Infrastructures

22 pages, 6875 KiB

Open AccessArticle

Evaluation of Flange Grease on Revenue Service Tracks Using Laser-Based Systems and Machine Learning

by Aditya Rahalkar, S. Morteza Mirzaei, Yang Chen, Carvel Holton and Mehdi Ahmadian

Infrastructures 2025, 10(4), 80; https://doi.org/10.3390/infrastructures10040080 - 31 Mar 2025

This study presents a machine learning approach for estimating the presence and extent of flange-face lubrication on a rail. It offers an alternative to the current empirical and subjective methods for lubrication assessment, in which track engineers’ periodic visual inspections are used to [...] Read more.

This study presents a machine learning approach for estimating the presence and extent of flange-face lubrication on a rail. It offers an alternative to the current empirical and subjective methods for lubrication assessment, in which track engineers’ periodic visual inspections are used to evaluate the condition of the rail. This alternative approach uses a laser-based optical sensing system developed by the Railway Technologies Laboratory (RTL) located at Virginia Tech in Blacksburg, VA, combined with a machine learning calibration model. The optical sensing system can capture the fluorescence emitted by the grease to identify its presence, while the machine learning model classifies the extent of grease present into four thickness indices (TIs), from 0 to 3, representing heavy (3), medium (2), light (1) and low/no (0) lubrication. Both laboratory and field tests are conducted, with the results demonstrating the ability of the system to differentiate lubrication levels and measure the presence or absence of grease and TI with an accuracy of 90%. Full article

(This article belongs to the Special Issue Remote Sensing for Infrastructure Health Monitoring: Advancements in Sensors and Analysis)

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22 pages, 2758 KiB

Open AccessArticle

Pedestrian Perceptions of Sidewalk Paving Attributes: Insights from a Pilot Study in Braga

by Fernando Fonseca, Alexandra Rodrigues and Hugo Silva

Infrastructures 2025, 10(4), 79; https://doi.org/10.3390/infrastructures10040079 - 30 Mar 2025

Abstract

The influence of sidewalk paving materials on pedestrian safety and comfort remains an underexplored topic within the walkability literature. This pilot study aims to address this gap by evaluating the role of five surface-related attributes—roughness, friction, texture, heat retention, and maintenance—through a qualitative [...] Read more.

The influence of sidewalk paving materials on pedestrian safety and comfort remains an underexplored topic within the walkability literature. This pilot study aims to address this gap by evaluating the role of five surface-related attributes—roughness, friction, texture, heat retention, and maintenance—through a qualitative approach complemented by a simplified quantitative evaluation. The study was conducted along a pedestrian route in Braga, Portugal, where pedestrian perceptions were collected via a questionnaire and compared with objective measurements obtained at seven testing points with different paving materials. The results indicate a strong preference for concrete and mortar pavements due to their slip-resistant surfaces, smoothness, and overall regularity. Quantitative tests confirmed that these materials exhibited the highest slip resistance and surface regularity, reinforcing the general alignment between pedestrian perceptions and measured performance. Participants rated paving attributes higher than others, such as sidewalk width or obstacle-free paths. Notable demographic differences also emerged: women rated sidewalk attributes more highly than men, seniors preferred traditional stone pavements more, and adults favored concrete. These findings highlight the importance of integrating surface-related sidewalk attributes into walkability assessments and urban design strategies to promote safer, more comfortable, and more inclusive pedestrian environments. Full article

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22 pages, 2572 KiB

Open AccessArticle

Rice Husk Ash and Waste Marble Powder as Alternative Materials for Cement

by Mezgebu Debas Yeshiwas, Mitiku Damtie Yehualaw, Betelhem Tilahun Habtegebreal, Wallelign Mulugeta Nebiyu and Woubishet Zewdu Taffese

Infrastructures 2025, 10(4), 78; https://doi.org/10.3390/infrastructures10040078 - 29 Mar 2025

Abstract

Concrete, a cornerstone of modern construction, owes its widespread adoption to global industrialization and urbanization, with mortar being an essential component. However, the cement production process is energy-intensive and generates significant CO₂ emissions. This study explores the use of agricultural (rice husk [...] Read more.

