Infrastructures

20 pages, 3155 KB

Open AccessArticle

Influence of Coarse Aggregate Geometry and Mineral Composition on the Durability of Asphalt Concrete

by Hussein K. Mohammad, Amjad H. Albayati and Mazen J. Al-Kheetan

Infrastructures 2025, 10(10), 263; https://doi.org/10.3390/infrastructures10100263 - 4 Oct 2025

The durability of asphalt concrete is highly dependent on the geometry and mineralogy of coarse aggregates, yet their combined influence on mechanical and moisture resistance properties is still not fully understood. This study evaluates the effects of coarse aggregate geometry, specifically flat and [...] Read more.

The durability of asphalt concrete is highly dependent on the geometry and mineralogy of coarse aggregates, yet their combined influence on mechanical and moisture resistance properties is still not fully understood. This study evaluates the effects of coarse aggregate geometry, specifically flat and elongated particle ratios and angularity, as well as mineral composition (quartz versus calcite), on asphalt mixture durability. The durability of mixtures was evaluated through Marshall properties as well as moisture susceptibility indicators, including the tensile strength ratio (TSR) and index of retained strength (IRS). Statistical analyses (ANOVA and t-tests) were also conducted to confirm the significance of the observed effects. Results showed that mixtures containing higher proportions of flat and elongated particles exhibited greater void content, reduced stability, and weaker moisture resistance, with the 1:5 flat-to-elongated ratio showing the most adverse impact (TSR 73.9%, IRS 69.2%). Conversely, increasing coarse aggregate angularity (CAA) enhanced mixture performance, with TSR values rising from 63.5% at 0% angularity to 81.2% at 100% angularity, accompanied by corresponding improvements in IRS. Mineral composition analysis further demonstrated that calcite-based aggregates achieved stronger bonding with asphalt binder and superior resistance to stripping compared to quartz-based ones. These findings confirm that aggregate geometry and mineralogy exert a decisive influence on asphalt mixture durability. They also highlight the need to revise current specifications that permit the use of uncrushed coarse aggregate in asphalt base courses, particularly when such layers may serve as surface courses in suburban or low-volume roads, where long-term resistance to moisture damage is critical. Full article

21 pages, 7289 KB

Open AccessArticle

Strength and Ductility Improvement of Low Confinement Spun Pile with Steel Jacket Strengthening

by Yuskar Lase, Mulia Orientilize, Widjojo Adi Prakoso, Jansen Reagen and Stevany Lydia Jedidjah Hugen

Infrastructures 2025, 10(10), 262; https://doi.org/10.3390/infrastructures10100262 - 3 Oct 2025

Abstract

Spun piles adjacent to the pile cap need sufficient confinement to ensure the formation of plastic hinges during severe earthquakes. However, the high confinement ratio required for precast piles according to ACI 318-19 results in tightly spaced spirals, which are difficult to implement. [...] Read more.

Spun piles adjacent to the pile cap need sufficient confinement to ensure the formation of plastic hinges during severe earthquakes. However, the high confinement ratio required for precast piles according to ACI 318-19 results in tightly spaced spirals, which are difficult to implement. Since higher confinement is only needed at specific regions of the pile, external transverse reinforcement using steel jacketing has been proposed as an alternative solution. An experimental and numerical study was conducted to evaluate the effectiveness. The experimental results showed that the jacket enhanced both the strength and energy dissipation of the connection, but had only a minor effect on its ductility. A parametric study using finite element analysis was performed to investigate the parameters influencing connection behavior. The results indicated that variations in jacket thickness did not significantly impact the connection’s performance. A jacket height equal to 1.53 times the pile diameter was found to be the maximum effective height. It was also observed that higher axial loads led to a sudden loss of connection strength, thereby reducing ductility. Partial bonding between the jacket, grout, and pile was found to be acceptable within a certain range. The numerical analysis found that the steel jacket increases the ductility. Full article

(This article belongs to the Topic Rehabilitation and Strengthening Techniques for Reinforced Concrete)

22 pages, 2815 KB

Open AccessArticle

Optimization of Pavement Maintenance Planning in Cambodia Using a Probabilistic Model and Genetic Algorithm

by Nut Sovanneth, Felix Obunguta, Kotaro Sasai and Kiyoyuki Kaito

Infrastructures 2025, 10(10), 261; https://doi.org/10.3390/infrastructures10100261 - 29 Sep 2025

Abstract

Optimizing pavement maintenance and rehabilitation (M&R) strategies is essential, especially in developing countries with limited budgets. This study presents an integrated framework combining a deterioration prediction model and a genetic algorithm (GA)-based optimization model to plan cost-effective M&R strategies for flexible pavements, including [...] Read more.

