in the tested mixtures. Furthermore, boiling tests supported by image analysis revealed reductions in stripping ratios, indicating enhanced moisture resistance. ANOVA results (p < 0.05) confirmed that CR content had a significant effect on bonding characteristics, whereas RAP aging and CR particle size jointly influenced rutting performance. Overall, mixtures incorporating 10% CR and 25% RAP achieved the best balance between adhesion, cohesion, and durability. These findings provide a quantitative understanding of how interfacial bonding governs the mechanical performance and moisture resistance of rubberized RAP mixtures. Full article
(This article belongs to the Special Issue Pavement Performance and Maintenance: Smart Technologies and Sustainable Practices)
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19 pages, 4731 KB  
Article
In Situ Estimation of Breach Outflow Hydrographs from Fluvial Dike Failures: A Methodology Integrating Real-Time Monitoring and Physical Modelling
by Ricardo Jónatas, Sílvia Amaral, Rui Aleixo, João Bilé Serra and Rui M. L. Ferreira
Infrastructures 2025, 10(12), 335; https://doi.org/10.3390/infrastructures10120335 - 5 Dec 2025
Viewed by 233
Abstract
Embankment structures in civil engineering, such as earth dams and fluvial dikes, have a crucial role in society. These structures, often used for water storage and mining tailing containment, are cost-effective due to their reliance on locally sourced materials. While the failure of [...] Read more.
Embankment structures in civil engineering, such as earth dams and fluvial dikes, have a crucial role in society. These structures, often used for water storage and mining tailing containment, are cost-effective due to their reliance on locally sourced materials. While the failure of concrete structures is not so frequent but often lead to severe consequences, embankment structures, particularly fluvial dikes, are more prone to breach and the consequences vary from mild to catastrophic, depending on the proximity to human populations. Worldwide, some fluvial dike failures have resulted in catastrophic outcomes for human lives, the local economy and the environment. This paper aims to develop a methodology to calculate in situ breach outflow hydrographs, resorting to real-time, non-intrusive and friendly access technology. The goal is to provide a practical platform for developing and testing integrated systems applicable to prototype failure cases. An accurate, real-time hydrograph estimation capacity improves risk assessment. The proposed methodology deploys, in a medium-scale experimental facility, common technology and data processing techniques to characterize the evolution of a fluvial dike failure. The morphodynamic and hydrodynamic components influencing the in situ breach outflow hydrograph are assessed by characterizing, in real-time, the breach morphology at the surface and underwater, the surface velocity maps and the corresponding cartesian coordinates. Full article
(This article belongs to the Special Issue Preserving Life Through Dams)
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24 pages, 6581 KB  
Article
Preliminary Mechanistic Optimization of Two-Mat Reinforcement Design in Continuously Reinforced Concrete Pavement
by Samuel Alalade, Rajesh Chakraborty, Sang-Wook Bae, Jung Heum Yeon and Moon Won
Infrastructures 2025, 10(12), 334; https://doi.org/10.3390/infrastructures10120334 - 5 Dec 2025
Viewed by 195
Abstract
In thick continuously reinforced concrete pavement (CRCP), thicknesses greater than 356 mm, the Texas Department of Transportation (TxDOT) places longitudinal steel in two mats, with equal amount of steel in both top and bottom mats. These longitudinal steel layouts may not be optimal [...] Read more.
In thick continuously reinforced concrete pavement (CRCP), thicknesses greater than 356 mm, the Texas Department of Transportation (TxDOT) places longitudinal steel in two mats, with equal amount of steel in both top and bottom mats. These longitudinal steel layouts may not be optimal for restraining concrete volume changes from temperature and moisture variations (environmental loading), which are most severe near the surface. This study mechanistically evaluated and optimized two-mat reinforcement layouts by placing more steel in the top layer while reducing the amount in the bottom layer. A total of 2160 three-dimensional finite-element models were developed in ANSYS to examine how variations in steel depth and spacing influence steel stress, concrete stress, and crack width under different environmental loading conditions. The results indicated that top-focused configurations with reduced bottom reinforcement satisfied all performance thresholds for steel and concrete stresses as well as crack width, reducing concrete stress by about 4% and 11% for 356 mm slabs and about 13% for 381 mm slabs, and reducing crack width by about 2% for 356 mm slabs and about 5% for 381 mm slabs. These optimized designs achieved performance better than the existing TxDOT two-mat design standards while requiring less steel amount. The findings in this study will be validated in the field experiment in the second phase of the study. Full article
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22 pages, 6433 KB  
Article
Numerical Investigation of Local Scour Around Bridge Pile-Group Foundations Under Steady Flows
by Wentao Li, Xiangdong Wang, Zhixun Wang, Qianmi Yu, Peng Huang, Yilin Yang and Jinzhao Li
Infrastructures 2025, 10(12), 333; https://doi.org/10.3390/infrastructures10120333 - 5 Dec 2025
Viewed by 277
Abstract
Local scour around pile-group foundations is a predominant cause of hydraulic instability in bridge engineering. This study employs a fully coupled three-dimensional computational fluid dynamics model to investigate local scour around a 2 × 2 inline pile group under steady flows. The model [...] Read more.
