Infrastructures

19 pages, 3205 KB

Open AccessArticle

Physics-Aware Informer: A Hybrid Framework for Accurate Pavement IRI Prediction in Diverse Climates

by Xintao Cao, Zhiping Zeng and Fan Yi

Infrastructures 2025, 10(10), 278; https://doi.org/10.3390/infrastructures10100278 - 18 Oct 2025

Viewed by 363

Accurate prediction of the International Roughness Index (IRI) is critical for road safety and maintenance decisions. In this study, we propose a novel Physics-Aware Informer (PA-Informer) model that integrates the efficiency of the Informer structure with physics constraints derived from partial differential equations [...] Read more.

Accurate prediction of the International Roughness Index (IRI) is critical for road safety and maintenance decisions. In this study, we propose a novel Physics-Aware Informer (PA-Informer) model that integrates the efficiency of the Informer structure with physics constraints derived from partial differential equations (PDEs). The model addresses two key challenges: (1) performance degradation in short-sequence scenarios, and (2) the lack of physics constraints in conventional data-driven models. By embedding residual PDEs to link IRI with influencing factors such as temperature, precipitation, and joint displacement, and introducing a dynamic weighting strategy for balancing data-driven and physics-informed losses, the PA-Informer achieves robust and accurate predictions. Experimental results, based on data from four climatic regions in China, demonstrate its superior performance. The model achieves a Mean Squared Error (MSE) of 0.0165 and R² of 0.962 with an input window length of 30 weeks, and an MSE of 0.0152 and R² with an input window length of 120 weeks. Its accuracy is superior to that of other models, and the stability of the model when the input window length changes is far better than that of other models. Sensitivity analysis highlights joint displacement and internal stress as the most influential features, with stable sensitivity coefficients (S_p ≈ 0.89 and S_p ≈ 0.81). These findings validate the PA-Informer as a reliable and scalable tool for predicting pavement performance under diverse conditions, offering significant improvements over other IRI prediction models. Full article

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17 pages, 3043 KB

Open AccessArticle

3D Effects on the Stability of Upstream-Raised Tailings Dams in Narrow Valleys

by Raul Conceição, Gonçalo Ferreira, Henrique Lopes and João Camões Lourenço

Infrastructures 2025, 10(10), 277; https://doi.org/10.3390/infrastructures10100277 - 15 Oct 2025

Viewed by 340

Abstract

Tailings dams are unique structures due to the materials they store and the methods applied in their construction, often resulting in complex three-dimensional (3D) problems. Most current slope-stability analyses neglect the 3D effects without significant consequences. However, certain conditions, such as the valley [...] Read more.

Tailings dams are unique structures due to the materials they store and the methods applied in their construction, often resulting in complex three-dimensional (3D) problems. Most current slope-stability analyses neglect the 3D effects without significant consequences. However, certain conditions, such as the valley shape, the spatial variability of the tailings’ resistance, and the presence of internal dikes, may render the 2D simplification inadequate. For translational slides, the sliding-mass width-to-height ratio (W/H) is a reliable estimator of the 3D effects. However, it is unclear whether this geometric ratio is the most suitable for rotational slides, where the width of the sliding mass varies along its height. This paper presents a parametric study of the 3D effects of the dam’s height (H_M) and the valley shape, namely the abutments’ slope angle with the horizontal (β) and the thalweg width (L_M), on the overall stability of a tailings dam raised by the upstream method, by means of 2D and 3D Limit Equilibrium (LE) analyses. The study evaluates the dam stability using a straightforward and practical methodology, specifically the FS_3D to FS_2D ratio (R_3D/2D), to compare the results of the 3D and 2D analyses, adapting current state-of-the-art techniques originally for translational slides, focused on pre-defined, closed-form slip-surface geometry, to rotational ones where the main focus is the geometry of the whole structure as a physical constraint for the sliding mass. The results show that the model average width-to-height ratio (W_M,avr/H_M), developed in this study, may be a better estimator of the 3D effects for rotational slides than the W/H ratio. Full article

(This article belongs to the Special Issue Preserving Life Through Dams)

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16 pages, 4467 KB

Open AccessArticle

Study on the Ablation of Slide Plate by Pantograph–Catenary Arc Based on Pantograph Slide Material

by Rui Tian, Shao-Jie Wang, Mai Lu and Jie Li

Infrastructures 2025, 10(10), 276; https://doi.org/10.3390/infrastructures10100276 - 15 Oct 2025

Viewed by 311

Abstract

The ablation of pantograph sliders caused by pantograph–catenary arcing is a critical issue in the operation of pantograph–catenary systems. The arc discharge induces localized high temperatures that lead to the melting and even evaporation of the slider material, resulting in material loss. This [...] Read more.

