Infrastructures

33 pages, 5773 KB

Open AccessArticle

Predicting Operating Speeds of Passenger Cars on Single-Carriageway Road Tangents

by Juraj Leonard Vertlberg, Marijan Jakovljević, Borna Abramović and Marko Ševrović

Infrastructures 2025, 10(8), 221; https://doi.org/10.3390/infrastructures10080221 - 20 Aug 2025

Viewed by 447

This research addresses the challenge of predicting operating vehicles’ speeds (V85) on single-carriageway road tangents. While most previous models rely on preceding segment speeds or focus on curves, this research develops an independent prediction model specifically for road tangents, based on empirical data [...] Read more.

This research addresses the challenge of predicting operating vehicles’ speeds (V85) on single-carriageway road tangents. While most previous models rely on preceding segment speeds or focus on curves, this research develops an independent prediction model specifically for road tangents, based on empirical data collected in Croatia. A total of 46 locations across 23 road cross-sections were analysed, with operating speeds measured using field radar surveys and fixed traffic counters. Following a comprehensive correlation and multicollinearity analysis of 24 geometric, environmental, and traffic-related variables, a multiple linear regression model was developed using a training dataset (36 locations) and validated on a separate test set (10 locations). The model includes nine statistically significant predictors: shoulder type (gravel), edge line quality (excellent and satisfactory), pavement quality (excellent), average summer daily traffic (ASDT), crash ratio, edge lane presence, overtaking allowed, and heavy goods vehicle share. The model demonstrated strong predictive performance (R² = 0.89, RMSE = 5.24), with validation results showing an average absolute deviation of 2.43%. These results confirm the model’s reliability and practical applicability in road design and traffic safety assessments. Full article

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

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18 pages, 10610 KB

Open AccessArticle

Development of an Intelligent Monitoring System for Settlement Prediction of High-Fill Subgrade

by Manhong Liao, Kai Wang, Xin Zhou, Liang Tian, Junxin Wang, Haopeng Zhang, Yunchuan Du and Enhui Yang

Infrastructures 2025, 10(8), 220; https://doi.org/10.3390/infrastructures10080220 - 20 Aug 2025

Viewed by 471

Abstract

There is currently no mature calculation theory to accurately predict the settlement of high-fill subgrade. This paper developed an intelligent monitoring system to accurately predict the settlement of high-fill subgrade based on on-site experiments, and the back-propagation (BP) neural network model was used [...] Read more.

There is currently no mature calculation theory to accurately predict the settlement of high-fill subgrade. This paper developed an intelligent monitoring system to accurately predict the settlement of high-fill subgrade based on on-site experiments, and the back-propagation (BP) neural network model was used to predict the settlement of high-fill subgrade. The results show that multiple data preprocessing methods built into intelligent systems can automatically generate multi-point and correlation curves, and the system can identify and distinguish various influencing factors to improve the accuracy and reliability of monitoring data. There will be a certain initial settlement of subgrade in the initial stage after filling construction is completed, and the settlement rate at this stage is relatively fast. Afterwards, the soil enters a rapid consolidation stage, and the settlement rate of subgrade gradually slows down. Finally, the filling soil consolidation becomes stable, and the rate of subgrade settlement enters a relatively stable stage. In addition, the BP neural network model is a good method for predicting the settlement of high-fill subgrade. The research findings can provide inspiration for developing an intelligent monitoring system to accurately predict the settlement of high-fill subgrade. Full article

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27 pages, 3121 KB

Open AccessArticle

Dynamic Probabilistic Modeling of Concrete Strength: Markov Chains and Regression for Sustainable Mix Design

by Md. Shahariar Ahmed, Anica Tasnim, Md Ferdous Hasan and Golam Kabir

Infrastructures 2025, 10(8), 219; https://doi.org/10.3390/infrastructures10080219 - 20 Aug 2025

Viewed by 507

Abstract

Concrete is fundamental to modern construction, comprising 70% of all building materials and supporting an industry projected to reach $15 trillion by 2030. Predicting compressive strength—a key factor for structural safety and resource efficiency—remains a challenge, as conventional models often fail to capture [...] Read more.

Concrete is fundamental to modern construction, comprising 70% of all building materials and supporting an industry projected to reach $15 trillion by 2030. Predicting compressive strength—a key factor for structural safety and resource efficiency—remains a challenge, as conventional models often fail to capture the dynamic, time-dependent nature of strength development across mix compositions and curing intervals. This study proposes an integrated modeling framework using Markov Chain analysis and regression, validated on 135 samples from 27 mixtures with varying proportions of Portland Cement (PC), Fly Ash (FA), and Blast Furnace Slag (BFS) over curing periods from 3 to 180 days. The Markov Chain framework, integrated with regression analysis, models strength transitions across 10 states (9–42 MPa), with high accuracy (R² = 0.977, standard error = 3.27 MPa). Curing time (β = 0.079), PC proportion (β = 0.063), and BFS proportion (β = 0.051) are identified as key drivers, while higher FA content (β = 0.019) enhances long-term durability. Model validation using Coefficient of Variation (CoV = 15.57%) and mean absolute error confirms robust and consistent performance across mix designs. The framework supports tailored mix strategies—PC for early strength, BFS for durability, FA for sustainability—empowering engineers to optimize mix selection and curing strategies for efficient and durable concrete applications. Full article

(This article belongs to the Special Issue Sustainable Construction Materials’ Contribution to a Zero-Waste Future)

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14 pages, 2707 KB

Open AccessArticle

A Preliminary Investigation into the Performance of Artificial High Friction Aggregates Manufactured Using Geopolymer Cement-Based Mortars

by Allistair Wilkinson, Bryan Magee, David Woodward, Svetlana Tretsiakova-McNally and Patrick Lemoine

Infrastructures 2025, 10(8), 218; https://doi.org/10.3390/infrastructures10080218 - 19 Aug 2025

Viewed by 470

Abstract

Despite local and national road authorities striving to provide motorists with a durable and safe infrastructure environment, one in six UK roads are currently classed as being in poor condition. In terms of safety, Department for Transport statistics report high numbers of road [...] Read more.

Despite local and national road authorities striving to provide motorists with a durable and safe infrastructure environment, one in six UK roads are currently classed as being in poor condition. In terms of safety, Department for Transport statistics report high numbers of road incidents; 29,711 killed or seriously injured in 2023, representing little change compared to 2022. As such, reported in this paper is research aimed at developing artificial geopolymer cement mortar-based aggregate as a cost/environmentally attractive alternative to calcined bauxite for high friction surfacing applications. Work was undertaken in two distinct phases. In the first, the performance of alkali silicate-based geopolymers comprising a range of industrial wastes as binder materials was assessed using modified versions of standardized polished stone value and micro-Deval tests. In phase two, selected mixes were assessed for resistance to simulated wear by exposing test specimens to 20,000-wheel passes on an accelerated road test machine. Performance was further investigated using a dynamic friction test method developed by the Indiana Department of Transportation. Despite commercially sourced calcined bauxite aggregates exhibiting the highest performance levels, the findings from this preliminary research were generally positive, with acceptable levels of performance noted for manufactured geopolymer-based aggregates. For instance, in accordance with recommended levels of performance prescribed in BBA/HAPPAS standards, this included attainment of polished stone values higher than 65 and, following accelerated road testing, average texture depths greater than 1.1 mm. It is recognized that further research is needed to investigate geopolymer binder systems and blends of aggregate types, as well as artificial aggregate manufacturing procedures. 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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10 pages, 363 KB

Open AccessArticle

Multi-Source Information Fusion-Based Rock-Grade Hybrid Model for Tunnel Construction Process

by Yong Huang, Wei Fu, Xiewen Hu and Songli Han

Infrastructures 2025, 10(8), 217; https://doi.org/10.3390/infrastructures10080217 - 18 Aug 2025

Viewed by 333

Abstract

Rock grade is a key indicator guiding tunnel construction. In order to ensure the efficiency and safety of construction, it is necessary to accurately predict the rock grade of the unexcavated part of a tunnel. Currently, geological sketches and geophysical exploration methods can [...] Read more.