Concrete, a cornerstone of modern construction, owes its widespread adoption to global industrialization and urbanization, with mortar being an essential component. However, the cement production process is energy-intensive and generates significant CO₂ emissions. This study explores the use of agricultural (rice husk ash, RHA) and industrial (waste marble powder, WMP) waste materials as partial cement replacements in mortar. Despite extensive research on RHA and WMP individually, studies examining their combined effects remain scarce. This research assessed cement replacement levels from 0% to 30% in 5% increments, evaluating the fresh, mechanical, durability, and microstructural properties of the mortar. The findings showed that replacing 20% of cement with RHA and WMP increased compressive strength by 20.65% after 28 days, attributed to improved homogeneity and pozzolanic reactions that produced more calcium silicate hydrate. Water absorption decreased from 8.3% to 6.34%, indicating lower porosity and enhanced uniformity. Microstructural analyzes showed a denser mortar with 13% less mass loss at 20% replacement level. However, higher replacement levels reduced workability due to the increased surface area of RHA and WMP. Generally, using RHA and WMP as partial replacements of up to 20% significantly enhances mortar properties and supports sustainability. Full article

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23 pages, 1347 KiB

Open AccessArticle

Enhancing Walkability for Older Adults: The Role of Government Policies and Urban Design

by Akshatha Rao, Rama Devi Nandineni, Roshan S. Shetty, Kailas Mallaiah and Giridhar B. Kamath

Infrastructures 2025, 10(4), 77; https://doi.org/10.3390/infrastructures10040077 - 28 Mar 2025

Abstract

This research examines the impact of government policy initiatives, community engagement programs, and age-friendly urban design policies on the built environment, with a specific focus on the walkability of older adults. The walkability of older adults in the built environment is essential because [...] Read more.

This research examines the impact of government policy initiatives, community engagement programs, and age-friendly urban design policies on the built environment, with a specific focus on the walkability of older adults. The walkability of older adults in the built environment is essential because it promotes physical activity, social connectedness, and independence, thereby enhancing the overall quality of life and supporting healthy aging. This study employs a quantitative approach and cross-sectional design with convenience sampling in Udupi district, one of the urbanizing districts in India. The sample includes 333 older adults from diverse sociodemographic backgrounds who actively use the built environment. Structural equation modeling was used to test the hypotheses. The findings indicate that community engagement programs are the strongest enabler of safety and security perceptions related to walkability. Safety and security positively correlate with increased physical activity level, increased socialization level, and improved quality of life in older adults. Security also mediates the relationship between community engagement programs and all three outcomes associated with walkability. It highlights priority urban design features such as strategic lighting, sheltered walkways, traffic calming measures, barrier-free access, rest areas, and inclusive design elements as critical components of adaptive urban spaces that promote safety, accessibility, and social inclusion for older adults. Full article

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27 pages, 8596 KiB

Open AccessArticle

Eco-Friendly High-Strength Geopolymer Mortar from Construction and Demolition Wastes

by Osama Youssf, Donia Safaa Eldin and Ahmed M. Tahwia

Infrastructures 2025, 10(4), 76; https://doi.org/10.3390/infrastructures10040076 - 27 Mar 2025

Abstract

Geopolymer mortar is an eco-friendly type of mortar that is mainly made of fly ash, slag, and sand as common precursors. Recently, the availability of these materials has become limited due to the huge increase in geopolymer constructions. This is aligned with the [...] Read more.

Geopolymer mortar is an eco-friendly type of mortar that is mainly made of fly ash, slag, and sand as common precursors. Recently, the availability of these materials has become limited due to the huge increase in geopolymer constructions. This is aligned with the recent demand for recycling construction and demolition waste (CDW). In this study, brick waste (BW), ceramic tile waste (CTW), roof tile waste (RTW), and glass waste (GW) extracted from CDW were prepared in the following two sizes: one equivalent to the traditional geopolymer mortar binder (fly ash and slag) size and the other one equivalent to the sand size. The prepared CDW was used to partially replace the binder or sand to produce high-strength geopolymer mortar (HSGM). The replacements were carried out at rates of 25% and 50% by volume. The variety of mechanical and durability characteristics were measured, including workability, compressive strength, freezing/thawing resistance, sulfate attack, water sorptivity, and water absorption. Three curing conditions were applied for the proposed HSGM in this study, namely, water, heat followed by water, and heat followed by air. The results showed that the compressive strength of all HSGM mixes containing CDW ranged from 24 to 104 MPa. HSGM mixes cured in heat followed by water showed the highest 28-day compressive strengths of 104 MPa (when using 25% BW binder), 84.5 MPa (when using 25% BW fine aggregate), 91.3 MPa (when using 50% BW fine aggregate), 84 MPa (when using 25% CTW binder), and 94 MPa (when using 25% CTW fine aggregate). The findings demonstrated that using BW provided good resistance to freezing/thawing and sulfate attack. The water absorption of HSGM increased by 57.8% when using 50% CTW fine aggregate and decreased by 26.5% when using 50% GW fine aggregate. The highest water sorptivity of HSGM was recorded when 50% CTW fine aggregate was used. The use of CDW in HSGM helps reduce the depletion of natural resources and minimizes waste accumulation, enhancing environmental sustainability. These benefits make HSGM an eco-friendly alternative that promotes circular economy practices. Full article