The ablation of pantograph sliders caused by pantograph–catenary arcing is a critical issue in the operation of pantograph–catenary systems. The arc discharge induces localized high temperatures that lead to the melting and even evaporation of the slider material, resulting in material loss. This phenomenon directly impacts the power supply safety and economic efficiency of trains. This study establishes a mathematical model of pantograph–catenary arcing based on Magneto Hydro Dynamics (MHD) theory, incorporating the physical parameters of the arc as well as electromagnetic, thermal, and radiative phenomena. Through secondary development using COMSOL 6.2 finite element software, the temperature distribution within the arc column region and on the surfaces of the electrode plates in pantograph–catenary arcing was simulated. The effects of the pantograph–catenary gap and slider material on arc ablation were investigated. The results show that with the increase in the distance between the pantograph and catenary, the arc shape lengthens gradually, and the high-temperature area inside the slider material shrinks gradually. When the arc duration is constant, the copper-impregnated carbon slider exhibits the best ablation resistance. Increasing the sublimation latent heat of the slider material enhances its anti-ablation performance. The findings of this study provide a valuable reference for understanding and mitigating surface arc erosion in pantograph–catenary systems. Full article

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42 pages, 6873 KB

Open AccessArticle

Sustainable Water and Energy Management Through a Solar-Hydrodynamic System in a Lake Velence Settlement, Hungary

by Attila Kálmán, Antal Bakonyi, Katalin Bene and Richard Ray

Infrastructures 2025, 10(10), 275; https://doi.org/10.3390/infrastructures10100275 - 13 Oct 2025

Viewed by 577

Abstract

The Lake Velence watershed faces increasing challenges driven by local and global factors, including the impacts of climate change, energy resource limitations, and greenhouse gas emissions. These issues, particularly acute in water management, are exacerbated by prolonged droughts, growing population pressures, and shifting [...] Read more.

The Lake Velence watershed faces increasing challenges driven by local and global factors, including the impacts of climate change, energy resource limitations, and greenhouse gas emissions. These issues, particularly acute in water management, are exacerbated by prolonged droughts, growing population pressures, and shifting land use patterns. Such dynamics strain the region’s scarce water resources, negatively affecting the environment, tourism, recreation, agriculture, and economic prospects. Nadap, a hilly settlement within the watershed, experiences frequent flooding and poor water retention, yet it also boasts the highest solar panel capacity per property in Hungary. This research addresses these interconnected challenges by designing a solar-hydrodynamic network comprising four multi-purpose water reservoirs. By leveraging the settlement’s solar capacity and geographical features, the reservoirs provide numerous benefits to local stakeholders and extend their impact far beyond their borders. These include stormwater management with flash flood mitigation, seasonal green energy storage, water security for agriculture and irrigation, wildlife conservation, recreational opportunities, carbon-smart winery developments, and the creation of sustainable blue-green settlements. Reservoir locations and dimensions were determined by analyzing geographical characteristics, stormwater volume, energy demand, solar panel performance, and rainfall data. The hydrodynamic system, modeled in Matlab, was optimized to ensure efficient water usage for irrigation, animal hydration, and other needs while minimizing evaporation losses and carbon emissions. This research presents a design framework for low-carbon and cost-effective solutions that address water management and energy storage, promoting environmental, social, and economic sustainability. The multi-purpose use of retained rainwater solves various existing problems/challenges, strengthens a community’s self-sustainability, and fosters regional growth. This integrated approach can serve as a model for other municipalities and for developing cost-effective inter-settlement and cross-catchment solutions, with a short payback period, facing similar challenges. Full article

(This article belongs to the Section Sustainable Infrastructures)

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18 pages, 1145 KB

Open AccessArticle

A Systematic Approach for Selection of Fit-for-Purpose Low-Carbon Concrete for Various Bridge Elements to Reduce the Net Embodied Carbon of a Bridge Project

by Harish Kumar Srivastava, Vanissorn Vimonsatit and Simon Martin Clark

Infrastructures 2025, 10(10), 274; https://doi.org/10.3390/infrastructures10100274 - 13 Oct 2025

Viewed by 626

Abstract

Australia consumes approximately 29 million m³ of concrete each year with an estimated embodied carbon (EC) of 12 Mt CO_2e. High consumption of concrete makes it critical for successful decarbonization to support the achievement of ‘Net Zero 2050’ objectives of [...] Read more.