Rock grade is a key indicator guiding tunnel construction. In order to ensure the efficiency and safety of construction, it is necessary to accurately predict the rock grade of the unexcavated part of a tunnel. Currently, geological sketches and geophysical exploration methods can be employed to obtain multi-source and heterogeneous detection data. However, the key challenge lies in how to integrate various types of exploration data to predict the rock grade, which is the focus of the current research. In this paper, we propose a multi-source information fusion-based rock-grade hybrid model for the tunnel construction process. The proposed approach consists of several steps. In the first step, homogenization processing of the acquired multi-source and heterogeneous data, such as geological and TSP (Tunnel Seismic Prediction) detection data, is performed. This primarily includes feature extraction, spatial registration, and the filtering of anomalous data, aimed at enhancing the quality of the data. In the second step, considering the variations in the geological conditions of the construction face, this paper first stratifies the rock grades at the construction face. Subsequently, utilizing TSP detection data, a rock-grade prediction model is established by combining knowledge-driven and data-driven approaches. In the third step, based on the rock grade predictions obtained from the rock grade forecasting model established in the second step, an intelligent decision-making process is conducted by comparing these predictions with the rock grades anticipated during the design stage. This results in the determination of the final rock grade. Finally, the effectiveness of the proposed method is validated through comparison with experimental results. Full article

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19 pages, 3365 KB

Open AccessArticle

Exploring Causal Factor in Highway–Railroad-Grade Crossing Crashes: A Comparative Analysis

by Yubo Wang, Yubo Jiao, Liping Fu and Qiangqiang Shangguan

Infrastructures 2025, 10(8), 216; https://doi.org/10.3390/infrastructures10080216 - 18 Aug 2025

Viewed by 528

Abstract

Identification of causal factors in traffic crashes has always been a significant challenge in road safety studies. Traditional crash prediction models are limited in elucidating the underlying causal mechanisms in road crashes. This research explores the application of three graphic models, namely, the [...] Read more.

Identification of causal factors in traffic crashes has always been a significant challenge in road safety studies. Traditional crash prediction models are limited in elucidating the underlying causal mechanisms in road crashes. This research explores the application of three graphic models, namely, the Gaussian graphical model (GGM), causal Bayesian network (CBN) and graphic extreme gradient boosting (XGBoost), through a case study using highway–railroad-grade crossing (HRGC) inventory and collision data from Canada. The three modelling approaches have generally yielded consistent findings on various risk factors such as crossing control type, track angle, and exposure, showing their potential for identifying causal relationships through the interpretation of causal graphs. With the ability to make better causal inferences from crash data, the effectiveness of safety countermeasures could be more accurately and reliably estimated. 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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14 pages, 1599 KB

Open AccessArticle

Rural Roads’ Passing Sight Distance Control Along Crest Vertical Curves

by Stergios Mavromatis, Vassilios Matragos, Konstantinos Markos and Antonios Kontizas

Infrastructures 2025, 10(8), 215; https://doi.org/10.3390/infrastructures10080215 - 15 Aug 2025

Viewed by 389

Abstract

Passing sight distance (PSD) is a vital design element that directly imposes economic, as well as safety and operational, considerations. The provision of PSD is highly prioritized, at least for rural road sections without additional passing lanes. The paper investigates areas with PSD [...] Read more.

Passing sight distance (PSD) is a vital design element that directly imposes economic, as well as safety and operational, considerations. The provision of PSD is highly prioritized, at least for rural road sections without additional passing lanes. The paper investigates areas with PSD inadequacy on rural roads with crest vertical curves. The research is based on the German rural roads design guidelines, where PSD is currently dependent on the homogeneousness of the proposed road design classes and no longer on speed. Therefore, the required PSD for all the examined design classes was set to 600 m. The interaction between the road surface and the line of sight between the passing and the opposing vehicles was assessed through six different cases, while every case was associated with the resulting formulas. The analysis revealed that, excluding one situation for the EKL4 design class, the boundaries of PSD inadequacy were concentrated in advance and inside the vertical curve, and do not depend on the grade difference of the vertical curve but only on the crest vertical curvature rate value. The paper delivers a ready-to-use tool for engineers to identify areas with inadequate PSD in the early stages of the design process and avoid implementing costly additional passing lanes. 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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30 pages, 12270 KB

Open AccessArticle

Cross-Border Cascading Hazard Scenarios and Vulnerability Assessment of Levees and Bridges in the Sava River Basin

by Gašper Rak, Gorazd Novak, Matjaž Četina, Mirko Kosič, Andrej Anžlin, Nicola Rossi, Meho Saša Kovačević and Mario Bačić

Infrastructures 2025, 10(8), 214; https://doi.org/10.3390/infrastructures10080214 - 14 Aug 2025

Viewed by 485

Abstract

This study investigates cross-border cascading hazards and infrastructure vulnerabilities in the Sava River Basin, a seismically active and flood-prone region spanning the Slovenia–Croatia border. Conducted within the CROSScade project, the research focuses on assessing cross-border hazards and the vulnerabilities of levees and bridges. [...] Read more.

This study investigates cross-border cascading hazards and infrastructure vulnerabilities in the Sava River Basin, a seismically active and flood-prone region spanning the Slovenia–Croatia border. Conducted within the CROSScade project, the research focuses on assessing cross-border hazards and the vulnerabilities of levees and bridges. Key earthquake and flood scenarios were identified using advanced hydraulic and seismic modelling, forming the basis for evaluating the cascading effects of these events, including the potential failure of hydropower plants and associated flood protection systems. The analysis reveals that levees are particularly vulnerable to failure during the recession phase of flooding that follows an earthquake. At the same time, bridges are primarily affected by seismic loading, with minimal structural impact from flood forces. These findings underscore the pressing need for enhanced cross-border collaboration, updated design standards, and the reinforcement of critical infrastructure. The study provides essential insights for multi-hazard resilience planning and emphasises the importance of integrated risk assessments in managing cascading disaster impacts across national boundaries. Full article

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35 pages, 2113 KB

Open AccessReview

A Review of the Characteristics of Recycled Aggregates and the Mechanical Properties of Concrete Produced by Replacing Natural Coarse Aggregates with Recycled Ones—Fostering Resilient and Sustainable Infrastructures

by Gerardo A. F. Junior, Juliana C. T. Leite, Gabriel de P. Mendez, Assed N. Haddad, José A. F. Silva and Bruno B. F. da Costa

Infrastructures 2025, 10(8), 213; https://doi.org/10.3390/infrastructures10080213 - 14 Aug 2025

Viewed by 1562

Abstract

The construction industry is responsible for 50% of mineral resource extraction and 35% of greenhouse gas (GHG) emissions. In this context, concrete stands out as one of the most consumed materials in the world. More than 30 billion tons of this material are [...] Read more.

