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Infrastructures

Infrastructures is an international, scientific, peer-reviewed open access journal on infrastructures published monthly online by MDPI. Infrastructures is affiliated to International Society for Maintenance and Rehabilitation of Transport Infrastructures (iSMARTi) and their members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, ESCI (Web of Science), Inspec, and other databases.
Journal Rank: JCR - Q2 (Engineering, Civil) / CiteScore - Q1 (Building and Construction)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.8 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the second half of 2024).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.

Impact Factor: 2.7 (2023); 5-Year Impact Factor: 2.8 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2412-3811

Latest Articles

21 pages, 6826 KiB

Open AccessArticle

A Mixed FEM for Studying Jointed Concrete Pavement Blowups

by Daniele Baraldi

Infrastructures 2025, 10(4), 86; https://doi.org/10.3390/infrastructures10040086 - 4 Apr 2025

This work aims to study the compressive buckling and consequent blowup of jointed concrete pavements due to thermal rise. For this purpose, a simple and effective mixed FEM, originally introduced for performing static and buckling analyses of beams on elastic supports, is extended [...] Read more.

This work aims to study the compressive buckling and consequent blowup of jointed concrete pavements due to thermal rise. For this purpose, a simple and effective mixed FEM, originally introduced for performing static and buckling analyses of beams on elastic supports, is extended for performing a preliminary study of jointed concrete pavements. An elastic Euler–Bernoulli beam in frictionless and bilateral contact with an elastic support is considered. Three different elastic support models are assumed, namely a Winkler support, an elastic half-space (3D), and half-plane (2D). The transversal pavement joint or crack is modeled employing a hinge at the beam midpoint with nil rotational stiffness. Numerical tests are performed by determining critical loads and the corresponding modal shapes, with particular attention to the first minimum critical load related to pavement blowup. From a theoretical point of view, the results show that minimum critical loads converge to existing results in the case of Winkler support, whereas new results are obtained in the case of the 2D and 3D support types. Associated modal shapes have maximum upward displacements at the beam midpoint. The second and subsequent critical loads, together with the corresponding sinusoidal modal shapes, converge to existing results. From a practical point of view, minimum critical loads represent a lower bound for estimating axial forces due to thermal variation causing jointed pavement blowup. Full article

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21 pages, 7725 KiB

Open AccessArticle

Trip Generation Models for Transportation Impact Analyses of Shopping Centers in Croatia

by Deana Breški, Biljana Maljković and Mihaela Senjak

Infrastructures 2025, 10(4), 85; https://doi.org/10.3390/infrastructures10040085 - 4 Apr 2025

For effective transportation planning, land use, travel behavior, and infrastructure capacity should be optimized to support sustainable urban growth and reduce congestion. Every new site development generates traffic volume, which can affect the quality of traffic flow in the surrounding road network. Therefore, [...] Read more.

For effective transportation planning, land use, travel behavior, and infrastructure capacity should be optimized to support sustainable urban growth and reduce congestion. Every new site development generates traffic volume, which can affect the quality of traffic flow in the surrounding road network. Therefore, trip generation, which predicts future travel demand, is a crucial step in the traditional four-step transportation model. In this context, the main objective of this study is to develop a model for estimating vehicle trip generation due to the construction of a shopping center, which is a significant traffic generator. The survey was conducted in Split (Croatia) at five existing locations, and linear regression analysis was used to develop models for different time periods. The results indicated that vehicle trips are strongly correlated with the gross floor area of shopping centers, with a high coefficient of determination. Additionally, this study presents a comparison of measured traffic volumes with estimates using ITE Trip Generation Manual equations. The findings suggest that these vehicle trip estimates should be reduced by approximately 40%. Since no previous studies have been conducted on the impact of land use on trip generation in the Republic of Croatia, the developed models represent a first step in creating a database that should be expanded with new data. Estimating the traffic generated by a new site development is a crucial component of traffic management, as it helps planners and engineers assess its impact on the surrounding road network and implement necessary measures to ensure efficient and safe traffic flow. Full article