Australia consumes approximately 29 million m³ of concrete each year with an estimated embodied carbon (EC) of 12 Mt CO_2e. High consumption of concrete makes it critical for successful decarbonization to support the achievement of ‘Net Zero 2050’ objectives of the Australian construction industry. Portland cement (PC) constitutes only 12–15% of the concrete mix but is responsible for approximately 90% of concrete’s EC. This necessitates reducing the PC in concrete with supplementary cementitious materials (SCMs) or using alternative binders such as geopolymer concrete. Concrete mixes including a combination of PC and SCMs as a binder have lower embodied carbon (EC) than those with only PC and are termed as low-carbon concrete (LCC). SCM addition to a concrete mix not only reduces EC but also enhances its mechanical and durability properties. Fly ash (FA) and granulated ground blast furnace slag (GGBFS) are the most used SCMs in Australia. It is noted that other SCMs such as limestone, metakaolin or calcinated clay, Delithiated Beta Spodumene (DBS) or lithium slag, etc., are being trialed. This technical paper presents a methodology that enables selecting LCCs with various degrees of SCMs for various elements of bridge structure without compromising their functional performance. The proposed methodology includes controls that need to be applied during the design/selection process of LCC, from material quality control to concrete mix design to EC evaluation for every element of a bridge, to minimize the overall carbon footprint of a bridge. Typical properties of LCC with FA and GGBFS as binary and ternary blends are also included for preliminary design of a fit-for-purpose LCC. An example for a bridge located in the B2 exposure classification zone (exposed to both carbonation on chloride ingress deterioration mechanisms) has also been included to test the methodology, which demonstrates that EC of the bridge may be reduced by up to 53% by use of the proposed methodology. Full article

(This article belongs to the Special Issue Sustainable Bridge Engineering)

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32 pages, 5437 KB

Open AccessArticle

Optimizing Mortar Strength for Infrastructure Applications Using Rice Husk Ash and Municipal Solid Waste Incineration Ash

by Sura Shamkhi Altaher, Nor Hasanah Abdul Shukor Lim, Nor Fazlin Zamri, Iman Faridmehr and Ghasan Fahim Huseien

Infrastructures 2025, 10(10), 273; https://doi.org/10.3390/infrastructures10100273 - 13 Oct 2025

Viewed by 495

Abstract

Infrastructure development increasingly requires sustainable construction materials, with waste utilization serving as a key strategy to address this need. Employing eco-friendly materials with enhanced engineering properties not only mitigates the environmental impact of waste but also lowers the carbon footprint associated with cement [...] Read more.

Infrastructure development increasingly requires sustainable construction materials, with waste utilization serving as a key strategy to address this need. Employing eco-friendly materials with enhanced engineering properties not only mitigates the environmental impact of waste but also lowers the carbon footprint associated with cement production. Accordingly, this research aims to investigate the potential of enhancing the performance of municipal solid waste incineration ash (MSWIA) mortar through the incorporation of rice husk ash (RHA) as a supplementary cementitious material (SCM), thereby supporting the principles of a circular economy. The MSWIA mortar comprised 25% bottom ash (BA) and 5% fly ash (FA) as substitutes for fine aggregate and cement, respectively. Cement was then replaced with RHA at 5–30% to assess the influence of RHA on the properties of MSWIA mortars such as workability, strength development, and water absorption. Adding RHA led to a lower flow rate and setting time than mortar content-only MSWIA. Nonetheless, the various mechanical properties of MSWIA mortar, such as compressive strength, split tensile strength, and flexure strength, were found to be increased when the RHA quantity was used at 10% as a cement replacement. The water absorption of the mortar mixes was reduced by increasing RHA up to 15%. The test results revealed that the mortar’s microstructural properties were notably enhanced, and the UPV measurements confirmed the overall good quality of the mortar specimens. Therefore, incorporating RHA and MSWIA in construction not only enhances performance but also contributes to environmental sustainability by reducing the carbon dioxide emission and landfill waste. Full article