The construction industry is responsible for 50% of mineral resource extraction and 35% of greenhouse gas (GHG) emissions. In this context, concrete stands out as one of the most consumed materials in the world. More than 30 billion tons of this material are produced annually, resulting in the extraction of around 19.4 billion tons of aggregates (mainly sand and gravel) per year. Therefore, it is urgent to develop strategies that aim to minimize the environmental impacts arising from this production chain. Currently, one of the most widely adopted solutions is the production of concrete through the reuse of construction and demolition waste. Thus, the objective of this research is to conduct a systematic literature review (SLR) on the use of recycled aggregates in concrete production, aiming to increase urban resilience by reducing the consumption of natural aggregates. An extensive search was performed in one of the most respected scientific databases (Scopus), and after a careful selection process, the main articles related to the topic were considered eligible through the PRISMA protocol. The selected manuscripts were then subjected to bibliographic and bibliometric analyses, allowing us to reach the state-of-the-art on the subject. The results obtained on the replacement rates of natural aggregate by recycled aggregate indicate that the recommendations vary from 20 to 60%, and these rates may be higher as long as the recycled aggregate is characterized, and may reach up to 100% as long as the matric concrete has a minimum compressive strength of 60 MPa. The specific gravity of most recycled aggregates ranges from 1.91 to 2.70, maintaining an average density of 2.32 g/cm³. Residual mortar adhered to recycled aggregates ranges from 20 to 56%. The water absorption process of recycled aggregate can vary from 2 to 15%. The mechanical strength of mixtures with recycled aggregates is significantly reduced due to the amount of mortar adhered to the aggregates. The use of recycled aggregates results in a compressive strength approximately 2.6 to 43% lower than that of concrete with natural aggregates, depending on the replacement rate. The same behavior was identified in relation to tensile strength. The modulus of elasticity showed a reduction of 25%, and the flexural strength was reduced by up to 15%. Full article

(This article belongs to the Special Issue Smart, Sustainable and Resilient Infrastructures, 3rd Edition)

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18 pages, 2364 KB

Open AccessArticle

Deterioration Modeling of Pavement Performance in Cold Regions Using Probabilistic Machine Learning Method

by Zhen Liu, Xingyu Gu and Wenxiu Wu

Infrastructures 2025, 10(8), 212; https://doi.org/10.3390/infrastructures10080212 - 14 Aug 2025

Viewed by 670

Abstract

Accurate and reliable modeling of pavement deterioration is critical for effective infrastructure management. This study proposes a probabilistic machine learning framework using Bayesian-optimized Natural Gradient Boosting (BO-NGBoost) to predict the International Roughness Index (IRI) of asphalt pavements in cold climates. A dataset only [...] Read more.

Accurate and reliable modeling of pavement deterioration is critical for effective infrastructure management. This study proposes a probabilistic machine learning framework using Bayesian-optimized Natural Gradient Boosting (BO-NGBoost) to predict the International Roughness Index (IRI) of asphalt pavements in cold climates. A dataset only for cold regions was constructed from the Long-Term Pavement Performance (LTPP) database, integrating multiple variables related to climate, structure, materials, traffic, and constructions. The BO-NGBoost model was evaluated against conventional deterministic models, including artificial neural networks, random forest, and XGBoost. Results show that BO-NGBoost achieved the highest predictive accuracy (R² = 0.897, RMSE = 0.184, MAE = 0.107) while also providing uncertainty quantification for risk-based maintenance planning. BO-NGBoost effectively captures long-term deterioration trends and reflects increasing uncertainty with pavement age. SHAP analysis reveals that initial IRI, pavement age, layer thicknesses, and precipitation are key factors, with freeze–thaw cycles and moisture infiltration driving faster degradation in cold climates. This research contributes a scalable and interpretable framework that advances pavement deterioration modeling from deterministic to probabilistic paradigms and provides practical value for more uncertainty-aware infrastructure decision-making. Full article

(This article belongs to the Special Issue Pavement Performance and Maintenance: Smart Technologies and Sustainable Practices)

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15 pages, 1395 KB

Open AccessArticle

Multi-Model Intelligent Prediction of Rock Integrity in Tunnels Based on Geological Differences of Ground-Penetrating Radar Exploration Workfaces

by Yong Huang, Wei Fu and Xiewen Hu

Infrastructures 2025, 10(8), 211; https://doi.org/10.3390/infrastructures10080211 - 13 Aug 2025

Viewed by 317

Abstract

Intelligent prediction of rock integrity is essential for tunneling construction. Ground-Penetrating Radar (GPR), a high-resolution detection technique, is usually used for rock integrity prediction. However, the geological conditions of the detection workface are rarely considered when utilizing the GPR to forecast rock integrity. [...] Read more.

Intelligent prediction of rock integrity is essential for tunneling construction. Ground-Penetrating Radar (GPR), a high-resolution detection technique, is usually used for rock integrity prediction. However, the geological conditions of the detection workface are rarely considered when utilizing the GPR to forecast rock integrity. In this paper, a multi-model intelligent prediction method for tunnel rock integrity based on geological differences of GPR exploration workfaces is proposed. Firstly, the structural features are extracted from the GPR detection data through matrix calculations. A statistic is proposed to judge the abnormal data, and filtering rules are formulated to eliminate abnormal data. Then, considering the difference of geological conditions of the GPR exploration workface, multi-models are established with different degrees of fragmentation of the exploration workface. Finally, the validity of the multi-model prediction method is proved by practical engineering verification. Full article

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14 pages, 3153 KB

Open AccessArticle

The Analysis of Axial Compression Performance of Reinforced Concrete Columns Strengthened with Prestressed Carbon Fiber Sheets

by Yiquan Lv, Yang Teng, Xing Li, Junli Liu, Chunling Lu and Cheng Zhang

Infrastructures 2025, 10(8), 210; https://doi.org/10.3390/infrastructures10080210 - 13 Aug 2025

Viewed by 390

Abstract

Current research primarily focuses on using CFRP materials to strengthen small or medium-sized test specimens. To address this, our study employed ABAQUS software to analyze the axial compression behavior of large-scale reinforced concrete (RC) columns strengthened with prestressed carbon fiber reinforced polymer (CFRP) [...] Read more.