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25 pages, 11379 KiB

Open AccessArticle

Dynamic Behaviour and Seismic Response of Scoured Bridge Piers

by Christos Antonopoulos, Enrico Tubaldi, Sandro Carbonari, Fabrizio Gara and Francesca Dezi

Infrastructures 2025, 10(4), 75; https://doi.org/10.3390/infrastructures10040075 - 25 Mar 2025

Abstract

This study explores the transverse response of bridge piers in riverbeds under a multi-hazard scenario, involving seismic actions and scoured foundations. The combined impact of scour on foundations’ stability and on the dynamic stiffness of soil–foundation systems makes bridges more susceptible to earthquake [...] Read more.

This study explores the transverse response of bridge piers in riverbeds under a multi-hazard scenario, involving seismic actions and scoured foundations. The combined impact of scour on foundations’ stability and on the dynamic stiffness of soil–foundation systems makes bridges more susceptible to earthquake damage. While previous research has extensively investigated this issue for bridges founded on piles, this work addresses the less explored but critical scenario of bridges on shallow foundations, typical of existing bridges. A comprehensive soil–foundation structure model is developed to be representative of the transverse response of multi-span and continuous girder bridges, and the effects of different scour scenarios and foundation embedment on the dynamic stiffness of the soil–foundation sub-systems are investigated through refined finite element models. Then, a parametric investigation is conducted to assess the effects of scour on the dynamic properties of the systems and, for some representative bridge prototypes, the seismic response at scoured and non-scoured conditions are compared considering real earthquakes. The research results demonstrate the significance of scour effects on the dynamic properties of the soil–foundation structure system and on the displacement demand of the bridge decks. Full article

(This article belongs to the Special Issue Bridge Modeling, Monitoring, Management and Beyond)

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20 pages, 10657 KiB

Open AccessArticle

The Integrity of Short-Span Bridges in the Case of Coastal Floods: Monitoring Strategies and an Example

by Mario Lucio Puppio, Alessandro Pucci and Mauro Sassu

Infrastructures 2025, 10(4), 74; https://doi.org/10.3390/infrastructures10040074 - 24 Mar 2025

Abstract

This paper examines short-span bridge (SSB) integrity against floods. They represent the majority of road infrastructures and are often affected by hydraulic erosion and overlap during rainfalls. A method to classify and identify a set of SSBs in an assigned territory is illustrated. [...] Read more.

This paper examines short-span bridge (SSB) integrity against floods. They represent the majority of road infrastructures and are often affected by hydraulic erosion and overlap during rainfalls. A method to classify and identify a set of SSBs in an assigned territory is illustrated. An analytical approach to evaluate the severity condition and priority of intervention is then presented, furnishing formulas for designing SSBs or evaluating the safety of existing ones. An emblematic case study, located on Sardinia Island (Italy), is described, applying the proposed approach in terms of hydraulic and structural loads to be considered. Finally, a discussion of the main obtained results is carried out, taking into account experiences due to recent floods and related collapses, with conclusions presented. Full article

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24 pages, 13834 KiB

Open AccessArticle

Development of a Stress Block Model to Predict the Ultimate Bending Capacity of Rectangular Concrete-Filled Steel Tube Beams Strengthened with U-Shaped CFRP Sheets

by Mohammad Ansari, Ahmed W. Al Zand, Emad Hosseinpour, Ali Joharchi and Masoud Abedini

Infrastructures 2025, 10(4), 73; https://doi.org/10.3390/infrastructures10040073 - 24 Mar 2025

Abstract

The prediction of the ultimate bending capacity of the rectangular concrete-filled steel tube (RCFST) beams strengthened with U-shaped carbon fiber reinforced polymer (CFRP) sheets is limited to using the existing empirical models. Thus, this study aims to develop a new theoretical model based [...] Read more.