Optimizing pavement maintenance and rehabilitation (M&R) strategies is essential, especially in developing countries with limited budgets. This study presents an integrated framework combining a deterioration prediction model and a genetic algorithm (GA)-based optimization model to plan cost-effective M&R strategies for flexible pavements, including asphalt concrete (AC) and double bituminous surface treatment (DBST). The GA schedules multi-year interventions by accounting for varied deterioration rates and budget constraints to maximize pavement performance. The optimization process involves generating a population of candidate solutions representing a set of selected road sections for maintenance, followed by fitness evaluation and solution evolution. A mixed Markov hazard (MMH) model is used to model uncertainty in pavement deterioration, simulating condition transitions influenced by pavement bearing capacity, traffic load, and environmental factors. The MMH model employs an exponential hazard function and Bayesian inference via Markov Chain Monte Carlo (MCMC) to estimate deterioration rates and life expectancies. A case study on Cambodia’s road network evaluates six budget scenarios (USD 12–27 million) over a 10-year period, identifying the USD 18 million budget as the most effective. The framework enables road agencies to access maintenance strategies under various financial and performance conditions, supporting data-driven, sustainable infrastructure management and optimal fund allocation. Full article

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23 pages, 5554 KB

Open AccessArticle

Innovative Forecasting: “A Transformer Architecture for Enhanced Bridge Condition Prediction”

by Manuel Fernando Flores Cuenca, Yavuz Yardim and Cengis Hasan

Infrastructures 2025, 10(10), 260; https://doi.org/10.3390/infrastructures10100260 - 29 Sep 2025

Abstract

The preservation of bridge infrastructure has become increasingly critical as aging assets face accelerated deterioration due to climate change, environmental loading, and operational stressors. This issue is particularly pronounced in regions with limited maintenance budgets, where delayed interventions compound structural vulnerabilities. Although traditional [...] Read more.

The preservation of bridge infrastructure has become increasingly critical as aging assets face accelerated deterioration due to climate change, environmental loading, and operational stressors. This issue is particularly pronounced in regions with limited maintenance budgets, where delayed interventions compound structural vulnerabilities. Although traditional bridge inspections generate detailed condition ratings, these are often viewed as isolated snapshots rather than part of a continuous structural health timeline, limiting their predictive value. To overcome this, recent studies have employed various Artificial Intelligence (AI) models. However, these models are often restricted by fixed input sizes and specific report formats, making them less adaptable to the variability of real-world data. Thus, this study introduces a Transformer architecture inspired by Natural Language Processing (NLP), treating condition ratings, and other features as tokens within temporally ordered inspection “sentences” spanning 1993–2024. Due to the self-attention mechanism, the model effectively captures long-range dependencies in patterns, enhancing forecasting accuracy. Empirical results demonstrate 96.88% accuracy for short-term prediction and 86.97% across seven years, surpassing the performance of comparable time-series models such as Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRUs). Ultimately, this approach enables a data-driven paradigm for structural health monitoring, enabling bridges to “speak” through inspection data and empowering engineers to “listen” with enhanced precision. Full article

(This article belongs to the Special Issue Advances in Structural Health Monitoring and Industry 5.0 Innovations for Bridge Management and Conservation)

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23 pages, 5055 KB

Open AccessArticle

Effect of Ground Motion Duration and Frequency Characteristics on the Probabilistic Risk Assessment of a Concrete Gravity Dam

by Tahmina Tasnim Nahar, Md Motiur Rahman and Dookie Kim

Infrastructures 2025, 10(10), 259; https://doi.org/10.3390/infrastructures10100259 - 27 Sep 2025

Abstract

Evaluation of seismic risk by capturing the influences of strong motion duration and frequency contents of ground motion through probabilistic approaches is the main element of this study. Unlike most existing studies that mainly focus on intensity measures such as peak ground acceleration [...] Read more.

Evaluation of seismic risk by capturing the influences of strong motion duration and frequency contents of ground motion through probabilistic approaches is the main element of this study. Unlike most existing studies that mainly focus on intensity measures such as peak ground acceleration or spectral acceleration, this work highlights how duration and frequency characteristics critically influence dam response. To achieve this, a total of 45 ground motion records, categorized by strong motion duration (long, medium, and short) and frequency content (low, medium, and high), were selected from the PEER database. Nonlinear numerical dynamic analysis was performed by scaling each ground motion from 0.05 g to 0.5 g, with the drift ratio at the dam crest used as the Engineering Demand Parameter. It is revealed that long-duration and low-frequency ground motions induced significantly higher drift demands. The fragility analysis was conducted using a lognormal distribution considering extensive damage threshold drift ratio. Finally, the probabilistic seismic risk was carried out by integrating the site-specific hazard curve and fragility curves which yield the height risk for long durations and low frequencies. The outcomes emphasize the importance of ground motion strong duration and frequency in seismic performance and these findings can be utilized in the dam safety evaluation. Full article

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

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17 pages, 2596 KB

Open AccessArticle

Comparative Assessment of Seismic Damping Scheme for Multi-Storey Frame Structures

by Shuming Jia and Pengfei Ma

Infrastructures 2025, 10(10), 258; https://doi.org/10.3390/infrastructures10100258 - 26 Sep 2025

Abstract

Traditional anti-seismic methods are constrained by high construction costs and the potential for severe structural damage under earthquakes. Energy dissipation technology provides an effective solution for structural earthquake resistance by incorporating energy-dissipating devices within structures to actively absorb seismic energy. However, existing research [...] Read more.