Current research primarily focuses on using CFRP materials to strengthen small or medium-sized test specimens. To address this, our study employed ABAQUS software to analyze the axial compression behavior of large-scale reinforced concrete (RC) columns strengthened with prestressed carbon fiber reinforced polymer (CFRP) sheets. We conducted comparative analyses on key parameters: the prestress level applied to the CFRP, the width of CFRP strips, the spacing between strips, the confinement ratio, and the overall load–displacement curves of the columns. The results demonstrate that applying prestress significantly improves the efficiency of stress transfer in the CFRP sheet, effectively mitigating the stress lag phenomenon common in traditional CFRP strengthening, leading to a substantially enhanced strengthening effect. The CFRP wrapping method critically impacts performance: increasing the confinement ratio enhanced ultimate load capacity by 21.8–59.9%; reducing the strip spacing increased capacity by 21.8–50.4%; and widening the strips boosted capacity by 38.7–58%. Although full wrapping achieved the highest capacity increase (up to 73.2%), it also incurred significantly higher costs. To ensure the required strengthening effect while optimizing economic efficiency and CFRP material utilization, the strip wrapping technique is recommended. For designing optimal reinforcement, priority should be given to optimizing the confinement ratio first, followed by adjusting strip width and spacing. Proper optimization of these parameters significantly enhances the strengthened member’s ultimate load capacity, ductility, and energy dissipation capacity. This study enriches the theoretical foundation for prestressed CFRP strengthening and provides an essential basis for rationally selecting prestress levels and layout parameters in engineering practice, thereby aiding the efficient design of strengthening projects for structures like bridges, with significant engineering and scientific value. Full article

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33 pages, 7645 KB

Open AccessArticle

Evaluation of Rail Corrugation and Roughness Using In-Service Tramway Bogie Frame Vibrations: Addressing Challenges and Perspectives

by Krešimir Burnać, Ivo Haladin and Katarina Vranešić

Infrastructures 2025, 10(8), 209; https://doi.org/10.3390/infrastructures10080209 - 12 Aug 2025

Viewed by 453

Abstract

Rail corrugation and roughness represent typical irregularities on railway and tramway tracks, which cause increased dynamic forces, high-frequency vibrations, reduced riding comfort, shorter track lifespan, higher maintenance costs, and increased noise levels. Roughness and corrugation can be measured by evaluating the unevenness of [...] Read more.

Rail corrugation and roughness represent typical irregularities on railway and tramway tracks, which cause increased dynamic forces, high-frequency vibrations, reduced riding comfort, shorter track lifespan, higher maintenance costs, and increased noise levels. Roughness and corrugation can be measured by evaluating the unevenness of the rail longitudinal running surface, which can be conducted using handheld devices or trolleys (directly on the track). Alternatively, vehicle or track-based indirect methods offer practical solutions for determining the condition of the rail running surface. This paper presents a methodology for rail corrugation and roughness evaluation, using bogie frame vibration data from an instrumented in-service tramway vehicle operating on Zagreb’s tramway network. Furthermore, it investigates the effects of various factors on the evaluation method, including wheel roughness, lateral positioning, signal processing methods, horizontal geometry, wheel–rail contact force, and tramway vehicle vibroacoustic characteristics. It was concluded that a simplified methodology that did not include transfer functions or wheel roughness measurements yielded relatively good results for evaluating rail corrugation and roughness across several wavelength bands. To improve the presented methodology, future research should assess the vehicle’s vibroacoustic characteristics with experimental hammer impact tests, measure the influence of wheel roughness on wheel–rail contact and bogie vibrations, and refine the measurement campaign by increasing test runs, limiting speed variation, and conducting controlled tests. Full article

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

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24 pages, 3897 KB

Open AccessArticle

Evolution Law and Prediction Model of Anti-Skid and Wear-Resistant Performance of Asphalt Pavement Based on Aggregate Types and Deepened Texture

by Shaopeng Zheng, Zilong Zhang, Peiwen Hao, Jian Ma and Liangliang Chen

Infrastructures 2025, 10(8), 208; https://doi.org/10.3390/infrastructures10080208 - 12 Aug 2025

Viewed by 496

Abstract

This study investigates the evolution laws and prediction models of anti-skid and wear-resistant performance for asphalt pavements during the operation period. Using a combination of indoor accelerated wear tests and field detection, mixed specimens are prepared with SBS modified asphalt, limestone, and basalt [...] Read more.

This study investigates the evolution laws and prediction models of anti-skid and wear-resistant performance for asphalt pavements during the operation period. Using a combination of indoor accelerated wear tests and field detection, mixed specimens are prepared with SBS modified asphalt, limestone, and basalt aggregates. Through accelerated wear tests of different durations, the structural depth and friction coefficient are measured. Combined with the field data from the G56 K2319 section of the Hangrui Expressway, the decay laws of anti-skid performance are analyzed, and prediction models are established. The results show that the anti-skid performance of basalt mixtures is superior to that of limestone. The deepened structure technology significantly enhances the performance of basalt but has a negative impact on the pendulum value of limestone. The influence degrees of wear duration, aggregate type, and deepened structure state on structural depth and pendulum value vary. The initial structural depth of basalt mixtures (0.85 mm) is 11.8% higher than that of limestone (0.76 mm). The longitudinal pendulum value of basalt (44) is 10% higher than that of limestone (40), while the transverse pendulum value of limestone (50) is 4.2% higher than that of basalt (48). After 21 h of wear, the structural depth of basalt (0.68 mm) is 4.6% higher than that of limestone (0.65 mm), with a decay rate 23.6% lower. The pendulum value of basalt remains above 50, while limestone’s longitudinal pendulum value drops to 36 (10% lower than its initial value), even below the unmodified state. The influence order for structural depth is deepened structure state > wear duration > aggregate type, and for lateral pendulum value, it is wear duration > deepened structure state > aggregate type. There is a significant linear relationship between structural depth/pendulum value and wear duration, and the prediction models are reliable. The indoor accelerated wear of 44.5 h is equivalent to the field operation wear of 3 years. The research findings provide a theoretical basis for the evaluation of anti-skid performance, maintenance decision-making, and material optimization of asphalt pavements. Full article

(This article belongs to the Special Issue Pavement Performance and Maintenance: Smart Technologies and Sustainable Practices)

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36 pages, 3139 KB

Open AccessArticle

Blockchain Technology Adoption for Sustainable Construction Procurement Management: A Multi-Pronged Artificial Intelligence-Based Approach

by Atul Kumar Singh, Saeed Reza Mohandes, Pshtiwan Shakor, Clara Cheung, Mehrdad Arashpour, Callum Kidd and V. R. Prasath Kumar

Infrastructures 2025, 10(8), 207; https://doi.org/10.3390/infrastructures10080207 - 12 Aug 2025

Viewed by 1033

Abstract

While blockchain technology (BT) has gained attention in the construction industry, limited research has focused on its application in sustainable construction procurement management (SCPM). Addressing this gap, the present study investigates the key drivers influencing BT adoption in SCPM using a hybrid methodological [...] Read more.

While blockchain technology (BT) has gained attention in the construction industry, limited research has focused on its application in sustainable construction procurement management (SCPM). Addressing this gap, the present study investigates the key drivers influencing BT adoption in SCPM using a hybrid methodological approach. This study includes a systematic review of academic and grey literature, expert consultations, and quantitative analysis using advanced fuzzy-based algorithms, k-means clustering, and social network analysis (SNA). Data were collected through an online survey distributed to professionals experienced in SCPM and blockchain implementation. The Fuzzy DEMATEL results identify “high quality”, “decentralization and data security”, and “cost of the overall project” as the most critical drivers. Meanwhile, SNA highlights “stability of the system”, “overall performance of the project”, and “customer satisfaction” as the most influential nodes within the network. These insights provide actionable guidance for industry stakeholders aiming to advance SCPM through blockchain integration and contribute to theoretical advancements by proposing novel analytical frameworks. Full article

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

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22 pages, 3203 KB

Open AccessArticle

Axial Compression Behavior of Square RC Columns Confined by Rectangular BFRP and Hybrid Ties

by Amr M. A. Moussa, Arafa M. A. Ibrahim, Ahmed Elsayed, Zhishen Wu and Ahmed Monier

Infrastructures 2025, 10(8), 206; https://doi.org/10.3390/infrastructures10080206 - 8 Aug 2025

Viewed by 506

Abstract

This study investigates the axial compression behavior of square reinforced concrete (RC) columns confined by a novel type of rectangular closed basalt fiber-reinforced polymer (BFRP) tie fabricated using a continuous filament winding method, and hybrid steel–BFRP configurations. The proposed ties were developed to [...] Read more.

