Infrastructures

21 pages, 17353 KB

Open AccessArticle

Verification of Possibility of Using Prestressed CFRP Strips to Strengthen Concrete Box Girder Bridge—Case Study

by Peter Koteš, Ondrej Krídla, Martin Vavruš, František Bahleda, Michal Zahuranec, Jozef Prokop and Matúš Farbák

Infrastructures 2026, 11(5), 180; https://doi.org/10.3390/infrastructures11050180 - 21 May 2026

Viewed by 165

Abstract

Strengthening existing structures and bridges allows us to continue using them, increase their reliability, resistance, durability and extend their service life instead of demolishing them and replacing them with new ones. This helps to reduce CO₂ (decarbonization). The use of prestressed CFRP [...] Read more.

Strengthening existing structures and bridges allows us to continue using them, increase their reliability, resistance, durability and extend their service life instead of demolishing them and replacing them with new ones. This helps to reduce CO₂ (decarbonization). The use of prestressed CFRP strips represents the use of new modern materials and new technology for strengthening existing bridges. The paper is focused on the use of prestressed CFRP strips for strengthening a concrete bridge made of precast prestressed box girders as the most suitable strengthening alternative in a given case. This is a technology that is more commonly used for strengthening structures, but it is not common to use this technology for strengthening bridges. There are relatively few examples of using this technology for strengthening bridges, also because these are dynamically loaded structures. The paper firstly presents the diagnostics and calculation of the load-carrying capacity of the railway bridge on a narrow-gauge railway line in Štrbské Pleso, Slovakia, and then the strengthening of the given bridge. The bridge is located in the mountains of the High Tatras in the northern part of Slovakia and bypasses two local roads. The bridge was made from the precast prestressed post-tensioned box girders of six single spans. The visual inspection, diagnostics, and verification of real dimensions and material characteristics were requested. The non-destructive and semi-destructive methods of testing were used to determine the geometrical and materials’ properties. After that, the calculation of the load-carrying capacity was done. For this purpose, a numerical 3D FEM model was created. For determining the load-carrying capacity, the standard approach, given in Eurocodes, was used according to provisions, which take into account the modified (lower) reliability levels and their adequate partial safety factors. From the calculation, it follows that the bridge should be strengthened. The strengthening of the superstructure was done using prestressed CFRP strips in the lower part of the box girders. This is one of the first applications of this modern method of strengthening, not only in Slovakia but in Central Europe as well. Full article

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31 pages, 7768 KB

Open AccessArticle

A Design Model for Urban Single-Lane Roundabouts with Offset Approaches

by Ivica Stančerić, Saša Ahac, Šime Bezina and Tamara Džambas

Infrastructures 2026, 11(5), 179; https://doi.org/10.3390/infrastructures11050179 - 20 May 2026

Viewed by 329

Abstract

The roundabout design procedures specified in current standards and guidelines presuppose that the centrelines of the approach legs intersect at right angles at the geometric centre of the roundabout. In urban areas, this requirement cannot always be met due to fixed structural constraints [...] Read more.

The roundabout design procedures specified in current standards and guidelines presuppose that the centrelines of the approach legs intersect at right angles at the geometric centre of the roundabout. In urban areas, this requirement cannot always be met due to fixed structural constraints along the approaches. Here, a lateral or radial offset of the approach legs from the roundabout’s geometric centre is required. This offset plays an important role in roundabout design, as it affects the roundabout’s ability to control vehicle speed. This study investigates the effects of a lateral approach leg offset on the geometric design of urban single-lane roundabouts and the driving speeds through them. Accordingly, speed analyses were conducted for numerous theoretical roundabouts with outer radii between 15 and 25 m, designed based on swept path analysis results, were conducted. The research results showed that it is possible to offset approaches laterally on roundabouts with outer radii between 15 and 25 m, depending on the design vehicle, and that the allowable offset values increase proportionally with the roundabout outer radius. The analysis results were used to create a design model for urban single-lane roundabouts with lateral approach leg offsets enabling their adaptation to spatial constraints while maintaining safe operating speeds. Full article