Traditional anti-seismic methods are constrained by high construction costs and the potential for severe structural damage under earthquakes. Energy dissipation technology provides an effective solution for structural earthquake resistance by incorporating energy-dissipating devices within structures to actively absorb seismic energy. However, existing research lacks in-depth analysis of the influence of energy dissipation devices’ placement on structural dynamic response. Therefore, this study investigates the seismic mitigation effectiveness of viscous dampers in multi-storey frame structures and their optimal placement strategies. A comprehensive parametric investigation was conducted using a representative three-storey steel-frame kindergarten facility in Shandong Province as the prototype structure. Advanced finite element modeling was implemented through ETABS software to establish a high-fidelity structural analysis framework. Based on the supplemental virtual damping ratio seismic design method, damping schemes were designed, and the influence patterns of different viscous damper arrangement schemes on the seismic mitigation effectiveness of multi-storey frame structures were systematically investigated. Through rigorous comparative assessment of dynamic response characteristics and energy dissipation mechanisms inherent to three distinct energy dissipation device deployment strategies (perimeter distribution, central concentration, and upper-storey localization), this investigation delineates the governing principles underlying spatial positioning effects on structural seismic mitigation performance. This comprehensive investigation elucidates several pivotal findings: damping schemes developed through the supplemental virtual damping ratio-based design methodology demonstrate excellent applicability and predictive accuracy. All three spatial configurations effectively attenuate structural seismic response, achieving storey shear reductions of 15–30% and inter-storey drift reductions of 19–28%. Damper spatial positioning critically influences mitigation performance, with perimeter distribution outperforming central concentration, while upper-storey localization exhibits optimal overall effectiveness. These findings validate the engineering viability and structural reliability of viscous dampers in multi-storey frame applications, establishing a robust scientific foundation for energy dissipation technology implementation in seismic design practice. Full article

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13 pages, 3922 KB

Open AccessArticle

Circular Slab Track—Structural Analysis of Adapting Composite Materials to Ballastless Track Systems

by Lasse Hansen, Lars Voll, Dragan Marinkovic and Birgit Milius

Infrastructures 2025, 10(10), 257; https://doi.org/10.3390/infrastructures10100257 - 24 Sep 2025

Abstract

Rail transport is widely regarded as an efficient and environmentally sustainable mode of mobility, although lifecycle emissions from infrastructure can diminish its ecological benefits. This study assesses a novel slab track system design that replaces conventional concrete components with recycled polymeric composite sleepers, [...] Read more.

Rail transport is widely regarded as an efficient and environmentally sustainable mode of mobility, although lifecycle emissions from infrastructure can diminish its ecological benefits. This study assesses a novel slab track system design that replaces conventional concrete components with recycled polymeric composite sleepers, supporting circular economy objectives. Analytical calculations (per EN 16432-2 and EN 13230-6) and finite element analysis (FEA) were conducted on a 2.6 m polymeric composite sleeper model under static vertical loading. The results demonstrate that bonded base layers comprising asphalt and hydraulically bound materials reduce bending stresses within the sleeper to 1.307 N/mm², substantially below the 5.50 N/mm² observed without bound layers and well below both characteristic fatigue limits. Laboratory validation via strain-gauge measurements corroborates the numerical model. Despite minor torsional effects from first-batch production, the polymeric composite sleeper design is structurally viable for slab track applications. The methodology is directly transferable to alternative composite designs, allowing material-based adaptation of mechanical performance. These findings support the use of recycled polymeric composite sleepers in slab track systems, combining structural adequacy with enhanced circularity. Further research can base itself on the findings and should incorporate long-term durability testing. Full article

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18 pages, 9067 KB

Open AccessArticle

Dynamic Response and Design Optimization of Box Girder Bridge with Corrugated Steel Webs Subjected to Blast Loads

by Changling Xie, Hexin Jin, Yunlong Xu, Xiaopei He and Junlong Zhou

Infrastructures 2025, 10(10), 256; https://doi.org/10.3390/infrastructures10100256 - 24 Sep 2025

Abstract

Throughout the service life, bridge structures may face blast hazards from military conflicts, terrorist attacks, and accidental explosions. Dynamic responses and damage modes of box girder bridges with corrugated steel webs under blast loading remain scarce. This study investigates the dynamic response and [...] Read more.