This study investigates the axial compression behavior of square reinforced concrete (RC) columns confined by a novel type of rectangular closed basalt fiber-reinforced polymer (BFRP) tie fabricated using a continuous filament winding method, and hybrid steel–BFRP configurations. The proposed ties were developed to overcome common limitations of conventional FRP stirrups, such as reduced tensile strength at bent regions and premature rupture. A total of five RC column specimens were tested under monotonic axial loading: one reference specimen with conventional steel ties, two specimens with BFRP ties spaced at 45 mm and 90 mm, and two hybrid specimens combining steel and BFRP ties. Experimental results showed that the steel-confined column achieved the highest peak axial load of 1793.2 kN and an ultimate strain value of 1.12. The specimen with closely spaced BFRP ties (45 mm) reached 94.7% of the peak load of the steel-confined specimen and exhibited over 137% higher axial strain capacity. The hybrid specimen with two interleaved BFRP ties achieved the highest confinement effectiveness ratio of 1.306. The findings demonstrate that the proposed BFRP ties offer a structurally viable and corrosion-resistant alternative to steel ties, particularly when used in hybrid systems. This research contributes to the development of durable, high-performance confinement strategies for RC columns in seismic and aggressive environmental conditions. Full article

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

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43 pages, 15193 KB

Open AccessArticle

Bio-Mitigation of Sulfate Attack and Enhancement of Crack Self-Healing in Sustainable Concrete Using Bacillus megaterium and sphaericus Bacteria

by Ibrahim AbdElFattah, Seleem S. E. Ahmad, Ahmed A. Elakhras, Ahmed A. Elshami, Mohamed A. R. Elmahdy and Attitou Aboubakr

Infrastructures 2025, 10(8), 205; https://doi.org/10.3390/infrastructures10080205 - 7 Aug 2025

Viewed by 1606

Abstract

Concrete cracks and sulfate degradation severely compromise structural durability, highlighting the need for sustainable solutions to enhance longevity and minimize environmental impact. This study assesses the efficacy of bacterial self-healing technology utilizing Bacillus megaterium (BM) and Bacillus sphaericus (BS) in enhancing the resistance [...] Read more.

Concrete cracks and sulfate degradation severely compromise structural durability, highlighting the need for sustainable solutions to enhance longevity and minimize environmental impact. This study assesses the efficacy of bacterial self-healing technology utilizing Bacillus megaterium (BM) and Bacillus sphaericus (BS) in enhancing the resistance of concrete to sulfate attacks and improving its mechanical properties. Bacterial suspensions (1% and 2.5% of cement weight) were mixed with concrete containing silica fume or fly ash (10% of cement weight) and cured in freshwater or sulfate solutions (2%, 5%, and 10% concentrations). Specimens were tested for compressive strength, flexural strength, and microstructure using a Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Spectroscopy (EDS), and X-ray diffraction (XRD) at various ages. The results indicate that a 2.5% bacterial content yielded the best performance, with BM surpassing BS, enhancing compressive strength by up to 41.3% and flexural strength by 52.3% in freshwater-cured samples. Although sulfate exposure initially improved early-age strength by 1.97% at 7 days, it led to an 8.5% loss at 120 days. Bacterial inclusion mitigated sulfate damage through microbially induced calcium carbonate precipitation (MICP), sealing cracks, and bolstering durability. Cracked specimens treated with BM recovered up to 93.1% of their original compressive strength, promoting sustainable, sulfate-resistant, self-healing concrete for more resilient infrastructure. Full article

(This article belongs to the Section Infrastructures Materials and Constructions)

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22 pages, 4426 KB

Open AccessArticle

A Digital Twin Platform for Real-Time Intersection Traffic Monitoring, Performance Evaluation, and Calibration

by Abolfazl Afshari, Joyoung Lee and Dejan Besenski

Infrastructures 2025, 10(8), 204; https://doi.org/10.3390/infrastructures10080204 - 4 Aug 2025

Viewed by 1311

Abstract

Emerging transportation challenges necessitate cutting-edge technologies for real-time infrastructure and traffic monitoring. To create a dynamic digital twin for intersection monitoring, data gathering, performance assessment, and calibration of microsimulation software, this study presents a state-of-the-art platform that combines high-resolution LiDAR sensor data with [...] Read more.

Emerging transportation challenges necessitate cutting-edge technologies for real-time infrastructure and traffic monitoring. To create a dynamic digital twin for intersection monitoring, data gathering, performance assessment, and calibration of microsimulation software, this study presents a state-of-the-art platform that combines high-resolution LiDAR sensor data with VISSIM simulation software. Intending to track traffic flow and evaluate important factors, including congestion, delays, and lane configurations, the platform gathers and analyzes real-time data. The technology allows proactive actions to improve safety and reduce interruptions by utilizing the comprehensive information that LiDAR provides, such as vehicle trajectories, speed profiles, and lane changes. The digital twin technique offers unparalleled precision in traffic and infrastructure state monitoring by fusing real data streams with simulation-based performance analysis. The results show how the platform can transform real-time monitoring and open the door to data-driven decision-making, safer intersections, and more intelligent traffic data collection methods. Using the proposed platform, this study calibrated a VISSIM simulation network to optimize the driving behavior parameters in the software. This study addresses current issues in urban traffic management with real-time solutions, demonstrating the revolutionary impact of emerging technology in intelligent infrastructure monitoring. Full article

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

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23 pages, 7257 KB

Open AccessArticle

The Development and Statistical Analysis of a Material Strength Database of Existing Italian Prestressed Concrete Bridges

by Michele D’Amato, Antonella Ranaldo, Monica Rosciano, Alessandro Zona, Michele Morici, Laura Gioiella, Fabio Micozzi, Alberto Poeta, Virginio Quaglini, Sara Cattaneo, Dalila Rossi, Carlo Pettorruso, Walter Salvatore, Agnese Natali, Simone Celati, Filippo Ubertini, Ilaria Venanzi, Valentina Giglioni, Laura Ierimonti, Andrea Meoni, Michele Titton, Paola Pannuzzo and Andrea Dall’Asta Show full author list Hide full author list

Infrastructures 2025, 10(8), 203; https://doi.org/10.3390/infrastructures10080203 - 2 Aug 2025

Cited by 1 | Viewed by 802

Abstract

This paper reports a statistical analysis of a database archiving information on the strengths of the materials in existing Italian bridges having pre- and post-tensioned concrete beams. Data were collected in anonymous form by analyzing a stock of about 170 bridges built between [...] Read more.