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

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28 pages, 45631 KB

Open AccessArticle

Field Vibration Monitoring for Detecting Stiffness Variations in RC, PSC, Steel, and UHPC Bridge Girders

by Osazee Oravbiere, Mi G. Chorzepa and S. Sonny Kim

Infrastructures 2025, 10(10), 272; https://doi.org/10.3390/infrastructures10100272 - 11 Oct 2025

Viewed by 398

Abstract

This study quantifies shear and flexural stiffnesses and their changes over time to support structural health monitoring of in-service bridge superstructures across four girder types: reinforced concrete (RC) beams, prestressed concrete (PSC) girders, steel girders, and ultra-high-performance concrete (UHPC) sections, using field ambient [...] Read more.

This study quantifies shear and flexural stiffnesses and their changes over time to support structural health monitoring of in-service bridge superstructures across four girder types: reinforced concrete (RC) beams, prestressed concrete (PSC) girders, steel girders, and ultra-high-performance concrete (UHPC) sections, using field ambient vibration testing. A total of 20 bridges across Georgia and Iowa are assessed, involving over 100 hours of on-site data collection and traffic control strategies. Results show that field-measured natural frequencies differ from theoretical predictions by average of 30–35% for RC, and 20–25% for PSC, 15–25% for steel and 2% for UHPC, reflecting the complexity of in situ structural dynamics and challenges in estimating material properties. Site-placed RC beams showed stiffness reduction due to deterioration, whereas prefabricated PSC girders maintained consistent stiffness with predictable variations. UHPC sections exhibited the highest stiffness, reflecting superior performance. Steel girders matched theoretical values, but a span-level test revealed that deck damage can reduce frequencies undetected by localized measurements. Importantly, vibration-based measurements revealed reductions in structural stiffness that were not apparent through conventional visual inspection, particularly in RC beams. The research significance of this work lies in establishing a portfolio-based framework that enables cross-comparison of stiffness behavior across multiple girder types, providing a scalable and field-validated approach for system-level bridge health monitoring and serving as a quantitative metric to support bridge inspections and decision-making. Full article

(This article belongs to the Section Infrastructures Inspection and Maintenance)

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18 pages, 3503 KB

Open AccessArticle

Effects of Granular Material Deposition on the Road’s Stormwater Drainage System

by Francesco Abbondati, Carlo Gualtieri, Salvatore Antonio Biancardo and Gianluca Dell’Acqua

Infrastructures 2025, 10(10), 271; https://doi.org/10.3390/infrastructures10100271 - 10 Oct 2025

Viewed by 390

Abstract

Travel safety and comfort depend on the design and maintenance of road and stormwater drainage systems. In low-lying areas, poor drainage systems can—especially near underpasses—lead to flooding and serious risks, such as reduced load-bearing capacity hydroplaning, where tires lose grip. This study focuses [...] Read more.

Travel safety and comfort depend on the design and maintenance of road and stormwater drainage systems. In low-lying areas, poor drainage systems can—especially near underpasses—lead to flooding and serious risks, such as reduced load-bearing capacity hydroplaning, where tires lose grip. This study focuses on the effect of granular material deposits on the surface roughness of roadside gutters, as expressed through the Gauckler–Strickler coefficient. The literature equations have pointed out that this coefficient is largely affected by the grain size distribution of granular material. To this end, a field study was carried out in six urban roads in San Nicola la Strada, Italy, with the objectives of the following: (1) identifying the grain size distribution of the material deposited in roadside gutters; (2) estimating how such material decreased in the cross-sectional area of the gutters, as well as increasing their flow resistance, ultimately resulting in decreased water conveyance. Considering gutters with deposited material rather than clean ones results in the failure of three out of six gutters to effectively drain stormwater. Full article

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19 pages, 2217 KB

Open AccessArticle

Assessing Infrastructure Readiness of Controlled-Access Roads in West Bangkok for Autonomous Vehicle Deployment

by Vasin Kiattikomol, Laphisa Nuangrod, Arissara Rung-in and Vanchanok Chuathong

Infrastructures 2025, 10(10), 270; https://doi.org/10.3390/infrastructures10100270 - 10 Oct 2025

Viewed by 407

Abstract

The deployment of autonomous vehicles (AVs) depends on the readiness of both physical and digital infrastructure. However, existing national and city-level indices often overlook deficiencies along specific routes, particularly in developing contexts such as Thailand, where infrastructure conditions vary widely. This study develops [...] Read more.