Throughout the service life, bridge structures may face blast hazards from military conflicts, terrorist attacks, and accidental explosions. Dynamic responses and damage modes of box girder bridges with corrugated steel webs under blast loading remain scarce. This study investigates the dynamic response and optimal design of box girder bridges with corrugated steel webs under blast loading. A box girder bridge model with corrugated steel webs is established through the software LS-DYNA, and the dynamic response of the bridge model subjected to blast loads is studied. Parametric studies are conducted to evaluate the effects of key geometric parameters, including the folding angle, height–span ratio, and dip angle of corrugated steel webs, on the blast-resistance performance of the bridge. The results indicate that a folding angle of 55° provides optimal blast resistance by balancing local stiffness and stress concentration. The 3.0 m height of corrugated steel webs maximizes the energy absorption capacity of corrugated steel webs while minimizing mid-span residual deflection. A dip angle of 85° ensures effective deformation constraint and load transfer, reducing damage in both the upper and bottom bridge decks. This study highlights the critical role of corrugated steel web geometry in enhancing blast resistance and provides practical guidelines for optimizing the design of box girder bridges with corrugated steel webs under extreme loading conditions. Full article

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23 pages, 3585 KB

Open AccessArticle

Deep Learning for Underwater Crack Detection: Integrating Physical Models and Uncertainty-Aware Semantic Segmentation

by Wenji Ai, Zongchao Liu, Shuai Teng, Shaodi Wang and Yinghou He

Infrastructures 2025, 10(10), 255; https://doi.org/10.3390/infrastructures10100255 - 23 Sep 2025

Abstract

Underwater crack detection is critical for ensuring the safety and longevity of submerged infrastructures, yet it remains challenging due to water-induced image degradation, limited labeled data, and the poor generalization of existing models. This paper proposes a novel deep learning framework that integrates [...] Read more.

Underwater crack detection is critical for ensuring the safety and longevity of submerged infrastructures, yet it remains challenging due to water-induced image degradation, limited labeled data, and the poor generalization of existing models. This paper proposes a novel deep learning framework that integrates physical priors and uncertainty modeling to address these challenges. Our approach introduces a physics-guided enhancement module that leverages underwater light propagation models, and a dual-branch segmentation network that combines semantic and geometry-aware curvature features to precisely delineate irregular crack boundaries. Additionally, an uncertainty-aware Transformer module quantifies prediction confidence, reducing the number of overconfident errors in ambiguous regions. Experiments on a self-collected dataset demonstrate State-of-the-Art performance, achieving 81.2% mIoU and 83.9% Dice scores, with superior robustness in turbid water and uneven lighting. The proposed method introduces a novel synergy of physical priors and uncertainty-aware learning, advancing underwater infrastructure inspection beyond the current data-driven approaches. Our framework offers significant improvements in accuracy, robustness, and interpretability, particularly in challenging conditions like turbid water and non-uniform lighting. Full article

(This article belongs to the Special Issue Advances in Damage Detection for Concrete Structures)

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25 pages, 3812 KB

Open AccessArticle

Seismic Vulnerability Assessment and Prioritization of Masonry Railway Tunnels: A Case Study

by Yaser Hosseini, Reza Karami Mohammadi and Tony Y. Yang

Infrastructures 2025, 10(10), 254; https://doi.org/10.3390/infrastructures10100254 - 23 Sep 2025

Abstract

Assessing seismic vulnerability and prioritizing railway tunnels for seismic rehabilitation are critical components of railway infrastructure management, especially in seismically active regions. This study focuses on a railway network in Northwest Iran, consisting of 103 old masonry rock tunnels. The vulnerability of these [...] Read more.

Assessing seismic vulnerability and prioritizing railway tunnels for seismic rehabilitation are critical components of railway infrastructure management, especially in seismically active regions. This study focuses on a railway network in Northwest Iran, consisting of 103 old masonry rock tunnels. The vulnerability of these tunnels is evaluated under 12 active faults as seismic sources. Fragility curves derived from the HAZUS methodology estimate the probability of various damage states under seismic intensities, including peak ground acceleration (PGA) and peak ground displacement (PGD). The expected values of the damage states are computed as the damage index (DI) to measure the severity of damage. A normalized prioritization index (NPI) is proposed, considering seismic vulnerability and life cycle damages in tunnel prioritizing. Finally, a detailed prioritization is provided in four classes. The results indicate that 10% of the tunnels are classified as priority, 33% as second priority, 40% as third priority, and 17% as fourth priority. This prioritization is necessary when there are budget limitations and it is not possible to retrofit all tunnels simultaneously. The main contribution of this study is the development of an integrated, data-driven framework for prioritizing the seismic rehabilitation of aging masonry railway tunnels, combining fragility-based vulnerability assessment with life-cycle damage considerations in a high-risk and data-limited region. The framework outlined in this study enables decision-making organizations to efficiently prioritize the tunnels based on vulnerability, which helps to increase seismic resilience. Full article