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

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20 pages, 4624 KB

Open AccessArticle

Crack Width Calculation Method for Concrete in Hogging Moment Region of Steel–UHPC–NC Composite Girder with Integrated Piers

by Li-Tao Yu, Chunbin Yu, Fawas. O. Matanmi and Zhiping Lin

Infrastructures 2026, 11(5), 178; https://doi.org/10.3390/infrastructures11050178 - 19 May 2026

Viewed by 188

Abstract

The application of ultra-high performance concrete (UHPC) in the hogging moment region significantly enhances the crack resistance of concrete slabs of composite girders with integrated piers, while also providing economic benefits. To investigate the crack resistance performance and develop a calculation method for [...] Read more.

The application of ultra-high performance concrete (UHPC) in the hogging moment region significantly enhances the crack resistance of concrete slabs of composite girders with integrated piers, while also providing economic benefits. To investigate the crack resistance performance and develop a calculation method for crack width in hogging moment region of steel–UHPC–normal concrete (NC) composite girders, a full-scale bending test was conducted. Based on the test results, the post-cracking residual tensile strength of UHPC was determined according to the energy equivalence principle. A calculation method for reinforcement stress incorporating the tensile contribution of UHPC at a cracked section was proposed and then the applicability for current design codes for crack width calculation was evaluated. For the UHPC–NC interface, a corresponding crack width calculation method was developed. The results indicate that cracks initiated on the surface of the NC layer beneath the UHPC overlay at the cantilever root. Then cracks developed in sequence at the top surface of the UHPC layer cantilever root, the UHPC–NC interface, and the mid-plane of the girder-to-pier joint. Ultimately, UHPC cracks exhibited a “numerous and closely spaced” distribution, whereas NC cracks were “few and widely spaced.” When the residual tensile strength of UHPC at cracked section was considered, the mean value and average coefficient of variation in the ratios of calculated to measured reinforcement stresses for different sections were 1.07 and 0.10, respectively, which can be further used for crack width calculation. The mean ratios of code-predicted to measured UHPC crack widths for different sections using the Chinese code, French code, and European code were 1.10, 0.98, and 1.13, respectively, with corresponding average coefficients of variation of 0.25, 0.33, and 0.28; the Chinese code is recommended for UHPC crack width prediction. For the UHPC–NC interface, an expression for crack width calculation was derived using the comprehensive theory, and the mean ratio of calculated to measured values and the coefficient of variation were 1.08 and 0.18, respectively, demonstrating good predictive accuracy. Full article

(This article belongs to the Special Issue Resilient and Sustainable Steel Structures: Advanced Manufacturing, Lifetime Extension and Disaster Mitigation)

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19 pages, 574 KB

Open AccessArticle

Statistical Modeling of the Probability and Duration of Hazardous Liquid Pipeline Shutdowns: A Hurdle Regression Approach

by Erfan Ramezanpour and Alexander Hainen

Infrastructures 2026, 11(5), 177; https://doi.org/10.3390/infrastructures11050177 - 18 May 2026

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Abstract

Operational shutdowns following hazardous liquid pipeline incidents are critical but poorly understood events that impact the U.S. energy supply. Although prior research has investigated the causes and outcomes of pipeline failures, limited work has explained what drives both the likelihood of a shutdown [...] Read more.

Operational shutdowns following hazardous liquid pipeline incidents are critical but poorly understood events that impact the U.S. energy supply. Although prior research has investigated the causes and outcomes of pipeline failures, limited work has explained what drives both the likelihood of a shutdown and the duration once it begins. The goal of this study is to address this gap by developing a hurdle regression model to examine the two-stage shutdown mechanism in pipeline incidents, using the Pipeline and Hazardous Materials Safety Administration (PHMSA) incident dataset from 2010 to 2025. The hurdle model consists of a logistic regression restricted to pre-decision predictors to model the probability of shutdown, and a lognormal regression to model the duration of those leading to shutdown. The results revealed that distinct factors are associated with each outcome. Shutdown probability is associated with pre-decision operational and contextual indicators, including operating pressure at the time of incident, accident type, location, monitoring presence, and response delay. In contrast, shutdown duration is associated with logistical complexity and post-incident severity, including incidents at pipeline crossings, pressures exceeding 110% of the maximum operating pressure, and reported property damage. These findings, while exploratory in nature given the use of public incident data, offer practical reference points for operators and regulators who aim to shorten recovery time and strengthen the resilience of energy infrastructure. Full article