The deployment of autonomous vehicles (AVs) depends on the readiness of both physical and digital infrastructure. However, existing national and city-level indices often overlook deficiencies along specific routes, particularly in developing contexts such as Thailand, where infrastructure conditions vary widely. This study develops and applies a corridor-level framework to assess AV readiness on five controlled-access roads in western Bangkok. The framework evaluates key infrastructure dimensions beyond conventional vehicle requirements. In this study, infrastructure readiness means the extent to which essential physical (EV charging capacity, traffic sign visibility, and lane marking retroreflectivity) and digital (5G speed and coverage) subsystems meet minimum operational thresholds required for AV deployment. Data were collected through field measurements and secondary sources, utilizing tools such as a retroreflectometer, a handheld spectrum analyzer, and the Ookla Speedtest application. The results reveal significant contrasts for physical infrastructure, showing that traffic signage is generally satisfactory, but EV charging capacity and road marking retroreflectivity are insufficient on most routes. On the digital side, 5G coverage was generally adequate, but network speeds remained less than half of the global benchmark. Kanchanaphisek Road demonstrated comparatively higher digital readiness, whereas Ratchaphruek Road exhibited the weakest road marking conditions. These findings point out the need for stepwise enhancements to EV charging infrastructure, lane marking maintenance, and digital connectivity to support safe and reliable AV operations. The proposed framework not only provides policymakers in Thailand with a practical tool for prioritizing corridor-level investments but also offers transferability to other rapidly developing urban regions experiencing similar infrastructure challenges for AV deployment. Full article

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18 pages, 2584 KB

Open AccessArticle

Evaluating Factors Influencing Dynamic Modulus Prediction: GRA-MLR Compared with Sigmoidal Modelling for Asphalt Mixtures with Reclaimed Asphalt

by Majda Belhaj, Jan Valentin, Nicola Baldo and Jan B. Król

Infrastructures 2025, 10(10), 269; https://doi.org/10.3390/infrastructures10100269 - 9 Oct 2025

Viewed by 283

Abstract

The dynamic modulus of asphalt mixtures (|E*|) is a key mechanical parameter in the design of road pavements, yet direct laboratory testing is time- and resource-intensive. This study evaluates two predictive models for estimating |E*| using data from 62 asphalt mixtures containing reclaimed [...] Read more.

The dynamic modulus of asphalt mixtures (|E*|) is a key mechanical parameter in the design of road pavements, yet direct laboratory testing is time- and resource-intensive. This study evaluates two predictive models for estimating |E*| using data from 62 asphalt mixtures containing reclaimed asphalt: a grey relational analysis–multiple linear regression (GRA-MLR) hybrid model and a mechanistic sigmoidal model. The results showed that the GRA-MLR model effectively identifies influential variables but achieved moderate predictive accuracy (R² values varying from 0.4743 to 0.6547). In contrast, the sigmoidal model outperformed across all temperature conditions (R² > 0.96) and produced predictions deviating by less than ±20% from measured values. Temperature-dependent shifts in factor influence were observed, with stiffness and gradation dominating at low temperatures and reclaimed asphalt (RA) content becoming more significant at higher temperatures. While the GRA-MLR model is advantageous, offering rapid assessments and early-stage evaluations, the sigmoidal model offers the precision suited for detailed design. Integrating both models can balance computational efficiency and provide a balanced strategy, with strong predictive reliability to advance mechanistic–empirical pavement design. Full article

(This article belongs to the Topic New Technological Solutions, Research Methods, Simulation and Analytical Models That Support the Development of Modern Transport Systems, 2nd Edition)

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30 pages, 4234 KB

Open AccessArticle

Quantitative Assessment of Seismic Retrofit Strategies for RC School Buildings Using Steel Exoskeletons and Localized Strengthening

by Armando La Scala

Infrastructures 2025, 10(10), 268; https://doi.org/10.3390/infrastructures10100268 - 9 Oct 2025

Viewed by 475

Abstract

This study offers a quantitative performance assessment of integrated seismic retrofit designs applied to an in-service 1960s reinforced concrete school structure in Central Italy. The research combines in-depth experimental material characterization with complex numerical simulations in order to estimate both the independent and [...] Read more.