This paper reports a statistical analysis of a database archiving information on the strengths of the materials in existing Italian bridges having pre- and post-tensioned concrete beams. Data were collected in anonymous form by analyzing a stock of about 170 bridges built between 1960 and 2000 and located in several Italian regions. To date, the database refers to steel reinforcing bars, concrete, and prestressing steel, whose strengths were gathered from design nominal values, acceptance certificates, and in situ test results, all derived by consulting the available documents for each examined bridge. At first, this paper describes how the available data were collected. Then, the results of a statistical analysis are presented and commented on. Moreover, goodness-of-fit tests are carried out to verify the assumption validity of a normal distribution for steel reinforcing bars and prestressing steel, and a log-normal distribution for concrete. The database represents a valuable resource for researchers and practitioners for the assessment of existing bridges. It may be applied for the use of prior knowledge within a framework where Bayesian methods are included for reducing uncertainties. The database provides essential information on the strengths of the materials to be used for a simulated design and/or for verification in the case of limited knowledge. Goodness-of-fit tests make the collected information very useful, even if probabilistic methods are applied. Full article

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

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21 pages, 7203 KB

Open AccessArticle

Experimental Lateral Behavior of Porcelain-Clad Cold-Formed Steel Shear Walls Under Cyclic-Gravity Loading

by Caeed Reza Sowlat-Tafti, Mohammad Reza Javaheri-Tafti and Hesam Varaee

Infrastructures 2025, 10(8), 202; https://doi.org/10.3390/infrastructures10080202 - 2 Aug 2025

Viewed by 468

Abstract

Lightweight steel-framing (LSF) systems have become increasingly prominent in modern construction due to their structural efficiency, design flexibility, and sustainability. However, traditional facade materials such as stone are often cost-prohibitive, and brick veneers—despite their popularity—pose seismic performance concerns. This study introduces an innovative [...] Read more.

Lightweight steel-framing (LSF) systems have become increasingly prominent in modern construction due to their structural efficiency, design flexibility, and sustainability. However, traditional facade materials such as stone are often cost-prohibitive, and brick veneers—despite their popularity—pose seismic performance concerns. This study introduces an innovative porcelain sheathing system for cold-formed steel (CFS) shear walls. Porcelain has no veins thus it offers integrated and reliable strength unlike granite. Four full-scale CFS shear walls incorporating screwed porcelain sheathing (SPS) were tested under combined cyclic lateral and constant gravity loading. The experimental program investigated key seismic characteristics, including lateral stiffness and strength, deformation capacity, failure modes, and energy dissipation, to calculate the system response modification factor (R). The test results showed that configurations with horizontal sheathing, double mid-studs, and three blocking rows improved performance, achieving up to 21.1 kN lateral resistance and 2.5% drift capacity. The average R-factor was 4.2, which exceeds the current design code values (AISI S213: R = 3; AS/NZS 4600: R = 2), suggesting the enhanced seismic resilience of the SPS-CFS system. This study also proposes design improvements to reduce the risk of brittle failure and enhance inelastic behavior. In addition, the results inform discussions on permissible building heights and contribute to the advancement of CFS design codes for seismic regions. Full article

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19 pages, 5698 KB

Open AccessArticle

Enhancing Iced 8-Bundled Conductor Galloping Prediction for UHV Transmission Line Infrastructure Through High-Fidelity Aerodynamic Modeling

by Bolin Zhong, Mengqi Cai, Maoming Hu and Jiahao Sun

Infrastructures 2025, 10(8), 201; https://doi.org/10.3390/infrastructures10080201 - 1 Aug 2025

Viewed by 329

Abstract

Icing on eight-bundled conductors can significantly alter their aerodynamic behavior, potentially leading to structural instabilities such as galloping. This study employed wind tunnel experiments and numerical simulations to analyze the aerodynamic parameters of each iced conductor across various angles of attack. The simulations [...] Read more.

Icing on eight-bundled conductors can significantly alter their aerodynamic behavior, potentially leading to structural instabilities such as galloping. This study employed wind tunnel experiments and numerical simulations to analyze the aerodynamic parameters of each iced conductor across various angles of attack. The simulations incorporated detailed stranded conductor geometries to assess their influence on aerodynamic accuracy. Incorporating stranded geometry in simulations reduced average errors in lift and drag coefficients by 45–50% compared to smooth models. The Den Hartog coefficient prediction error decreased from 15.6% to 3.9%, indicating improved reliability in oscillation predictions. Additionally, conductors with larger windward areas exhibited more pronounced wake effects, with lower sub-conductors experiencing greater wake interference than upper ones. The above results illustrate that explicit modeling of stranded conductor surfaces enhances the precision of aerodynamic simulations, providing a more accurate framework for predicting icing-induced galloping in multi-bundled conductors. Full article

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31 pages, 5334 KB

Open AccessArticle

Tailoring a Three-Layer Track Model to Delay Instability and Minimize Critical Velocity Effects at Very High Velocities

by Zuzana Dimitrovová

Infrastructures 2025, 10(8), 200; https://doi.org/10.3390/infrastructures10080200 - 31 Jul 2025

Viewed by 255

Abstract

The aim of this paper is to tailor the geometry and material parameters of a three-layer railway track model to achieve favorable properties for the circulation of high-speed trains at very high velocities. The three layers imply that the model should have three [...] Read more.

The aim of this paper is to tailor the geometry and material parameters of a three-layer railway track model to achieve favorable properties for the circulation of high-speed trains at very high velocities. The three layers imply that the model should have three critical velocities for resonance. However, in many cases, some of these values are missing and must be replaced by pseudo-critical values. Since no resonance occurs at pseudo-critical velocities, even in the absence of damping, deflections never reach infinity. By using optimization techniques, it is possible to adjust the model’s parameters, so that the increase in vibrations remains minimal and does not pose a real danger. In this way, circulation velocities could be extended beyond the critical value, thereby increasing the network capacity and, consequently, improving the competitiveness of rail transport compared to other modes of transportation, thus contributing to decarbonization. The presented results are preliminary and require further analysis and validation. Several optimization techniques are implemented, leading to the establishment of designs that already have rather high pseudo-critical velocities. Further research will show how these theoretical findings can be utilized in practice. 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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23 pages, 9610 KB

Open AccessArticle

Research on the Design and Application of a Novel Curved-Mesh Circumferential Drainage Blind Pipe for Tunnels in Water-Rich Areas

by Wenti Deng, Xiabing Liu, Shaohui He and Jianfei Ma

Infrastructures 2025, 10(8), 199; https://doi.org/10.3390/infrastructures10080199 - 28 Jul 2025

Viewed by 585

Abstract

To address the issues of low permeability, clogging susceptibility, and insufficient circumferential bearing capacity of traditional drainage blind pipes behind tunnel linings in water-rich areas, this study proposes a novel curved-mesh circumferential drainage blind pipe specifically designed for such environments. First, through engineering [...] Read more.

To address the issues of low permeability, clogging susceptibility, and insufficient circumferential bearing capacity of traditional drainage blind pipes behind tunnel linings in water-rich areas, this study proposes a novel curved-mesh circumferential drainage blind pipe specifically designed for such environments. First, through engineering surveys and comparative analysis, the limitations and application demands of conventional circumferential annular drainage blind pipes in highway tunnels were identified. Based on this, the key parameters of the new blind pipe—including material, wall thickness, and aperture size—were determined. Laboratory tests were then conducted to evaluate the performance of the newly developed pipe. Subsequently, the pipe was applied in a real-world tunnel project, where a construction process and an in-service blockage inspection method for circumferential drainage pipes were proposed. Field application results indicate that, compared to commonly used FH50 soft permeable pipes and F100 semi-split spring pipes, the novel curved-mesh drainage blind pipe exhibits superior circumferential load-bearing capacity, anti-clogging performance, and deformation resistance. The proposed structure provides a total permeable area exceeding 17,500 mm², three to four times larger than that of conventional drainage pipes, effectively meeting the drainage requirements behind tunnel linings in high-water-content zones. The use of four-way connectors enhanced integration with other drainage systems, and inspection of the internal conditions confirmed that the pipe remained free of clogging and deformation. Furthermore, the curved-mesh design offers better conformity with the primary support and demonstrates stronger adaptability to complex installation conditions. Full article

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22 pages, 12147 KB

Open AccessTechnical Note

Effects of the Aggregate Shape and Petrography on the Durability of Stone Mastic Asphalt

by Alain Stony Bile Sondey, Vincent Aaron Maleriado, Helga Ros Fridgeirsdottir, Damian Serwin, Carl Christian Thodesen and Diego Maria Barbieri

Infrastructures 2025, 10(8), 198; https://doi.org/10.3390/infrastructures10080198 - 26 Jul 2025

Viewed by 596

Abstract

Compared to traditional dense asphalt concrete mixtures, stone mastic asphalt (SMA) generally offers superior performance in terms of its mechanical resistance and extended pavement lifespan. Focusing on the Norwegian scenario, this laboratory-based study investigated the durability of SMA considering the influence of the [...] Read more.