The prediction of the ultimate bending capacity of the rectangular concrete-filled steel tube (RCFST) beams strengthened with U-shaped carbon fiber reinforced polymer (CFRP) sheets is limited to using the existing empirical models. Thus, this study aims to develop a new theoretical model based on a stress block model to predict the ultimate bending capacity (M_u) of the RCFST beams strengthened with a U-shaped CFRP-wrapping scheme. For this purpose, 28 finite element (FE) models of CFRP-strengthened RCFST beams had been analyzed for further investigation of the flexural behavior and longitudinal stresses distributed along with the beam’s components (steel tube, concrete core, and CFRP layers). The main parameters investigated are concrete compressive strength, steel yield strength, number of CFRP layers, and CFRP-wrapping-depth ratio. In addition, the M_u values obtained from the FE models of the current study and those from the existing experimental tests performed by others are used to verify the corresponding values that are theoretically predicted by the new model. The comparison showed that the proposed model is moderately conservative, as the predicted values of M_u are, on average, up to 10% lower than those obtained from experimental tests and FE analysis. Full article

(This article belongs to the Section Infrastructures and Structural Engineering)

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18 pages, 10302 KiB

Open AccessArticle

Research on Asphalt Pavement Surface Distress Detection Technology Coupling Deep Learning and Object Detection Algorithms

by Hong Zhang, Yuanshuai Dong, Yun Hou, Xiangjun Cheng, Peiwen Xie and Keming Di

Infrastructures 2025, 10(4), 72; https://doi.org/10.3390/infrastructures10040072 - 24 Mar 2025

Abstract

To address the challenges posed by the vast scale of highway maintenance in China and the high costs associated with traditional inspection vehicles. This study focuses on a routine maintenance project for national and provincial roads in Shanxi Province, with an emphasis on [...] Read more.

To address the challenges posed by the vast scale of highway maintenance in China and the high costs associated with traditional inspection vehicles. This study focuses on a routine maintenance project for national and provincial roads in Shanxi Province, with an emphasis on the selection and design of hardware for lightweight, portable pavement inspection devices. A monocular camera was used to capture pavement surface images, resulting in a dataset of 85,511 training samples. Additionally, the YOLOv5 object detection algorithm, combined with convolutional deep learning techniques, was employed to classify and identify pavement surface distresses in the collected images. Through multiple iterations of model tuning and validation, the proposed detection system achieved a false negative rate of 1.13%, a recall rate of 97.35%, and a precision rate of 98.30%. Its high accuracy provides a technical reference for the development and design of portable pavement distress detection devices. Full article

(This article belongs to the Special Issue Sustainable and Digital Transformation of Road Infrastructures)

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18 pages, 9282 KiB

Open AccessArticle

Parametric Analysis as a Tool for Hypothesis Generation: A Case Study of the Federal Archive Building in New York City

by Mike Christenson

Infrastructures 2025, 10(4), 71; https://doi.org/10.3390/infrastructures10040071 - 24 Mar 2025

Abstract

This study investigates the epistemological potentials of parametric analysis for digitally modeling ordinary, existing buildings, addressing a gap in architectural research. While traditional digital modeling prioritizes geometric accuracy, it often limits the ability to generate new architectural insights, treating models as static representations [...] Read more.

This study investigates the epistemological potentials of parametric analysis for digitally modeling ordinary, existing buildings, addressing a gap in architectural research. While traditional digital modeling prioritizes geometric accuracy, it often limits the ability to generate new architectural insights, treating models as static representations rather than as tools for knowledge production. This research challenges the assumption that geometric accuracy is necessary for epistemological validity, proposing parametric analysis as a hypothesis-generating tool capable of uncovering latent spatial and morphological properties that conventional methods overlook. Using Suárez’s inferential conception of scientific representation as a theoretical framework, this research employs a comparative case study methodology, contrasting direct and parametric digital models of the Federal Archive Building in New York City, analyzing their respective contributions to architectural knowledge. Existing documentation of the Federal Archive Building provides the primary data. The findings reveal that parametric modeling can enable the discovery of latent design properties by facilitating the systematic exploration of geometric variations while maintaining other logics, specifically by demonstrating how certain architectural features accommodate site irregularities while preserving visual coherence. This research advances theoretical discourse by repositioning parametric models from descriptive artifacts to instruments of architectural reasoning, challenging conventional associations between representational accuracy and epistemological validity. Practical applications are suggested in heritage documentation, comparative architectural analysis, and educational contexts where the interpretive exploration of buildings can generate new insights beyond what geometrically accurate models alone can provide. Full article