This study offers a quantitative performance assessment of integrated seismic retrofit designs applied to an in-service 1960s reinforced concrete school structure in Central Italy. The research combines in-depth experimental material characterization with complex numerical simulations in order to estimate both the independent and interaction effects of external steel exoskeletons in conjunction with localized CAM (Cucitura Attiva dei Materiali) strengthening. The experimental investigation includes extensive material characterization through core drilling and non-destructive pacometric inspections to accurately define the existing concrete properties. The numerical analysis is performed with Finite Element modeling to estimate four different structural conditions: the original state, the condition with static strengthening, the condition with additional steel exoskeletons, and the condition with both exoskeletons and localized CAM reinforcements. The results quantitatively estimate the specific performance gains from the individual retrofit strategies. The steel exoskeletons show effective reduction in inter-story drifts but negligible effect on strength-oriented failure mechanisms. Localized CAM strengthening therefore stands out as necessary in reaching adequate safety levels in all the failure mechanisms. Economic analysis reveals that while steel exoskeletons provide the major cost component, the integrated approach with localized strengthening is essential for achieving comprehensive seismic safety enhancement. Full article

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24 pages, 2660 KB

Open AccessArticle

Determination of Mohr–Coulomb Failure Criterion of Cement-Treated Materials Using Mixture Design Properties

by Mario Castaneda-Lopez, Thomas Lenoir, Luc Thorel and Jean-Pierre Sanfratello

Infrastructures 2025, 10(10), 267; https://doi.org/10.3390/infrastructures10100267 - 9 Oct 2025

Cited by 1 | Viewed by 467

Abstract

The compressive, tensile, and shear strength properties of two cement-stabilized soils (CSS) treated with 2% to 4% of cement are investigated for several different curing times at several densities. The measured Mohr–Coulomb (MC) shear strength features, cohesion (c), and friction angle [...] Read more.

The compressive, tensile, and shear strength properties of two cement-stabilized soils (CSS) treated with 2% to 4% of cement are investigated for several different curing times at several densities. The measured Mohr–Coulomb (MC) shear strength features, cohesion (c), and friction angle (φ) are compared with values reported in the literature for similar materials and are subject to debate depending on the estimation methods used. In addition, an alternative geometric criterion based on indirect tensile strength (ITS) and unconfined compressive strength (UCS) is evaluated. The results show that the value of c determined using the alternative criterion is slightly higher than the value of c measured using the direct shear (DS) test. A relationship between mixture variables and c is established and validated by combining numerical and experimental approaches. The friction angle appears to be constant, independent of mixture parameters. This parameter is underestimated using the geometric approach. Full article

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37 pages, 3970 KB

Open AccessArticle

Digital Integration in Construction: A Case Study on Common Data Environment Implementation for a Metro Line Project

by Samuel Da Silva and Conrad Boton

Infrastructures 2025, 10(10), 266; https://doi.org/10.3390/infrastructures10100266 - 8 Oct 2025

Viewed by 817

Abstract

This study examines the deployment of a Common Data Environment (CDE) during the extension of a major North American metro line—an infrastructure project marked by complex stakeholder dynamics and fragmented digital practices. Employing a four-phase action research approach (diagnosis, planning, implementation, evaluation), the [...] Read more.