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36 pages, 1266 KB

Open AccessArticle

Disaggregate Analysis of Crash Severity for Heavy-Duty, Medium-Duty, and Light-Duty Vehicles: A Random Parameters Approach with Observed and Unobserved Heterogeneity

by Thanapong Champahom, Chamroeun Se, Supanida Nanthawong, Panuwat Wisutwattanasak, Chinnakrit Banyong, Sajjakaj Jomnonkwao and Vatanavongs Ratanavaraha

Infrastructures 2026, 11(5), 176; https://doi.org/10.3390/infrastructures11050176 - 16 May 2026

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Abstract

Crashes involving freight and commercial vehicles impose substantial human and economic costs, yet most severity studies pool vehicle types or focus exclusively on heavy trucks, masking class-specific risk mechanisms. This study estimates separate Random Parameters Binary Logit models with heterogeneity in means and [...] Read more.

Crashes involving freight and commercial vehicles impose substantial human and economic costs, yet most severity studies pool vehicle types or focus exclusively on heavy trucks, masking class-specific risk mechanisms. This study estimates separate Random Parameters Binary Logit models with heterogeneity in means and variances for three vehicle categories—heavy-duty multi-axle trucks (n = 6512), two-axle trucks (n = 2656), and light-duty pickup trucks (n = 23,477)—using 32,645 crash records from Thailand’s national highway network (May 2022–December 2024). Pairwise transferability tests rejected parameter transferability, with four of six comparisons exceeding the 97 percent confidence level (three of these above 99 percent; χ² = 85.38 to 240.01), confirming that disaggregate estimation is statistically warranted. Three core findings emerge: First, although barrier medians, cut-in-front maneuvers, and sideswipe crashes affect severity in consistent directions across all vehicle types, their magnitudes differ sharply: the protective effect of barrier medians is nearly six times larger for two-axle trucks (ME = −0.160) compared to heavy-duty trucks (ME = −0.028). Second, several determinants are class-specific: dark unlit conditions elevate severity only for two-axle trucks (ME = 0.128), flush medians only for heavy-duty trucks (ME = 0.040), and raised medians only for light-duty pickups (ME = 0.042). Third, no random parameter is common to all three models. Pooled models, therefore, impose misleading homogeneity assumptions; vehicle-type-specific estimation is essential for targeted safety policy. Full article

(This article belongs to the Special Issue Smart Mobility and Transportation Infrastructure)

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24 pages, 1068 KB

Open AccessArticle

Research on Maximum Synchronous Transfer Between Metro and Bus Considering Passenger Flow Constraint

by Ziye Lan, Shuyi Wang, Yinzhu Zhao, Yimeng Liu and Yuanwen Lai

Infrastructures 2026, 11(5), 175; https://doi.org/10.3390/infrastructures11050175 - 15 May 2026

Viewed by 241

Abstract

Synchronous transfer has been widely studied in public transport scheduling, with most research focusing on coordination among conventional bus lines. However, with the rapid expansion of urban rail transit systems, metro–bus transfers have become increasingly important for enhancing overall urban public transport network [...] Read more.