(This article belongs to the Special Issue Modern Digital Technologies for the Built Environment of the Future)

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17 pages, 6954 KiB

Open AccessArticle

Point Transformer Network-Based Surrogate Model for Spatial Prediction in Bridges

by Javier Grandío, Brais Barros, Manuel Cabaleiro and Belén Riveiro

Infrastructures 2025, 10(4), 70; https://doi.org/10.3390/infrastructures10040070 - 22 Mar 2025

Abstract

Bridges are essential assets of inland transportation infrastructure; however, they are among the most vulnerable elements of these networks due to deterioration caused by aging and the increasing loads to which they are subjected over time. Consequently, maintenance becomes critical to ensure acceptable [...] Read more.

Bridges are essential assets of inland transportation infrastructure; however, they are among the most vulnerable elements of these networks due to deterioration caused by aging and the increasing loads to which they are subjected over time. Consequently, maintenance becomes critical to ensure acceptable levels of safety and service. Finite element (FE) models are traditionally used to reliably assess structural health, but their computational expense often prevents their extensive use in routine bridge assessments. To overcome this computational limitation, this paper presents an innovative deep learning-based surrogate model for predicting local displacements in bridge structures. By utilizing point cloud data and transformer neural networks, the model provides fast and accurate predictions of displacements, addressing the limitations of traditional methods. A case study of a historical bridge demonstrates the model’s efficiency. The proposed approach integrates spatial data processing techniques, offering a computationally efficient alternative for bridge health monitoring. Our results show that the model achieves mean absolute errors below 0.0213 mm, drastically reducing the time required for structural analysis. Full article

(This article belongs to the Section Infrastructures and Structural Engineering)

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16 pages, 3637 KiB

Open AccessArticle

Development of a Large Database of Italian Bridge Bearings: Preliminary Analysis of Collected Data and Typical Defects

by Angelo Masi, Giuseppe Santarsiero, Marco Savoia, Enrico Cardillo, Beatrice Belletti, Ruggero Macaluso, Maurizio Orlando, Giovanni Menichini, Giacomo Morano, Giuseppe Carlo Marano, Fabrizio Palmisano, Anna Saetta, Luisa Berto, Maria Rosaria Pecce, Antonio Bilotta, Pier Paolo Rossi, Andrea Floridia, Mauro Sassu, Marco Zucca, Eugenio Chioccarelli, Alberto Meda, Daniele Losanno, Marco Di Prisco, Giorgio Serino, Paolo Riva, Nicola Nisticò, Sergio Lagomarsino, Stefania Degli Abbati, Giuseppe Maddaloni, Gennaro Magliulo, Mattia Calò, Fabio Biondini, Francesca da Porto, Daniele Zonta and Maria Pina Limongelli Show full author list Hide full author list

Infrastructures 2025, 10(3), 69; https://doi.org/10.3390/infrastructures10030069 - 20 Mar 2025

Abstract

This paper presents the development and analysis of a bridge bearing database consistent with the 2020 Italian Guidelines (LG2020), currently enforced by the Italian law for risk classification and management of existing bridges. The database was developed by putting together the contribution of [...] Read more.

This paper presents the development and analysis of a bridge bearing database consistent with the 2020 Italian Guidelines (LG2020), currently enforced by the Italian law for risk classification and management of existing bridges. The database was developed by putting together the contribution of 24 research teams from 18 Italian universities in the framework of a research project foreseen by the agreement between the High Council of Public Works (CSLP, part of the Italian Ministry of Transportation) and the research consortium ReLUIS (Network of Italian Earthquake and Structural Engineering University Laboratories). This research project aimed to apply LG2020 to a set of about 600 bridges distributed across the Italian country, in order to find possible issues and propose modifications and integrations. The database includes almost 12,000 bearing defect forms related to a portfolio of 255 existing bridges located across the entire country. This paper reports a preliminary analysis of the dataset to provide an overview of the bearings installed in a significant bridge portfolio, referring to major highways and state roads. After a brief state of the art about the main bearing types installed on the bridges, along with inspection procedures, the paper describes the database structure, showing preliminary analyses related to bearing types and defects. The results show the prevalence of elastomeric pads, representing more than 55% of the inspected bearings. The remaining bearings are pot, low-friction with steel–Teflon surfaces and older-type steel devices. Lastly, the study provides information about typical defects for each type of bearing, while also underscoring some issues related to the current version of the LG2020 bearing inspection form. Full article