Compared to traditional dense asphalt concrete mixtures, stone mastic asphalt (SMA) generally offers superior performance in terms of its mechanical resistance and extended pavement lifespan. Focusing on the Norwegian scenario, this laboratory-based study investigated the durability of SMA considering the influence of the aggregate shape and petrography. The rock aggregates were classified according to three different-shaped refinement stages involving vertical shaft impact crushing. Further, the aggregates were sourced from three distinct locations (Jelsa, Tau and Dirdal) characterized by different petrographic origins: granodiorite, quartz diorite and granite, respectively. Two mixtures with maximum aggregate sizes of 16 mm (SMA 16) and 11 mm (SMA 11) were designed according to Norwegian standards and investigated in terms of their durability performance. In this regard, two main functional tests were performed for the asphalt mixture, namely resistance against permanent deformation and abrasion by studded tyres, and one for the asphalt mortar, namely water sensitivity. Overall, the best test results were related to the aggregates sourced from Jelsa and Tau, thus highlighting that the geological origin exerts a major impact on SMA’s durability performance. On the other hand, the different aggregate shapes related to the crushing refinement treatments seem to play an effective but secondary role. Full article

(This article belongs to the Special Issue Sustainable Materials, Design, Maintenance, and Management for Transport Infrastructure)

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18 pages, 7521 KB

Open AccessArticle

Study on Optimization of Construction Parameters and Schemes for Complex Connecting Tunnels of Extra-Long Highway Tunnels Based on Field Monitoring and Numerical Simulation

by Shaohui He, Jiaxuan Liu, Dawei Huang and Jianfei Ma

Infrastructures 2025, 10(8), 197; https://doi.org/10.3390/infrastructures10080197 - 26 Jul 2025

Viewed by 412

Abstract

To study the optimization of construction parameters and schemes for complex connecting tunnels in extra-long highway tunnels in granite strata, the research team, relying on the construction project of the complex connecting tunnel between the Xiaolongmen Extra-long Highway Tunnel and the ultra-deep shaft, [...] Read more.

To study the optimization of construction parameters and schemes for complex connecting tunnels in extra-long highway tunnels in granite strata, the research team, relying on the construction project of the complex connecting tunnel between the Xiaolongmen Extra-long Highway Tunnel and the ultra-deep shaft, established an on-site monitoring scheme and a refined numerical simulation model. It systematically analyzed the impact of various construction parameters on the construction process of connecting tunnels and the main tunnel, and on this basis, optimized the construction scheme, improving construction efficiency. The research results show that (1) after the excavation of the connecting tunnel, the confining pressure at the top of the working face decreases rapidly, while the confining pressure on both sides increases rapidly; the extreme point of the confining pressure decrease is located at the central point at the top of the excavated working face. (2) For Class III surrounding rock excavated using the full-face blasting method, the maximum influence range of working face excavation on the stratum along the tunneling direction is approximately 4D (where D represents the excavation step). (3) The larger the excavation step of the connecting tunnel, the more obvious the stress concentration phenomenon at the central point of the working face arch crown, and the excavation step should be optimally controlled within the range of 2–3 m. (4) When explosives in the blast hole adopt decoupled charging, the ratio of borehole diameter to charge diameter can be increased to utilize the air gap to buffer the energy generated by the explosion. Full article

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18 pages, 2723 KB

Open AccessArticle

Study on Harmless Treatment and Performance of Phosphogypsum-Based Inorganic Cementing Material

by Hui Xiang, Chenyang Dong, Hao Wu, Xiaodi Hu, Bo Gao, Zhiwei Fan, Jiuming Wan, Yuan Ma and Hongtao Guan

Infrastructures 2025, 10(8), 196; https://doi.org/10.3390/infrastructures10080196 - 25 Jul 2025

Cited by 1 | Viewed by 503

Abstract

Phosphogypsum, a by-product of phosphate fertilizer production, was predominantly used as a supplementary additive in recycled construction materials. However, there are few detailed studies on utilizing phosphogypsum as the primary component in inorganic cementing materials while achieving cost-effective detoxification. This study aimed to [...] Read more.

Phosphogypsum, a by-product of phosphate fertilizer production, was predominantly used as a supplementary additive in recycled construction materials. However, there are few detailed studies on utilizing phosphogypsum as the primary component in inorganic cementing materials while achieving cost-effective detoxification. This study aimed to develop a harmless phosphogypsum-based inorganic cementing material (PICM) mainly based on phosphogypsum, in which cement, quicklime, and a stabilizer were used as additives. Harmful ions and acidity were first detected through X-ray fluorescence and ion chromatography and then harmlessly treated with quicklime. Compaction parameters, mechanical performance, X-ray diffraction analysis, moisture, and freezing resistance were characterized successively. The results illustrated that fluoride and phosphate ions were the primary soluble contaminants, whose leaching solution concentration can be reduced to 15.31 mg/L and undetectable with 2% quicklime through the mass proportion of phosphogypsum added and mixed. Meanwhile, the corresponding pH value was also raised to over 8. Cement content and quicklime were positively correlated with PICM’s maximum dry density. PICM with 25% cement and 2.5% stabilizer presented the highest unconfined compression strength, and flexural strength did not show significant regularity. PICM was mainly composed of quartz, gypsum, ettringite, and calcite, whose content decreased as cement content and quicklime content increased. Stabilizer, quicklime and cement content were positively correlated with PICM’s freezing and moisture resistance. Full article

(This article belongs to the Section Sustainable Infrastructures)

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21 pages, 4886 KB

Open AccessArticle

Field-Test-Driven Sensitivity Analysis and Model Updating of Aging Railroad Bridge Structures Using Genetic Algorithm Optimization Approach

by Rahul Anand, Sachin Tripathi, Celso Cruz De Oliveira and Ramesh B. Malla

Infrastructures 2025, 10(8), 195; https://doi.org/10.3390/infrastructures10080195 - 25 Jul 2025

Viewed by 553

Abstract

Aging railroad bridges present complex challenges due to advancing deterioration and outdated design assumptions. This study develops a comprehensive analytical approach for assessing an aging steel truss railroad bridge through finite element (FE) modeling, sensitivity analysis, and model updating, supported by field testing. [...] Read more.