Synchronous transfer has been widely studied in public transport scheduling, with most research focusing on coordination among conventional bus lines. However, with the rapid expansion of urban rail transit systems, metro–bus transfers have become increasingly important for enhancing overall urban public transport network performance. This study investigates the maximum synchronous transfer problem between metro and conventional bus services under passenger flow constraints. Considering the large transfer demand and the pulse-arrival characteristics of metro trains, a passenger waiting constraint at bus stops is incorporated to reflect capacity limitations and crowding effects. A passenger-flow-constrained maximum synchronization model is formulated to optimize bus departure times without increasing service frequency. Dongjiekou Metro Station and three surrounding pairs of bus stops are selected as a case study. Model parameters are determined through field surveys and operational data. The Grey Wolf Optimizer (GWO) and a simulated annealing–improved Grey Wolf Optimizer (SA-IGWO) are employed to solve the proposed model. The results show that both algorithms significantly improve synchronized transfer volumes by adjusting departure times without increasing service frequency. Compared with the original schedule, the SA-GWO achieves an improvement in synchronization performance ranging from 45% to 50%, outperforming the standard GWO. Full article

(This article belongs to the Special Issue Sustainable Road Infrastructure: Safety, Performance and Resilience)

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19 pages, 20254 KB

Open AccessArticle

Runway Microtexture Degradation Under Operational Wear and Rubber Contamination, and Subsequent Recovery: A Case Study

by Gadel Baimukhametov and Greg White

Infrastructures 2026, 11(5), 174; https://doi.org/10.3390/infrastructures11050174 - 15 May 2026

Viewed by 312

Abstract

Runway microtexture is a key parameter governing pavement friction. In recent years, several microtexture assessment methods have been developed; however, understanding of microtexture evolution under operational conditions, as well as the effects of maintenance techniques, remains limited. In this study, a runway at [...] Read more.

Runway microtexture is a key parameter governing pavement friction. In recent years, several microtexture assessment methods have been developed; however, understanding of microtexture evolution under operational conditions, as well as the effects of maintenance techniques, remains limited. In this study, a runway at an Australian airport was investigated using laser profilometry. Measurements were conducted across multiple transverse sections, including aircraft touchdown and mid-runway zones. Microtexture deterioration rates were evaluated based on the estimated number of tire–pavement contacts, and aggregate polishing was assessed at different locations. Measurements were also performed after rubber contamination removal and rejuvenation treatments. The results indicate that approximately 25% of total microtexture reduction can be attributed to surface polishing, with a lower contribution in touchdown zones due to the protective effect of rubber deposits. A non-linear degradation trend was observed in touchdown zones, where approximately 1100 tire contacts reduced average microtexture roughness from 18 μm to 11 μm. Rubber removal effectively restored microtexture close to its original levels across the runway width. A rejuvenation treatment with a covering of fine sand initially improved microtexture; however, rapid deterioration occurred due to loss of the sand coating. These findings improve the understanding of microtexture evolution under operational runway conditions, albeit only at a case study level, and support more effective runway maintenance planning and intervention strategies. Full article

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

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30 pages, 3505 KB

Open AccessArticle

Minimizing Cost Overrun in Rail Projects Through 5D-Bim: The Case Study of Victoria

by Osama A. I. Hussain, Robert C. Moehler, Stuart D. C. Walsh and Dominic D. Ahiaga-Dagbui

Infrastructures 2026, 11(5), 173; https://doi.org/10.3390/infrastructures11050173 - 14 May 2026

Viewed by 588

Abstract

This study evaluates the adoption and efficacy of the 5th Dimension Building Information Modelling (5D-BIM) as a cost dimension for mega rail projects, extending the discussion beyond just technological implementation to consider broader policy and practical implications. The purpose of this article is [...] Read more.