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

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32 pages, 2651 KiB

Open AccessReview

Effects of Crumb Rubber-Modified Asphalt as a Pavement Layer in Railways: A Scoping Review

by Milad Kazemian, Ebrahim Hadizadeh Raeisi, Ahmad Davari Ghezelhesar, Amir Hajimirzajan and Szabolcs Fischer

Infrastructures 2025, 10(4), 84; https://doi.org/10.3390/infrastructures10040084 - 3 Apr 2025

Railway track performance and durability face growing challenges from higher speeds, heavier axle loads, and changing environmental conditions. Crumb rubber-modified asphalt (CRMA) offers a sustainable solution by repurposing waste tires into a durable material for railway trackbeds, improving both performance and environmental impact. [...] Read more.

Railway track performance and durability face growing challenges from higher speeds, heavier axle loads, and changing environmental conditions. Crumb rubber-modified asphalt (CRMA) offers a sustainable solution by repurposing waste tires into a durable material for railway trackbeds, improving both performance and environmental impact. Following PRISMA-ScR guidelines, this scoping review synthesizes an extensive body of global research on the structural, mechanical, and environmental benefits of CRMA in railway trackbeds. A systematic literature search was conducted across major academic databases, covering studies published over several decades. Selection criteria focused on CRMA applications in railway trackbeds, using keywords such as “crumb rubber-modified asphalt”, “railway track vibration”, and “sustainable railway materials.” After rigorous screening and eligibility assessment, the most relevant peer-reviewed studies were included, emphasizing mechanical performance, durability, and environmental impact. Key findings indicate that CRMA effectively reduces ground vibrations, enhances load distribution, and lowers long-term maintenance costs while promoting sustainable waste management through tire recycling. However, challenges such as optimal mix design, potential emissions, and long-term bonding stability require further investigation. Additionally, the review was limited to English-language studies, potentially omitting relevant non-English research, and some reports were inaccessible during retrieval. This review maps critical research gaps, identifies key areas for future optimization, and highlights CRMA’s potential to advance resilient and eco-friendly railway infrastructure. Full article

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21 pages, 5472 KiB

Open AccessArticle

Mitigating Settlement and Enhancing Bearing Capacity of Adjacent Strip Footings Using Sheet Pile Walls: An Experimental Approach

by Ali M. Basha, Ahmed Yousry Akal and Mohamed H. Zakaria

Infrastructures 2025, 10(4), 83; https://doi.org/10.3390/infrastructures10040083 - 2 Apr 2025

In construction, closely spaced footings cause stress interactions that impact bearing capacity, settlement, and stability. This study experimentally evaluates the role of sheet pile walls (SPWs) in improving the performance of two adjacent strip footings—an existing footing and a newly placed footing—on sandy [...] Read more.

In construction, closely spaced footings cause stress interactions that impact bearing capacity, settlement, and stability. This study experimentally evaluates the role of sheet pile walls (SPWs) in improving the performance of two adjacent strip footings—an existing footing and a newly placed footing—on sandy soil. The influence of SPW penetration depth (L_s) and center-to-center spacing between footings (X) on settlement and bearing resistance under vertical loads was investigated. Experiments were conducted in a large-scale soil tank (330 × 30 cm, depth 210 cm), with X ranging from 300 mm to 1000 mm and SPW lengths varying from 0 mm to 1500 mm. The results show that SPWs significantly enhance foundation performance by reducing settlement and increasing bearing capacity. When L_s/B = 6, the settlement of the new footing (F₁) decreases by 48%, while the existing footing (F₂) sees reductions of 47%, 67%, and 77% at L_s/B = 3, 4, and 5, respectively, under 500 kN/m² stress. The bearing capacity of F1 increases by 53% when X = 300 mm, demonstrating strong interference effects. Conversely, the F₂ settlement increases as X decreases, with a 96% rise at X = 300 mm, but it stabilizes at L_s/B = 5. SPWs also shift failure from general shear to punching shear, modifying soil–structure interaction. These findings highlight the effectiveness of SPWs in mitigating settlement, enhancing load-bearing capacity, and optimizing foundation design in closely spaced footing systems. The results suggest that an SPW length-to-footing width ratio (L_s/B) between 4 and 5 is optimal for minimizing settlement and improving stability, with only a slight difference in effectiveness between these two ratios. Full article