Local scour around pile-group foundations is a predominant cause of hydraulic instability in bridge engineering. This study employs a fully coupled three-dimensional computational fluid dynamics model to investigate local scour around a 2 × 2 inline pile group under steady flows. The model is validated against detailed laboratory measurements of flow and scour, demonstrating good agreement in both hydrodynamic and scour results, with scour depth simulations deviating by less than 15% from experimental data. Analysis of the flow fields reveal that scour evolution is accompanied by the descent of the horseshoe vortex, intensification of gap-flow, and acceleration around the side piles, while migration of bed shear stress from the pile flanks to the upstream slope dictates the equilibrium scour morphology. A systematic parametric study was conducted to evaluate the influence of the Froude number (Fr) and pile spacing (G/D) on scour depth. The results indicate that scour depth increases rapidly with Fr up to approximate 0.35, beyond which it plateaus as form-induced drag dissipates the incoming flow energy. Increasing G/D from 1 to 1.5 reduces the scour depth by about 12%, with smaller further reduction beyond G/D = 1.5, suggesting that this spacing offers a pragmatic compromise between structural footprint and scour resistance. Full article
(This article belongs to the Section Infrastructures and Structural Engineering)
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16 pages, 2265 KB  
Article
Research on the Flexural Capacity of Pre-Tensioned Prestressed Hollow Concrete-Filled Steel Tubular Piles with Consideration of Pile–Soil Interaction
by Lin Huang, Jun Gao and Haodong Li
Infrastructures 2025, 10(12), 332; https://doi.org/10.3390/infrastructures10120332 - 3 Dec 2025
Viewed by 211
Abstract
Compared to traditional single/double-row concrete cast-in-place piles or concrete walls commonly used in foundation pit engineering, pre-tensioned prestressed hollow concrete-filled steel tube piles (referred to as prestressed Steel Cylinder Piles, or prestressed SC piles) demonstrate superior advantages including high bearing capacity, light weight, [...] Read more.
Compared to traditional single/double-row concrete cast-in-place piles or concrete walls commonly used in foundation pit engineering, pre-tensioned prestressed hollow concrete-filled steel tube piles (referred to as prestressed Steel Cylinder Piles, or prestressed SC piles) demonstrate superior advantages including high bearing capacity, light weight, enhanced stiffness, excellent crack resistance, and cost-effectiveness, indicating a promising future in foundation pit engineering. However, current research has paid limited attention to such piles. Only a few experimental studies have focused on their flexural performance. No studies have presented bearing behavior investigations considering soil–pile interactions and the differences between these kinds of piles and traditional piles. To address this gap, this paper conducts a systematic investigation into the bearing performance of prestressed SC piles. A refined finite element analysis model capable of accurately characterizing pile–soil interactions is developed to analyze the mechanical behavior. Subsequently, the elastic foundation beam method recommended by design codes is employed to analyze the internal forces and displacement variations of these piles during excavation. Finally, the predictions by the design code are compared against those from the refined model. Results shows that the established finite element model presents reasonable predictions on monitoring data and experimental results, with deviations in bending moments and deformations within the range of 10–15%; a comparative analysis of different pile types reveals that prestressed SC piles exhibit smaller horizontal displacements and higher bearing capacities; the bending moments and deformations predicted by design methods (elastic foundation beam method) are conservative, with the predicted values significantly higher than those predicted by the refined model. Full article
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10 pages, 192 KB  
Editorial
Advances in Dam Engineering of the 21st Century
by Jerzy W. Salamon and M. Amin Hariri-Ardebili
Infrastructures 2025, 10(12), 331; https://doi.org/10.3390/infrastructures10120331 - 3 Dec 2025
Viewed by 512
Abstract
The 21st century has emerged as a transformative era for dam engineering, shaped by rapid technological innovation, heightened environmental awareness, the progressive aging of existing infrastructure, and an urgent global call for climate resilience [...] Full article
(This article belongs to the Special Issue Advances in Dam Engineering of the 21st Century)
30 pages, 3685 KB  
Article
Conflict Risk Assessment Between Pedestrians and Right-Turn Vehicles: A Trajectory-Based Analysis of Front and Rear Wheel Dynamics
by Rui Li, Guohua Liang, Chenzhu Wang, Said M. Easa, Yajuan Deng, Baojie Wang and Yi Mao
Infrastructures 2025, 10(12), 330; https://doi.org/10.3390/infrastructures10120330 - 2 Dec 2025
Viewed by 391
Abstract
Right-turning vehicles at intersections permitting right turn on red (RTOR) frequently conflict with pedestrians, posing significant safety risks. Existing studies often simplify vehicle trajectories by treating vehicles as centroid points, ignoring the spatial disparities between pedestrians and vehicles. To address this gap, we [...] Read more.