This study evaluates the adoption and efficacy of the 5th Dimension Building Information Modelling (5D-BIM) as a cost dimension for mega rail projects, extending the discussion beyond just technological implementation to consider broader policy and practical implications. The purpose of this article is to understand the governance context of 5D-BIM implementation for rail and transport projects and evaluate the effectiveness of the 5D-BIM framework as currently applied by conducting semi-structured interviews with key stakeholders. Drawing on semi-structured interviews with 22 stakeholders across government, industry, and technology providers, the research examines current 5D-BIM practices. While the primary focus of the research is 5D BIM implementations within the state of Victoria, Australia, which is currently experiencing a surge in rail projects, interviews were also conducted with additional stakeholders from international rail projects for context. The findings reveal fragmented adoption, varying levels of organisational maturity, and significant policy and implementation gaps, particularly in the role of government as the primary client of transport infrastructure. The results of the interviews emphasise the centrality of government and regulatory context in driving the adoption and implementation of 5D-BIM as the primary client of transportation infrastructure and identify actionable recommendations for policymakers and practitioners towards a more integrated approach to 5D-BIM in mega rail projects. While 5D-BIM demonstrates clear benefits in enhancing cost estimation, coordination, and decision-making, its effectiveness is constrained by the absence of clear standards, limited BIM literacy, and inconsistent regulatory guidance. This study provides one of the first empirical validations of the 5D-BIM governance framework, demonstrating that its success is driven less by technological capability and more by policy alignment, standardisation, and institutional leadership. Full article

(This article belongs to the Special Issue Building Information Modeling (BIM) for Civil Infrastructures)

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17 pages, 1850 KB

Open AccessArticle

Vapour-Driven Moisture Flux in Frozen Road Subgrades

by Assel Sarsembayeva, Saltanat Mussakhanova, Darkhan Sakanov, Iliyas Zhumadilov and Gulizat Orazbekova

Infrastructures 2026, 11(5), 172; https://doi.org/10.3390/infrastructures11050172 - 14 May 2026

Viewed by 215

Abstract

Frost heave in cold-region pavements is governed by coupled heat and moisture migration, but the specific contribution of vapour transport in multilayer subgrades remains poorly constrained. This study combines field temperature monitoring with analytical modelling to estimate effective thermal conductivities of pavement structural [...] Read more.

Frost heave in cold-region pavements is governed by coupled heat and moisture migration, but the specific contribution of vapour transport in multilayer subgrades remains poorly constrained. This study combines field temperature monitoring with analytical modelling to estimate effective thermal conductivities of pavement structural layers and to evaluate vapour-driven moisture fluxes during seasonal freezing. A vertical thermistor array beneath a two-lane highway near Astana (Kazakhstan) and in the adjacent snow-covered ground is used to back-calculate layer-specific conductivities from midwinter temperature gradients by applying Fourier’s law under quasi-steady conditions. Vapour migration is then assessed by two complementary approaches. A diffusion-based formulation, which couples measured vapour-density gradients with air-filled porosity, provides a conservative lower bound and yields very small fluxes, with maximum daily ice deposition of 8.17 × 10⁻⁵ kg·m⁻²·day⁻¹ beneath the pavement and cumulative seasonal masses of order 10⁻² kg·m⁻² (10⁻³ kg·m⁻² under snow). An energy-balance approach, which relates conductive heat flux to latent heat of vapour–ice phase change and introduces an efficiency parameter α, supplies a physically constrained upper envelope. For a central scenario with α = 0.6, daily deposition in the 0.60–1.00 m layer reaches 0.0961 and 0.0330 kg·m⁻²·day⁻¹ beneath pavement and snow, respectively, yielding seasonal totals of 12.1 and 4.1 kg·m⁻². Together, these bounds indicate that vapour migration beneath pavements, although unlikely to be the dominant driver of frost heave, can be substantially more intense than under adjacent snow-covered ground due to steeper temperature gradients in the upper subgrade. Full article

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19 pages, 2784 KB

Open AccessArticle

Beyond Mass Loss: Residual Flexural Strength as an Indicator for Concrete Durability in Sulfuric Acid and Sewage Environments

by Hatem Affes and Salem Georges Nehme

Infrastructures 2026, 11(5), 171; https://doi.org/10.3390/infrastructures11050171 - 14 May 2026

Viewed by 258

Abstract

Current industry standards for evaluating concrete durability in wastewater environments, such as ASTM C267, rely almost exclusively on mass loss as the primary performance indicator. This study demonstrates that mass change alone can be an ambiguous metric that does not fully characterize the [...] Read more.