This study examines the deployment of a Common Data Environment (CDE) during the extension of a major North American metro line—an infrastructure project marked by complex stakeholder dynamics and fragmented digital practices. Employing a four-phase action research approach (diagnosis, planning, implementation, evaluation), the research identifies inefficiencies in existing document management through contract reviews, field observations, and stakeholder interviews. In response, three standardized processes were introduced to streamline document workflows within the Autodesk Construction Cloud (ACC). These processes enabled partial automation of data handling, reduced reliance on manual inputs, and improved the consistency of information exchanges. While constrained by limited governance and executive engagement, the initiative demonstrates the potential of CDEs to support digital integration and automation in construction. Findings highlight the need for early planning, field-level support, and a strategic framework to ensure sustainable adoption. The results contribute practical insights for leveraging CDEs to enhance automation in large-scale infrastructure projects. Full article

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29 pages, 2357 KB

Open AccessArticle

A Comprehensive Decision Support Tool for Accelerated Bridge Construction

by Nasim Mohamadiazar and Ali Ebrahimian

Infrastructures 2025, 10(10), 265; https://doi.org/10.3390/infrastructures10100265 - 8 Oct 2025

Viewed by 562

Abstract

Over 35% of bridges in the United States are currently rated in fair or poor condition, highlighting ongoing challenges in maintaining safety and performance amid aging infrastructure, limited budgets, and extended repair timelines. While Accelerated Bridge Construction (ABC) offers a faster solution, its [...] Read more.

Over 35% of bridges in the United States are currently rated in fair or poor condition, highlighting ongoing challenges in maintaining safety and performance amid aging infrastructure, limited budgets, and extended repair timelines. While Accelerated Bridge Construction (ABC) offers a faster solution, its adoption requires comprehensive decision frameworks. This paper presents a multi-criteria decision support tool (DST) that builds on the Connecticut Department of Transportation (CTDOT) ABC decision matrix. This DST quantifies the benefits of ABC for road and work zone safety, social equity, and environmental justice (SEEJ) and integrates them with structural, traffic, and construction factors to provide a comprehensive approach for determining the suitability of ABC techniques in bridge construction projects. Crash costs and corresponding safety benefits are quantified based on crash severity and frequency. While the tool incorporates both safety and SEEJ criteria, it also allows decision makers to consider either criterion individually based on their preferences. To demonstrate the applicability and benefits of the tool, it was applied to case studies in Connecticut. The results demonstrated how the considerations of safety and SEEJ can affect ABC decision-making. The presented DST is simple (Excel-based) and offers a practical and flexible tool that utilizes readily available data from national databases, making it applicable to all state DOTs across the United States. Full article

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25 pages, 3896 KB

Open AccessArticle

Bridge Risk Index for Freight Corridor Resilience: A Non-Parametric Machine Learning and Threat Modeling Approach

by Raj Bridgelall

Infrastructures 2025, 10(10), 264; https://doi.org/10.3390/infrastructures10100264 - 7 Oct 2025

Viewed by 515

Abstract

Bridges are critical nodes in freight networks, yet limited funding prevents agencies from maintaining all structures in good condition. This creates the need for a transparent and scalable method to identify which bridges pose the greatest risk to supply chain continuity. This study [...] Read more.

Bridges are critical nodes in freight networks, yet limited funding prevents agencies from maintaining all structures in good condition. This creates the need for a transparent and scalable method to identify which bridges pose the greatest risk to supply chain continuity. This study develops a bridge risk index using the threat–vulnerability–consequence (TVC) framework and validates its components with machine learning. Threat is defined as per-lane average daily traffic, vulnerability as effective bridge age (epoch), and consequence as detour distance, with traffic also contributing to disruption magnitude. The methodology applies log transformation and normalization to construct an interpretable multiplicative index, then classifies risk using Jenks natural breaks. The results show that epoch dominates vulnerability, detour distance amplifies consequence, and their interaction explains most of the risk variation. Specifically, effective age explains over three times more variation in bridge condition than any other attribute. The vulnerability–consequence interaction dominates with an R² = 0.98. The highest-risk bridges are concentrated in rural areas and near major freight gateways where detour options are limited. The proposed TVC index provides a transparent, data-driven decision-support tool that agencies can apply nationwide to prioritize investments, safeguard freight corridors, and strengthen supply chain resilience. Full article

(This article belongs to the Special Issue Sustainable Bridge Engineering)

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19 pages, 3652 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

Viewed by 440

Abstract

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

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20 pages, 8594 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

Viewed by 336

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)

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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

Viewed by 539

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

Viewed by 598

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

Viewed by 534

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

Viewed by 395

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

Viewed by 534

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

Viewed by 426

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

Viewed by 539

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

Viewed by 522

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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Infrastructures, Volume 10, Issue 10 (October 2025) – 25 articles

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