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17 pages, 4387 KiB

Open AccessArticle

Failure Mode- and Time-Dependent Reliability Model of Tunnel Lining Structure Under Extremely High Ground Stress

by Tao Peng, Dongxing Ren, Fanmin He, Binjia Li, Fei Wu and Shijie Xu

Infrastructures 2025, 10(3), 68; https://doi.org/10.3390/infrastructures10030068 - 20 Mar 2025

Abstract

Damage to tunnel lining significantly influences the stability of tunnels during operation, particularly under conditions of extra-high ground stress. This article investigates the stability of tunnel linings subjected to extra-high ground stress, providing an in-depth analysis of crack damage modes. A time-varying reliability [...] Read more.

Damage to tunnel lining significantly influences the stability of tunnels during operation, particularly under conditions of extra-high ground stress. This article investigates the stability of tunnel linings subjected to extra-high ground stress, providing an in-depth analysis of crack damage modes. A time-varying reliability model based on the structural performance function is proposed, which incorporates the effects of the plastic zone and the identified crack damage modes. The plastic zone and the distribution of the surrounding rock stress field throughout the excavation process were simulated, elucidating the relationship between vault displacement and stress release rate. The time-varying reliability model is employed to assess lining behavior under extremely high ground stress and to establish the patterns governing its service life. The findings of this study offer a crucial reference for further investigations into the time-varying reliability of tunnel linings in the context of extreme ground stress. Full article

(This article belongs to the Topic Development of Underground Space for Engineering Application)

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26 pages, 3014 KiB

Open AccessReview

Shear Behavior of Ultra-High-Performance Concrete Deep Beams Reinforced with Fibers: A State-of-the-Art Review

by Hossein Mirzaaghabeik, Nuha S. Mashaan and Sanjay Kumar Shukla

Infrastructures 2025, 10(3), 67; https://doi.org/10.3390/infrastructures10030067 - 20 Mar 2025

Abstract

Ultra-high-performance concrete (UHPC) is considered a highly applicable composite material due to its exceptional mechanical properties, such as high compressive strength and ductility. UHPC deep beams are structural elements suitable for short spans, transfer girders, pile caps, offshore platforms, and bridge applications where [...] Read more.

Ultra-high-performance concrete (UHPC) is considered a highly applicable composite material due to its exceptional mechanical properties, such as high compressive strength and ductility. UHPC deep beams are structural elements suitable for short spans, transfer girders, pile caps, offshore platforms, and bridge applications where they are designed to carry heavy loads. Several key factors significantly influence the shear behavior of UHPC deep beams, including the compressive strength of UHPC, the vertical web reinforcement (ρ_sv), horizontal web reinforcement (ρ_sh), and longitudinal reinforcement (ρ_s), as well as the shear span-to-depth ratio (λ), fiber type, fiber content (FC), and geometrical dimensions. In this paper, a comprehensive literature review was conducted to evaluate factors influencing the shear behavior of UHPC deep beams, with the aim of identifying research gaps and enhancing understanding of these influences. The findings from the literature were systematically classified and analyzed to clarify the impact and trends associated with each factor. The analyzed data highlight the effect of each factor on the shear behavior of UHPC deep beams, along with the overall trends. The findings indicate that an increase in compressive strength, FC, ρ_sv, ρ_s, and ρ_sh can enhance the shear capacity of UHPC-DBs by up to 63.36%, 63.24%, 38.14%, 19.02%, and 38.14%, respectively. Additionally, a reduction of 61.29% in λ resulted in a maximum increase of 49.29% in the shear capacity of UHPC-DBs. Full article

(This article belongs to the Topic Advances on Structural Engineering, 3rd Edition)

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27 pages, 5217 KiB

Open AccessReview

The Use of Earth Observation Data for Railway Infrastructure Monitoring—A Review

by Milan Banic, Danijela Ristic-Durrant, Milos Madic, Alina Klapper, Milan Trifunovic, Milos Simonovic and Szabolcs Fischer

Infrastructures 2025, 10(3), 66; https://doi.org/10.3390/infrastructures10030066 - 19 Mar 2025

Abstract

Satellite data have the potential to significantly enhance railway operations and drive the digitization of the rail sector. In the context of railways, satellite data primarily refers to the use of Global Navigation Satellite System (GNSS) data for applications such as navigation, positioning, [...] Read more.