(This article belongs to the Special Issue Earthquake and Multi-Hazard Resilience: Community-Level Insights and AI/ML Applications)

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28 pages, 3682 KB

Open AccessArticle

Development of an Integrated 3D Simulation Model for Metro-Induced Ground Vibrations

by Omrane Abdallah, Mohammed Hussein and Jamil Renno

Infrastructures 2025, 10(9), 253; https://doi.org/10.3390/infrastructures10090253 - 21 Sep 2025

Abstract

This paper introduces a novel 3D simulation framework that integrates the Pipe-in-Pipe (PiP) model with Finite Element Analysis (FEA) using Ansys Parametric Design Language (APDL). This framework is designed to incorporate a 3D building model directly, assessing ground-borne vibrations from metro tunnels and [...] Read more.

This paper introduces a novel 3D simulation framework that integrates the Pipe-in-Pipe (PiP) model with Finite Element Analysis (FEA) using Ansys Parametric Design Language (APDL). This framework is designed to incorporate a 3D building model directly, assessing ground-borne vibrations from metro tunnels and their impact on surrounding structures. The PiP model efficiently calculates displacement fields around tunnels in full-space, applying the resulting fictitious forces to the FEA model, which includes a directly coupled 3D building model. This integration allows for precise simulation of vibration propagation through soil into buildings. A comprehensive verification test confirmed the model’s accuracy and reliability, demonstrating that the hybrid PiP-FEA model achieves significant computational savings-approximately 40% in time and 65% in memory usage-compared to the traditional full 3D FEA model. The results exhibit strong agreement between the PiP-FEA and full FEA models across a frequency range of 1–250 Hz, with less than 1% deviation, highlighting the effectiveness of the PiP-FEA approach in capturing the dynamic behavior of ground-borne vibrations. Additionally, the methodology developed in this paper extends beyond the specific case study presented and shows potential for application to various urban vibration scenarios. While the current validation is limited to numerical comparisons, future work will incorporate field data to further support the framework’s applicability under real metro-induced vibration conditions. Full article

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

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70 pages, 4598 KB

Open AccessReview

Maintenance Budget Allocation Models of Existing Bridge Structures: Systematic Literature and Scientometric Reviews of the Last Three Decades

by Eslam Mohammed Abdelkader, Abobakr Al-Sakkaf, Kyrillos Ebrahim and Moaaz Elkabalawy

Infrastructures 2025, 10(9), 252; https://doi.org/10.3390/infrastructures10090252 - 20 Sep 2025

Abstract

Bridges play an increasingly indispensable role in endorsing the economic and social development of societies by linking highways and facilitating the mobility of people and goods. Concurrently, they are susceptible to high traffic volumes and an intricate service environment over their lifespans, resulting [...] Read more.

Bridges play an increasingly indispensable role in endorsing the economic and social development of societies by linking highways and facilitating the mobility of people and goods. Concurrently, they are susceptible to high traffic volumes and an intricate service environment over their lifespans, resulting in undergoing a progressive deterioration process. Hence, efficient measures of maintenance, repair, and rehabilitation planning are critical to boost the performance condition, safety, and structural integrity of bridges while evading less costly interventions. To this end, this research paper furnishes a mixed review method, comprising systematic literature and scientometric reviews, for the meticulous examination and analysis of the existing research work in relation with maintenance fund allocation models of bridges (BriMai_all). With that in mind, Scopus and Web of Science databases are harnessed collectively to retrieve peer-reviewed journal articles on the subject, culminating in 380 indexed journal articles over the study period (1990–2025). In this respect, VOSviewer and Bibliometrix R package are utilized to create a visualization network of the literature database, covering keyword co-occurrence analysis, country co-authorship analysis, institution co-authorship analysis, journal co-citation analysis, journal co-citation, core journal analysis, and temporal trends. Subsequently, a rigorous systematic literature review is rendered to synthesize the adopted tools and prominent trends of the relevant state of the art. Particularly, the conducted multi-dimensional review examines the six dominant methodical paradigms of bridge maintenance management: (1) multi-criteria decision making, (2) life cycle assessment, (3) digital twins, (4) inspection planning, (5) artificial intelligence, and (6) optimization. It can be argued that this research paper could assist asset managers with a practical guide and a protocol to plan maintenance expenditures and implement sustainable practices for bridges under deterioration. Full article

(This article belongs to the Special Issue Advances in Structural Health Monitoring and Industry 5.0 Innovations for Bridge Management and Conservation)

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18 pages, 6298 KB

Open AccessArticle

Structural Characteristics and Damage Analysis of Beijing Wanning Bridge Under the Coupling Effect of Dynamic Traffic and Subway Vibrations

by Yuhua Zhu and Yingmei Guo

Infrastructures 2025, 10(9), 251; https://doi.org/10.3390/infrastructures10090251 - 19 Sep 2025

Abstract

The Wanning Bridge is a critical component of Beijing’s Central Axis World Heritage site and the only Yuan Dynasty heritage bridge in Beijing still in service. Investigating its structural response under complex traffic conditions is therefore essential for ensuring the longevity of this [...] Read more.