Aging railroad bridges present complex challenges due to advancing deterioration and outdated design assumptions. This study develops a comprehensive analytical approach for assessing an aging steel truss railroad bridge through finite element (FE) modeling, sensitivity analysis, and model updating, supported by field testing. An initial FE model of the bridge was created based on original drawings and field observations. Field testing using a laser Doppler vibrometer captured the bridge’s dynamic response (vibrations and deflections) under regular train traffic. Key structural parameters (material properties, section properties, support conditions) were identified and varied in a sensitivity analysis to determine their influence on model outputs. A hybrid sensitivity analysis combining log-normal sampling and a genetic algorithm (GA) was employed to explore the parameter space and calibrate the model. The GA optimization tuned the FE model parameters to minimize discrepancies between simulated results and field measurements, focusing on vertical deflections and natural frequencies. The updated FE model showed significantly improved agreement with observed behavior; for example, vertical deflections under a representative train were matched within a few percent, and natural frequencies were accurately reproduced. This validated model provides a more reliable tool for predicting structural performance and fatigue life under various loading scenarios. The results demonstrate that integrating field data, sensitivity analysis, and model updating can greatly enhance the accuracy of structural assessments for aging railroad bridges, supporting more informed maintenance and management decisions. Full article

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

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24 pages, 1295 KB

Open AccessArticle

A Performance-Based Ranking Approach for Optimizing NDT Selection for Post-Tensioned Bridge Assessment

by Carlo Pettorruso, Dalila Rossi and Virginio Quaglini

Infrastructures 2025, 10(8), 194; https://doi.org/10.3390/infrastructures10080194 - 23 Jul 2025

Viewed by 451

Abstract

Post-tensioned (PT) reinforced concrete bridges are particularly vulnerable structures, as the deterioration of internal tendons is often difficult to detect using conventional inspection methods or visual assessments. This paper introduces a practical framework for ranking non-destructive testing (NDT) techniques employed to assess PT [...] Read more.

Post-tensioned (PT) reinforced concrete bridges are particularly vulnerable structures, as the deterioration of internal tendons is often difficult to detect using conventional inspection methods or visual assessments. This paper introduces a practical framework for ranking non-destructive testing (NDT) techniques employed to assess PT systems. The ranking is based on four performance categories: measurement accuracy, ease of use, cost, and impact of disruption to bridge operations on traffic. For each NDT technique, a score is assigned for each evaluation category, and the final ranking is determined using the weighted sum model (WSM). This approach enables the final assessment to reflect the priorities of different decision-making contexts defined by the end-user such as accuracy-oriented, cost-oriented, and impact-oriented scenarios. The proposed method is then applied to an existing bridge in order to practically demonstrate its effectiveness and the flexibility of the proposed criteria. Full article

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

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30 pages, 10277 KB

Open AccessArticle

A Finite Element Formulation for True Coupled Modal Analysis and Nonlinear Seismic Modeling of Dam–Reservoir–Foundation Systems: Application to an Arch Dam and Validation

by André Alegre, Sérgio Oliveira, Jorge Proença, Paulo Mendes and Ezequiel Carvalho

Infrastructures 2025, 10(8), 193; https://doi.org/10.3390/infrastructures10080193 - 22 Jul 2025

Viewed by 481

Abstract

This paper presents a formulation for the dynamic analysis of dam–reservoir–foundation systems, employing a coupled finite element model that integrates displacements and reservoir pressures. An innovative coupled approach, without separating the solid and fluid equations, is proposed to directly solve the single non-symmetrical [...] Read more.

This paper presents a formulation for the dynamic analysis of dam–reservoir–foundation systems, employing a coupled finite element model that integrates displacements and reservoir pressures. An innovative coupled approach, without separating the solid and fluid equations, is proposed to directly solve the single non-symmetrical governing equation for the whole system with non-proportional damping. For the modal analysis, a state–space method is adopted to solve the coupled eigenproblem, and complex eigenvalues and eigenvectors are computed, corresponding to non-stationary vibration modes. For the seismic analysis, a time-stepping method is applied to the coupled dynamic equation, and the stress–transfer method is introduced to simulate the nonlinear behavior, innovatively combining a constitutive joint model and a concrete damage model with softening and two independent scalar damage variables (tension and compression). This formulation is implemented in the computer program DamDySSA5.0, developed by the authors. To validate the formulation, this paper provides the experimental and numerical results in the case of the Cahora Bassa dam, instrumented in 2010 with a continuous vibration monitoring system designed by the authors. The good comparison achieved between the monitoring data and the dam–reservoir–foundation model shows that the formulation is suitable for simulating the modal response (natural frequencies and mode shapes) for different reservoir water levels and the seismic response under low-intensity earthquakes, using accelerograms measured at the dam base as input. Additionally, the dam’s nonlinear seismic response is simulated under an artificial accelerogram of increasing intensity, showing the structural effects due to vertical joint movements (release of arch tensions near the crest) and the concrete damage evolution. Full article

(This article belongs to the Special Issue Advances in Dam Engineering of the 21st Century)

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26 pages, 4303 KB

Open AccessArticle

Thermal Degradation and Microstructural Evolution of Geopolymer-Based UHPC with Silica Fume and Quartz Powder

by Raghda A. Elhefny, Mohamed Abdellatief, Walid E. Elemam and Ahmed M. Tahwia

Infrastructures 2025, 10(8), 192; https://doi.org/10.3390/infrastructures10080192 - 22 Jul 2025

Viewed by 622

Abstract

The durability and fire resilience of concrete structures are increasingly critical in modern construction, particularly under elevated-temperature exposure. With this context, the current study explores the thermal and microstructural characteristics of geopolymer-based ultra-high-performance concrete (G-UHPC) incorporating quartz powder (QP) and silica fume (SF) [...] Read more.

The durability and fire resilience of concrete structures are increasingly critical in modern construction, particularly under elevated-temperature exposure. With this context, the current study explores the thermal and microstructural characteristics of geopolymer-based ultra-high-performance concrete (G-UHPC) incorporating quartz powder (QP) and silica fume (SF) after exposure to elevated temperatures. SF was used at 15% and 30% to partially replace the precursor material, while QP was used at 25%, 30%, and 35% as a partial replacement for fine sand. The prepared specimens were exposed to 200 °C, 400 °C, and 800 °C, followed by air cooling. Mechanical strength tests were conducted to evaluate compressive and flexural strengths, as well as failure patterns. Microstructural changes due to thermal exposure were assessed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). Among the prepared mixtures, the 30SF35QP mixture exhibited the highest compressive strength (156.0 MPa), followed by the 15SF35QP mix (146.83 MPa). The experimental results demonstrated that G-UHPC underwent varying levels of thermal degradation across the 200–800 °C range yet displayed excellent resistance to thermal spalling. At 200 °C, compressive strength increased due to enhanced geopolymerization, with the control mix showing a 29.8% increase. However, significant strength reductions were observed at 800 °C, where the control mix retained only 30.8% (32.0 MPa) and the 30SF25QP mixture retained 28% (38.0 MPa) of their original strengths. Despite increased porosity and cracking at 800 °C, the 30SF35QP mixture exhibited superior strength retention due to its denser matrix and reduced voids. The EDS results confirmed improved gel stability in the 30% SF mixtures, as evidenced by higher silicon content. These findings suggest that optimizing SF and QP content significantly enhances the fire resistance and structural integrity of G-UHPC, providing practical insights for the design of sustainable, high-performance concrete structures in fire-prone environments. Full article

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