Satellite data have the potential to significantly enhance railway operations and drive the digitization of the rail sector. In the context of railways, satellite data primarily refers to the use of Global Navigation Satellite System (GNSS) data for applications such as navigation, positioning, and signalling. However, remote sensing data from Earth Observation (EO) satellites remain comparatively underutilized in railway applications. While the use of GNSS data in railways is well documented in the literature, research on EO-based remote sensing methods remains relatively limited. This paper aims to bridge this gap as it presents a comprehensive review of the use of satellite data in railway applications, with a particular focus on the underexplored potential of EO data. It provides the first in-depth analysis of EO techniques, primarily examining the use of synthetic aperture radar (SAR) and optical satellite data for key applications for infrastructure managers and railway operators, such as assessing track stability, detecting deformations, and monitoring surrounding environmental conditions. The goal of this review is to explore the diverse range of EO-based applications in railways and to identify emerging trends, including the integration of thermal EO data and the novel use of SAR for dynamic and predictive analyses. By synthesizing existing research and addressing knowledge gaps, the presented review underscores the potential of EO data to transform railway infrastructure management. Enhanced spatial resolution, frequent revisit cycles, and advanced AI-driven analytics are highlighted as key enablers for safer, more reliable, and cost-effective solutions. This review provides a framework for leveraging EO data to drive innovation and improve railway monitoring practices. Full article

(This article belongs to the Special Issue Emerging Technologies for Effective and Intelligent Transport Infrastructure Monitoring)

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16 pages, 1863 KiB

Open AccessArticle

Determining Passing Sight Distance on Upgraded Road Sections over Single and Platooned Heavy Military Vehicles

by Stergios Mavromatis, Vassilios Matragos, Antonis Kontizas and Kiriakos Amiridis

Infrastructures 2025, 10(3), 65; https://doi.org/10.3390/infrastructures10030065 - 19 Mar 2025

Abstract

Although truck platooning enhances transportation efficiency, reduces fuel consumption, and lowers freight transport costs, it can also create limited overtaking opportunities, potentially leading to risky overtaking maneuvers. The present study examines the impact of platooned heavy military vehicles on the quantification of Passing [...] Read more.

Although truck platooning enhances transportation efficiency, reduces fuel consumption, and lowers freight transport costs, it can also create limited overtaking opportunities, potentially leading to risky overtaking maneuvers. The present study examines the impact of platooned heavy military vehicles on the quantification of Passing Sight Distance (PSD). Two distinct cases are examined: single and platooned military vehicles passing, the latter formed by five trucks. The authors, by realistically modeling the passing task, examined the interaction between vehicle dynamic parameters and roadway grade utilizing an existing vehicle dynamics model. The analysis of various speed values revealed significant PSD variations depending on the examined impeding (overtaken) vehicle’s platooning configuration and utilized grade. The present assessment accurately quantifies the grade impact on the required PSDs for such special vehicle arrangements and can be applied to any vehicle platooning configuration. Moreover, a preliminary tool is introduced to assist road designers in accurately assessing the impact of roadway grade on the passing process. This tool, when combined with a more in-depth analysis of additional factors, can help justify the need for an extra lane in road sections where platooning regularly occurs. Full article

(This article belongs to the Special Issue Sustainable Road Design and Traffic Management)

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36 pages, 11633 KiB

Open AccessReview

Review and Insights Toward Cognitive Digital Twins in Pavement Assets for Construction 5.0

by Mohammad Oditallah, Morshed Alam, Palaneeswaran Ekambaram and Sagheer Ranjha

Infrastructures 2025, 10(3), 64; https://doi.org/10.3390/infrastructures10030064 - 15 Mar 2025

Abstract

With the movement of the construction industry towards Construction 5.0, Digital Twin (DT) has emerged in recent years as a pivotal and comprehensive management tool for predictive strategies for infrastructure assets. However, its effective adoption and conceptual implementation remain limited in this domain. [...] Read more.