The Wanning Bridge is a critical component of Beijing’s Central Axis World Heritage site and the only Yuan Dynasty heritage bridge in Beijing still in service. Investigating its structural response under complex traffic conditions is therefore essential for ensuring the longevity of this ancient structure and the safety of the urban transport system. However, the application of traditional research methods, such as direct sampling, is often constrained by the cultural relic characteristics of heritage bridges. This study first conducted a macroscopic on-site survey to document its current appearance and global geometry. Subsequently, more accurate geometric and material parameters of the bridge were acquired through non-destructive testing techniques including 3D laser scanning, ground-penetrating radar, and ultrasonic testing. Subsequently, using a combined approach of experimental and numerical simulation, this study reveals key structural responses and damage conditions of the bridge through static, dynamic, and metro-induced vibration tests. Dynamic tests show a maximum deformation of 0.26 mm and a natural frequency of 10.547 Hz, indicating shear strain accumulation as the primary damage driver. Subway-induced vibrations are well within the safety limits for stone relics, and the structure’s current load-bearing capacity complies with Class-II highway standards. Full article

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

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17 pages, 8823 KB

Open AccessArticle

Static Loading Tests and Finite Element Analysis of Phosphogypsum Steel Truss Concrete Slabs

by Ao Zhang, Lirong Sha and Juan Fang

Infrastructures 2025, 10(9), 250; https://doi.org/10.3390/infrastructures10090250 - 19 Sep 2025

Abstract

This study investigates the utilization of phosphogypsum (PG), an industrial byproduct, as a sustainable additive in reinforced truss concrete slabs to promote eco-friendly construction practices. Through static loading tests (monotonic/cyclic) under mixed boundary conditions (simply supported fixed), four slabs—including 2% PG-modified and ordinary [...] Read more.

This study investigates the utilization of phosphogypsum (PG), an industrial byproduct, as a sustainable additive in reinforced truss concrete slabs to promote eco-friendly construction practices. Through static loading tests (monotonic/cyclic) under mixed boundary conditions (simply supported fixed), four slabs—including 2% PG-modified and ordinary concrete—were evaluated for mechanical performance, stress strain response, deflection, and crack propagation. The results demonstrated that PG enhanced slabs achieved comparable strength to conventional counterparts while exhibiting superior structural integrity at failure, highlighting PG’s potential to reduce environmental waste without compromising performance. Finite element analysis (ABAQUS2023) closely aligned with experimental data (<5% error), validating the model’s reliability in predicting failure modes. The study underscores PG’s viability as a circular economy solution for green building materials, offering dual benefits of waste valorization and resource efficiency. These findings advance sustainable construction by providing actionable insights for integrating industrial byproducts into high-performance structural systems, aligning with global decarbonization goals. Full article

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23 pages, 56189 KB

Open AccessArticle

Connecting Cities: Solving Optimal-Resource-Distribution Problem Using Critical Range Radius

by Jorge L. Perez-Ramos, Ana M. Herrera-Navarro and Hugo Jimenez-Hernandez

Infrastructures 2025, 10(9), 249; https://doi.org/10.3390/infrastructures10090249 - 18 Sep 2025

Abstract

Navigating and planning optimal paths for resource delivery algorithms poses significant physical and technical challenges in urban areas, primarily due to the limitations of existing infrastructure. As smart cities continue to develop, the importance of these algorithms becomes increasingly evident. The saturation of [...] Read more.