Right-turning vehicles at intersections permitting right turn on red (RTOR) frequently conflict with pedestrians, posing significant safety risks. Existing studies often simplify vehicle trajectories by treating vehicles as centroid points, ignoring the spatial disparities between pedestrians and vehicles. To address this gap, we propose a conflict risk assessment framework based on front and rear wheel trajectories (FRWTs), which accounts for the dynamic differences in vehicle segments during turns. First, we partition vehicles into four segments (inner/outer and front/rear wheels) and develop a trajectory prediction model to quantify risk variations across these segments. Our analysis reveals that the inner front wheel poses the highest collision risk due to its speed, trajectory curvature, and pedestrian proximity. Next, we introduce three conflict interaction modes—hard interaction, no interaction, and soft interaction—and evaluate the applicability of conflict indicators (e.g., Time to Collision (TTC) and Post-Encroachment Time (PET)) under each mode. Using a Support Vector Machine (SVM) classification algorithm, we classify risk severity with high accuracy: 96% for hard interaction, 96% for no interaction, and 97% for soft interaction modes when TTC-PET dual indicators are employed. Our findings demonstrate that FRWT-based modeling significantly improves conflict risk assessment accuracy compared to centroid-point approaches. This work provides actionable insights for proactive traffic safety management and supports the development of targeted conflict mitigation strategies at RTOR intersections. Full article
(This article belongs to the Special Issue Data-Driven Innovations in Smart and Safe Transportation Infrastructure)
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38 pages, 883 KB  
Article
Barriers and Enablers in Implementing the Vision Zero Approach to Road Safety: A Case Study of Haryana, India, with Lessons from Sweden
by Mahfooz Ulhaq Bajwa, Wafaa Saleh and Grigorios Fountas
Infrastructures 2025, 10(12), 329; https://doi.org/10.3390/infrastructures10120329 - 1 Dec 2025
Viewed by 768
Abstract
Empirical studies on barriers and enablers to implementing Vision Zero remain limited, especially in low- and middle-income countries (LMICs), limiting broader adoption. India exemplifies this gap: while some cities and states have adopted Vision Zero, national uptake has been slow. The purpose of [...] Read more.
Empirical studies on barriers and enablers to implementing Vision Zero remain limited, especially in low- and middle-income countries (LMICs), limiting broader adoption. India exemplifies this gap: while some cities and states have adopted Vision Zero, national uptake has been slow. The purpose of this study is to investigate barriers and enablers in the Indian state of Haryana. Using a qualitative approach, we conducted semi-structured interviews with 16 Vision Zero experts selected through purposive and snowball sampling. Data was analyzed using inductive content analysis following Graneheim and Lundman’s approach. The findings revealed five categories and 21 sub-categories of barriers and four categories with 13 sub-categories of enablers. Cultural and institutional barriers were most prominent, including poor road safety culture, staff shortages, limited technical expertise and weak research capacity. Operational, financial and political barriers were less frequently discussed but included complex management processes, delayed funding and lack of political will in certain states. Key enablers included strong political support, long-term vision, ambitious road safety targets, and continuous monitoring and evaluation. Identifying these factors can strengthen the implementation capacity in LMICs and guide policymakers in overcoming challenges and leveraging enablers to advance Vision Zero. Full article
(This article belongs to the Special Issue Sustainable Road Design and Traffic Management)
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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 290
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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25 pages, 2975 KB  
Article
Laboratory Study on the Effect of Kraft Lignin and Sasobit on Construction Temperatures, Compactability and Physical Properties of Hot and Warm Mix Asphalt
by Ali Rezazad Gohari, Sébastien Lamothe, Jean-Pascal Bilodeau, Ahmad Mansourian and Alan Carter
Infrastructures 2025, 10(12), 327; https://doi.org/10.3390/infrastructures10120327 - 1 Dec 2025
Viewed by 382
Abstract
This study investigates the feasibility of using Kraft lignin in Hot and Warm Mix Asphalt (HMA and WMA), with a particular focus on its integration alongside Sasobit®. The research aims to evaluate the impact of Kraft lignin and Sasobit, individually and [...] Read more.