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

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17 pages, 3783 KiB

Open AccessArticle

A Multi-Scale CNN-BiLSTM Framework with An Attention Mechanism for Interpretable Structural Damage Detection

by Shengping Wu and Jingliang Liu

Infrastructures 2025, 10(4), 82; https://doi.org/10.3390/infrastructures10040082 - 2 Apr 2025

Structural damage detection is essential for civil infrastructure safety. The challenges in noise sensitivity, multi-scale feature extraction, and handling bidirectional temporal dependencies are often encountered by traditional methods such as vibration analysis and computer vision. Although potential solutions are offered by recent deep-learning [...] Read more.

Structural damage detection is essential for civil infrastructure safety. The challenges in noise sensitivity, multi-scale feature extraction, and handling bidirectional temporal dependencies are often encountered by traditional methods such as vibration analysis and computer vision. Although potential solutions are offered by recent deep-learning advancements, limitations are frequently imposed by low interpretability and the incapability to adaptively prioritize crucial features within complex time-series data. To address these, a novel hybrid deep-learning framework is proposed. It is integrated with multi-scale convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and attention mechanisms. Localized time-frequency features are captured from vibration signals by the CNN using multi-scale kernels. Bidirectional temporal dependencies are skillfully captured by the BiLSTM. The interpretability is improved by the attention mechanism through dynamic feature weighting. Experiments on a simulated steel frame demonstrate that detection accuracy and robustness can be enhanced by this framework. This work promotes structural health monitoring, providing a practical tool for engineering applications. Full article

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22 pages, 7837 KiB

Open AccessArticle

Improved Yield Line Analysis and Innovative Methodology to Evaluate the Capacity of RC Barriers Subjected to Vehicular Collision Force

by Fahed H. Salahat, Hayder A. Rasheed, Christopher A. Jones and Isaac Klugh

Infrastructures 2025, 10(4), 81; https://doi.org/10.3390/infrastructures10040081 - 31 Mar 2025

Reinforced Concrete (RC) barriers are used for different purposes in the highway inventory. An important purpose is the use of concrete barriers to act as railing that protects bridge piers against vehicular collision force (VCF). Therefore, these barriers are designed to absorb the [...] Read more.

Reinforced Concrete (RC) barriers are used for different purposes in the highway inventory. An important purpose is the use of concrete barriers to act as railing that protects bridge piers against vehicular collision force (VCF). Therefore, these barriers are designed to absorb the collision energy and/or redirect the vehicle away from the parts being protected. Accurate estimation of the capacity of RC barriers during crash events is an important consideration in their design and placement. The American Association of State Highway and Transportation Officials (AASHTO) considers yield line analysis (YLA) with the V-shape failure pattern to predict the barrier capacity. AASHTO’s analysis method involves some assumptions that are intended to simplify the analysis process. Some of these assumptions have been shown to underestimate the actual barrier capacity and might disqualify many existing RC barriers from acting as intervening structures due to structural inadequacy. Many researchers have proposed alternative failure patterns and methodologies in an attempt to better predict the capacity of RC barriers. This research shows that AASHTO’s YLA, with the current V-shape failure pattern, can be improved and still predict the barrier capacity when some of the simplifying assumptions are eliminated. Also, the research presents an alternative innovative truss analogy model to predict the capacity of RC barriers. The results of the improved YLA and the proposed truss model are validated by finite element analysis (FEA) using Abaqus. The results of this research will help structural engineers in the highway industry to initially design new barriers for the intended capacity as well as estimate the capacity of existing ones. Full article

(This article belongs to the Special Issue Advances in Reinforced Concrete Infrastructure: Enhancing Structural Resilience and Promoting Sustainability)

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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

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

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

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

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

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

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

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

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

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

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

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

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

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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