Navigating and planning optimal paths for resource delivery algorithms poses significant physical and technical challenges in urban areas, primarily due to the limitations of existing infrastructure. As smart cities continue to develop, the importance of these algorithms becomes increasingly evident. The saturation of current urban landscapes exacerbates the complexity of navigating essential resources. Navigating densely connected networks can be intricate and often requires substantial computational resources or additional algorithms, as it can easily transform into an NP problem. Unfortunately, there is a lack of explicit algorithms designed for navigating these networks, resulting in a dependence on heuristic approaches and previous network systems. This reliance can create computational challenges, as navigation in this context typically involves a combinatorial search space. Current advances in Morphological Mathematics (MM) help to model everyday tasks as processes in discrete spaces, which take advantage of the properties offered by the morphological operators. Morphological Shortest-Path-Planning (MSPP) is a recent solution that effectively calculates the optimal trajectory within complex graphs. By utilizing morphological operators, this approach takes into account discrete properties and maps the process as a complete implementation algorithm using integer logic. In larger cities, determining the optimal delivery route and time from a resource center is a common task. This process is influenced by factors such as average speed, travel time, and distance, which generate a complex graph representation of the town, complicating its analysis. This paper presents a strategy for computing and analyzing delivery times by determining the accessibility of reliable paths from a delivery center to potential destinations in dense urban areas. The strategy presented and the use of the MSPP approach are suitable for calculating the time spent delivering and the distance traveled in working journeys. The MSPP approach is found to be nearly

60 %

more efficient than the reference approach for computing the optimal path in the case study presented. Full article

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18 pages, 8827 KB

Open AccessArticle

Evaluation of Connected Vehicle Pavement Roughness Data for Statewide Needs Assessment

by Andrew Thompson, Jairaj Desai and Darcy M. Bullock

Infrastructures 2025, 10(9), 248; https://doi.org/10.3390/infrastructures10090248 - 18 Sep 2025

Abstract

Many agencies use pavement condition assessments such as the Pavement Surface Evaluation and Rating (PASER) and Pavement Condition Index (PCI) to develop localized pavement management programs. However, both techniques involve some subjectivity and inconsistent measurement practices, making it difficult to scale uniformly across [...] Read more.

Many agencies use pavement condition assessments such as the Pavement Surface Evaluation and Rating (PASER) and Pavement Condition Index (PCI) to develop localized pavement management programs. However, both techniques involve some subjectivity and inconsistent measurement practices, making it difficult to scale uniformly across all 86 thousand miles of local agency roadway in Indiana’s 92 counties. International Roughness Index (IRI) data is one emerging data source that could address this need. This paper evaluates the feasibility of using Connected Vehicle-estimated IRI (IRI_CVe) data for long-term statewide pavement monitoring on local roads. The analysis is based on approximately 4.1 billion daily IRI_CVe records collected over a multi-year study period from connected vehicles operating throughout the state. A modular data processing workflow was developed to clean and process these records and is presented in detail in the paper. The study includes network-level condition comparisons, insights on spatiotemporal trends, and localized segment-level condition monitoring. In 2024, approximately 53% of paved local roads in Indiana had at least one IRI_CVe observation per year. Coverage varied widely by county: for example, 79% of roads in urban Hamilton County had coverage, but only 14% had coverage in rural Martin County. The findings in this study demonstrate the potential of IRI_CVe to support local agency pavement asset management by providing cost-effective data-driven insights in near real-time. Full article

(This article belongs to the Section Smart Infrastructures)

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22 pages, 5930 KB

Open AccessArticle

A Computer Vision-Based Pedestrian Flow Management System for Footbridges and Its Applications

by Can Zhao, Yiyang Jiang and Jinfeng Wang

Infrastructures 2025, 10(9), 247; https://doi.org/10.3390/infrastructures10090247 - 17 Sep 2025

Abstract

Urban footbridges are critical infrastructure increasingly challenged by vibration issues induced by crowd activity. Real-time monitoring of pedestrian dynamics is essential for evaluating structural safety, ensuring pedestrian comfort, and enabling proactive management. This paper proposes a lightweight, fully automated computer vision system for [...] Read more.

Urban footbridges are critical infrastructure increasingly challenged by vibration issues induced by crowd activity. Real-time monitoring of pedestrian dynamics is essential for evaluating structural safety, ensuring pedestrian comfort, and enabling proactive management. This paper proposes a lightweight, fully automated computer vision system for real-time monitoring of crowd dynamics on footbridges. The system integrates object detection, multi-target tracking, and monocular depth estimation to precisely quantify key crowd metrics: pedestrian flow rate, density, and velocity. Experimental validation demonstrated high performance: Flow rate estimation achieved 92.7% accuracy; density estimation yielded a 2.05% average relative error; and velocity estimation showed an 8.7% average relative error. Furthermore, the system demonstrates practical utility by successfully categorizing pedestrian behaviors using velocity data and triggering timely warnings. Crucially, field tests confirmed a minimum error of 5.56% between bridge vibration simulations driven by the system’s captured crowd data and physically measured acceleration data. This high agreement validates the system’s capability to provide reliable inputs for structural assessment. The proposed system establishes a practical technological foundation for intelligent footbridge management, focusing on safety, comfort, and operational efficiency through real-time crowd insights and automated alerts. Full article

(This article belongs to the Topic Advances in Intelligent Construction, Operation and Maintenance, 2nd Edition)