With the movement of the construction industry towards Construction 5.0, Digital Twin (DT) has emerged in recent years as a pivotal and comprehensive management tool for predictive strategies for infrastructure assets. However, its effective adoption and conceptual implementation remain limited in this domain. Current review works focused on applications and potentials of DT in general infrastructures. This review focuses on interpreting DT’s conceptual foundation in the flexible pavement asset context, including core components, considerations, and methodologies. Existing pavement DT implementations are evaluated to uncover their strengths, limitations, and potential for improvement. Based on a systematic review, this study proposes a comprehensive cognitive DT framework for pavement management. It explores the extent of enhanced decision-making and a large-scale collaborative DT environment. This study also identifies current and emerging challenges and enablers, as well as highlights future research directions to advance DT implementation and support its alignment with the transformative goals of Construction 5.0. Full article

(This article belongs to the Special Issue Sustainable and Digital Transformation of Road Infrastructures)

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25 pages, 3743 KiB

Open AccessArticle

Cost Efficiency and Effectiveness of Drone Applications in Bridge Condition Monitoring

by Taraneh Askarzadeh and Raj Bridgelall

Infrastructures 2025, 10(3), 63; https://doi.org/10.3390/infrastructures10030063 - 13 Mar 2025

Abstract

Bridges are an integral and important part of road networks, but monitoring their condition using traditional methods is expensive, dangerous, and laborious. This study examines the rapidly emerging field of drone-based transportation asset monitoring, focusing on analyzing the cost efficiency and effectiveness of [...] Read more.

Bridges are an integral and important part of road networks, but monitoring their condition using traditional methods is expensive, dangerous, and laborious. This study examines the rapidly emerging field of drone-based transportation asset monitoring, focusing on analyzing the cost efficiency and effectiveness of drone applications in bridge condition monitoring. This research innovated a multi-dimensional framework that highlights the transformative role of drone technology in enhancing inspection accuracy, safety, and cost savings. Using statistical models and Monte Carlo simulations, the framework provides an extensive cost–benefit analysis to inform drone investment decisions. A case study demonstrates the utility of the framework in quantifying costs and benefits. Furthermore, a sensitivity analysis evaluates how variations in drone costs, driven by technological progress, can potentially influence adoption of the technology. Full article

(This article belongs to the Special Issue Sustainable and Digital Transformation of Road Infrastructures)

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19 pages, 5841 KiB

Open AccessArticle

Comparative Analysis of Soft Clay Improvement Using Ordinary and Grouted Sand Columns with Geosynthetic Reinforcement

by Mohammed Y. Fattah, Muthanna A. Al-Khafaji, Makki K. Mohsen and Mohamed Hafez

Infrastructures 2025, 10(3), 62; https://doi.org/10.3390/infrastructures10030062 - 13 Mar 2025

Abstract

Soft clay soil is known for its high compressibility and low bearing capacity, making it one of the most challenging soil types. Sand columns and sand layers reinforced with geosynthetics are effective techniques to enhance the performance of foundations built on soft clay. [...] Read more.

Soft clay soil is known for its high compressibility and low bearing capacity, making it one of the most challenging soil types. Sand columns and sand layers reinforced with geosynthetics are effective techniques to enhance the performance of foundations built on soft clay. Stone or sand columns improve load-bearing capacity by utilizing the natural lateral confinement of the soil. However, in very soft soil, a significant design challenge arises due to bulging in the stone columns, as the surrounding soil may not provide adequate confinement to support the required load capacity. This issue has been addressed by grouting the columns, resulting in highly stable and solid structures. Additionally, the grouting pressure enhances frictional resistance and fills any voids within the soil, contributing to increased overall stability. In the current study, soil improvement methods using ordinary sand columns and grouted sand columns were investigated and then compared with adding sand layers with geogrid reinforcement. The study demonstrated that grouted sand columns improved the bearing capacity by 90% over untreated clay. With geogrid reinforcement, sand columns achieved a 180% increase, while grouted columns with geogrid reinforcement reached a 260% improvement. Increasing the thickness of reinforced sand (H/B = 1.5) further raised capacity improvements to 300% for ungrouted and 420% for grouted columns. Full article

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