This study investigates the feasibility of using Kraft lignin in Hot and Warm Mix Asphalt (HMA and WMA), with a particular focus on its integration alongside Sasobit®. The research aims to evaluate the impact of Kraft lignin and Sasobit, individually and in combination, on the construction temperatures, compactability, and physical properties of asphalt mixtures. The experimental program included a reference HMA and modified mixes with 20% Kraft lignin, 3% Sasobit, and their combinations. These mixes were designed and subjected to tests to assess their volumetric and mass properties and to determine the construction temperatures using the Superpave Gyratory Compactor (SGC). The results demonstrated that adding Kraft lignin increased construction temperatures, while Sasobit effectively reduced these temperatures by lowering binder viscosity. When used together, Sasobit offset the increase in construction temperatures caused by Kraft lignin, resulting in compaction temperatures similar to the reference HMA mix. Additionally, Kraft lignin increased air voids, leading to reduced compactability at higher gyration levels. It also exhibited indications of a dual role, functioning as both a binder replacement and a filler. In conclusion, the combination of 20% Kraft lignin with 3% Sasobit offers a promising solution for enhancing the sustainability of asphalt mixtures. Full article
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24 pages, 3275 KB  
Article
Multiple Regression and Neural Network-Based Models for the Prediction of the Ultimate Strength of CFRP-Confined Columns
by Baylasan Mohamad, Muna Hamadeh, Firas Al Mahmoud and George Wardeh
Infrastructures 2025, 10(12), 326; https://doi.org/10.3390/infrastructures10120326 - 1 Dec 2025
Viewed by 303
Abstract
Carbon Fiber-Reinforced Polymers (CFRPs) are gaining popularity as a reliable strengthening technique for reinforced concrete (RC) columns. Several efficient models were developed to predict the stress–strain (σ-ε) curve of CFRP-confined concrete based on experiment findings. The ultimate strength is a crucial parameter for [...] Read more.
Carbon Fiber-Reinforced Polymers (CFRPs) are gaining popularity as a reliable strengthening technique for reinforced concrete (RC) columns. Several efficient models were developed to predict the stress–strain (σ-ε) curve of CFRP-confined concrete based on experiment findings. The ultimate strength is a crucial parameter for accurate (σ-ε) behavior prediction, since it constitutes an initial step in estimating the corresponding axial strain, as it provides a direct indication of the desired increase in strength. Literature analytical models often produce inconsistent results due to errors in estimating the confinement pressure or effectively confined area or the lack of a strong and stable correlation between ultimate strength and confinement parameters. This study looked at a large collection of experimental results from existing research. It used a statistical method (Pearson’s coefficient) to see how well ultimate strength correlated with various confinement factors. For normal-strength concrete columns with circular sections, there was a strong linear correlation between ultimate strength and the thickness of the CFRP jacket. This correlation weakened for high-strength concrete (HSC) and for rectangular columns. A sensitivity analysis was performed to identify the most influential confinement parameters, showing that the number of CFRP layers (n × t) is the most dominant factor, particularly with normal-strength concrete (NSC) in circular columns, accounting for the vast majority of the variance in ultimate strength. Using multiple linear regression equations to predict ultimate strength was also explored; this method demonstrated the best performance with HSC in circular sections, but the results were less promising with NSC. Artificial Neural Networks (ANNs) were developed and trained on the built database, and four statistical metrics were computed for evaluation (R2, RMSE, MAE, MRAE), proving highly accurate and superior to linear regression equations, with mean relative absolute errors MRAEs between 2.4–7.2% for ultimate strength prediction, opening new avenues for optimizing CFRP-strengthened element designs. Full article
(This article belongs to the Topic Rehabilitation and Strengthening Techniques for Reinforced Concrete)
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26 pages, 5454 KB  
Article
The Importance of Structural Configuration in the Seismic Performance and Reliability of Buildings
by Rodolfo J. Tirado-Gutiérrez, Ramón González-Drigo and Yeudy F. Vargas-Alzate
Infrastructures 2025, 10(12), 325; https://doi.org/10.3390/infrastructures10120325 - 26 Nov 2025
Viewed by 353
Abstract
The optimal performance of buildings strongly depends on their structural configuration, as it influences the structural response to expected loads during life service. For instance, structural arrangements oriented to reduce torsional effects increase performance and, in turn, mitigate vulnerability to seismic events. However, [...] Read more.