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44 pages, 7055 KB

Open AccessReview

Towards Resilient Critical Infrastructure in the Face of Extreme Wildfire Events: Lessons and Policy Pathways from the US and EU

by Nikolaos Kalapodis, Georgios Sakkas, Danai Kazantzidou-Firtinidou, Fermín Alcasena, Monica Cardarilli, George Eftychidis, Cassie Koerner, Lori Moore-Merrell, Emilia Gugliandolo, Konstantinos Demestichas, Dionysios Kolaitis, Mohamed Eid, Vasiliki Varela, Claudia Berchtold, Kostas Kalabokidis, Olga Roussou, Krishna Chandramouli, Maria Pantazidou, Mike Cox and Anthony Schultz

Infrastructures 2025, 10(9), 246; https://doi.org/10.3390/infrastructures10090246 - 17 Sep 2025

Abstract

Escalating extreme wildfires, fueled by the confluence of climate change, land use patterns alterations, ignitions by humans, and flammable fuels accumulation, pose significant and increasingly destructive risks to critical infrastructure (CI). This study presents a comprehensive comparative analysis of wildfire impacts and the [...] Read more.

Escalating extreme wildfires, fueled by the confluence of climate change, land use patterns alterations, ignitions by humans, and flammable fuels accumulation, pose significant and increasingly destructive risks to critical infrastructure (CI). This study presents a comprehensive comparative analysis of wildfire impacts and the corresponding CI resilience strategies employed across the EU and the US. It examines the vulnerability of CIs to the devastating effects of wildfires and their inadvertent contribution to wildfire ignition and spread. The study evaluates the EU’s CER Directive and the US National Infrastructure Protection Plan and assesses European Commission wildfire resilience-related initiatives, including FIRELOGUE, FIRE-RES, SILVANUS, and TREEADS flagship projects. It synthesizes empirical evidence and extracts key lessons learned from major wildfire events in the EU (2017 Portuguese fires; 2018 Mati wildfire) and the US (2023 Lahaina disaster; 2025 Los Angeles fires), drawing insights regarding the effectiveness of various resilience measures and identifying areas for improvement. Persistent challenges impeding effective wildfire resilience are identified, including governance fragmentation, lack of standardization in risk assessment and mitigation protocols, and insufficient integration of scientific knowledge and data into policy formulation and implementation. It concludes with actionable recommendations aimed at fostering science-based, multi-stakeholder approaches to strengthen wildfire resilience at both policy and operational levels. Full article

(This article belongs to the Topic Disaster Risk Management and Resilience)

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30 pages, 1627 KB

Open AccessArticle

Comparative Sustainability Assessment of Proprietary and Non-Proprietary Ultra-High Performance Concrete Mixtures

by Ali Alsalman, Lateef Assi, Kealy Carter, Mohammed A. Mousa, Canh N. Dang, W. Micah Hale and Ayad Al-Yousuf

Infrastructures 2025, 10(9), 245; https://doi.org/10.3390/infrastructures10090245 - 16 Sep 2025

Abstract

Ultra-high-performance concrete (UHPC) has greater strength and durability compared to traditional concrete. While these benefits are well established, there are differences in UHPC based on the constituent materials in the mixture. These variations impact the mixtures’ CO₂ emissions, efficiency, and cost. Given [...] Read more.

Ultra-high-performance concrete (UHPC) has greater strength and durability compared to traditional concrete. While these benefits are well established, there are differences in UHPC based on the constituent materials in the mixture. These variations impact the mixtures’ CO₂ emissions, efficiency, and cost. Given the contribution of concrete to overall greenhouse gas emissions, it is important to understand the potential impact of UHPC from an environmental standpoint. This study addresses the environmental and economic impact of UHPC by examining five proprietary and five non-proprietary mixtures. The investigation is guided by three research questions, as follows: (1) How do energy consumption, CO₂ emissions, and cost compare between proprietary and non-proprietary UHPC mixtures? (2) Which materials are the most influential drivers of these sustainability metrics? (3) Can non-proprietary mixtures provide comparable or better performance in terms of sustainability? Using secondary data from the literature, we calculate and analyze the energy, emissions, and cost of each UHPC constituent. The results indicate that steel fibers account for 53% of the total energy of UHPC. Ordinary Portland cement (OPC) is responsible for 73% of total CO₂ emissions. Aggregates, admixtures, and SCMs have a minimal impact on the energy and emissions of the selected mixtures. However, they can affect the cost significantly. To highlight the key findings, non-proprietary mixtures showed substantial sustainability advantages. For example, UHPC-1 achieved up to 65% lower energy consumption, 49% lower CO₂ emissions, and 80% lower cost compared to proprietary mixtures. These results highlight the potential of non-proprietary UHPC to serve as an ecologically friendly and cost-effective substitute for infrastructure applications. Full article

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

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