The optimal performance of buildings strongly depends on their structural configuration, as it influences the structural response to expected loads during life service. For instance, structural arrangements oriented to reduce torsional effects increase performance and, in turn, mitigate vulnerability to seismic events. However, several structural analyses should be performed to ensure that these structural arrangements are robust This can be computationally expensive depending on the type of analysis. The objective of this research is twofold. The first objective is to compare the dynamic response of two reinforced concrete buildings that are almost identical in height and floor area but whose structural elements are placed differently. The dynamic response of both structures was calculated via nonlinear dynamic analysis (NLDA) by considering a large set of ground motion records. Second, NLDA results were compared with those stemming from a spectral-based methodology. The comparison is made on the basis of the fragility and damage functions given different return periods. The results show that an adequate spatial distribution of structural elements reduces materials and increases safety and stability, since the expected damage is lower. Likewise, it is observed that the results based on reduced-order procedures accurately represent those obtained from NLDA while entailing a significantly lower computational cost. Full article
(This article belongs to the Topic Resilient Civil Infrastructure, 2nd Edition)
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24 pages, 4839 KB  
Article
An Aerial-Ground Collaborative Framework for Asphalt Pavement Quality Inspection
by Peng Li, Sijin Wei, Tao Lei, Lei Niu, Wenyang Han, Chunhua Su, Guangyong Wang, Kai Chen, Ting Cui, Zhang Ding and Zhi Fu
Infrastructures 2025, 10(12), 324; https://doi.org/10.3390/infrastructures10120324 - 26 Nov 2025
Viewed by 371
Abstract
To overcome the limitations of conventional methods, this study developed a novel aerial-ground collaborative framework for multi-dimensional quality assessment of asphalt pavement. The quality inspection of asphalt pavement in the whole construction process is realized. Multiple non-destructive testing (NDT) techniques were integrated, including [...] Read more.
To overcome the limitations of conventional methods, this study developed a novel aerial-ground collaborative framework for multi-dimensional quality assessment of asphalt pavement. The quality inspection of asphalt pavement in the whole construction process is realized. Multiple non-destructive testing (NDT) techniques were integrated, including drone-based infrared thermography, ground-penetrating radar (GPR), and a nuclear-free density gauge. Results showed a strong correlation (R2 > 0.95) between the radar-derived dielectric constant and core samples, enabling rapid, full-coverage characterization. The density gauge achieved less than 3% error. Furthermore, a compactness prediction model based on the dielectric constant and an air void content evaluation model based on temperature parameters are further constructed. This system enables aerial screening, point verification, and ground diagnosis, significantly enhancing inspection efficiency and comprehensiveness. Full article
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26 pages, 4516 KB  
Article
Hybrid AI–FEA Framework for Seismic Assessment of Confined Masonry Walls Using Crack Image-Based Material Property Inference
by Piero R. Yupanqui, Jeferson L. Orihuela and Rick M. Delgadillo
Infrastructures 2025, 10(12), 323; https://doi.org/10.3390/infrastructures10120323 - 25 Nov 2025
Viewed by 441
Abstract
Recent advances in computer vision and artificial intelligence have enabled new approaches for non-destructive post-earthquake assessment of masonry structures. This study proposes a hybrid AI–FEA framework that integrates a MobileNetV2 convolutional neural network for crack-image-based material property inference with nonlinear finite element analysis [...] Read more.
Recent advances in computer vision and artificial intelligence have enabled new approaches for non-destructive post-earthquake assessment of masonry structures. This study proposes a hybrid AI–FEA framework that integrates a MobileNetV2 convolutional neural network for crack-image-based material property inference with nonlinear finite element analysis (FEA) of confined masonry walls. The model predicts key mechanical parameters, including elastic modulus, compressive and tensile strengths, and fracture energies, directly from crack morphology, and these parameters are subsequently used as input for DIANA FEA to simulate the wall’s seismic response. The framework is validated against reference experimental data, achieving a strong parametric correlation (R2 = 0.91) and accurately reproducing characteristic nonlinear behavior such as stiffness degradation, diagonal cracking, and post-peak softening in pushover analysis. Photographs from the Limatambo urban area in Lima, Peru, are included to illustrate typical damage patterns in a high-seismic-risk context, although the numerical model represents a standardized confined masonry wall typology rather than site-specific buildings. The proposed methodology offers a consistent, non-destructive, and efficient tool for seismic performance evaluation and supports the digital modernization of structural diagnostics in earthquake-prone regions. Full article
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