Current industry standards for evaluating concrete durability in wastewater environments, such as ASTM C267, rely almost exclusively on mass loss as the primary performance indicator. This study demonstrates that mass change alone can be an ambiguous metric that does not fully characterize the structural degradation of advanced cementitious binders. Through a comprehensive physical, chemical, and mechanical evaluation of 27 binary and ternary mixtures (totalling 486 specimens), we identify four limitations of mass-based standards: (1) The Slag Anomaly, where excellent surface mass preservation masks a significant loss of internal structural capacity, indicating potential internal structural softening. (2) The Sewage Anomaly, where specimens in active biogenic environments exhibit mass gain (up to +1.21%) despite continuous chemical attack. (3) Non-Linear Scaling, where 5% “accelerated” acid tests fundamentally alter degradation kinetics compared to realistic 1% environments. (4) The Maturation Conflict, where extended curing (56 days) significantly improves the physical resistance of slow-reacting pozzolans (cyment) while increasing the mass loss of high-performance ternary blends (MK/SF), likely linked to the exhaustion of their chemical buffering capacity. Current standards relying solely on mass loss may not capture internal degradation in slag-based cements that remain geometrically intact. We propose residual flexural strength as a necessary complementary metric. Full article

(This article belongs to the Special Issue Recent Advances in Enhancing Sustainability and Durability of Cement and Concrete)

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37 pages, 11252 KB

Open AccessArticle

Strength and Ductility of Hybrid Steel and FRP Reinforced Concrete Sections Subjected to Combined Axial and Bending Regime

by Mattia Mairone, Gaetano Maragno, Davide Masera and Mauro Corrado

Infrastructures 2026, 11(5), 170; https://doi.org/10.3390/infrastructures11050170 - 13 May 2026

Viewed by 382

Abstract

Hybrid reinforced concrete (HRC) sections combining steel and fiber-reinforced polymer (FRP) bars provide a structural solution that balances durability, load-bearing capacity and energy dissipation. However, the absence of unified design provisions and the coexistence of distinct safety formats in European and American codes [...] Read more.

Hybrid reinforced concrete (HRC) sections combining steel and fiber-reinforced polymer (FRP) bars provide a structural solution that balances durability, load-bearing capacity and energy dissipation. However, the absence of unified design provisions and the coexistence of distinct safety formats in European and American codes complicate the consistent assessment of ultimate limit state behavior under combined axial force and bending moment. In this study, a strain-based sectional model founded on compatibility and internal force equilibrium is implemented through a layer-by-layer numerical integration procedure to generate axial force–bending moment (N–M) interaction domains and moment–curvature (M–

χ

) relationships. The formulation is extended to a dimensionless framework in terms of normalized axial load, bending moment, total hybrid mechanical reinforcement ratio

ω_{h}

and hybridization parameter R. The analysis is conducted within two regulatory formats: the European framework based on Eurocode 2 and CNR-DT 203 R1/2026 and the American framework based on ACI 318-25 and ACI 440.11-22. The results show that increasing

ω_{h}

leads to a progressive expansion of the interaction domain and modifies the transition between FRP rupture-controlled and steel-yielding-controlled limit states. Increasing R shifts balanced conditions towards higher axial compression and bending levels. Differences between the two regulatory approaches are observed in terms of predicted curvature capacity and design resistance within the N–M domain, reflecting the distinct safety formats adopted. The proposed dimensionless parametric formulation enables consistent comparison of hybrid configurations and provides basis for interpreting failure-mode transitions and deformation capacity of HRC sections under combined axial and flexural actions. Full article

(This article belongs to the Special Issue Recent Advances in Enhancing Sustainability and Durability of Cement and Concrete)

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19 pages, 6242 KB

Open AccessArticle

Constructing a Competency Model for EPC Safety Directors Under Smart Construction

by Jing Guan, Zhenchao Yang, Congcong Wang and Yisheng Liu

Infrastructures 2026, 11(5), 169; https://doi.org/10.3390/infrastructures11050169 - 12 May 2026

Viewed by 305

Abstract

In smart construction, identifying the competencies required of engineering–procurement–construction (EPC) safety directors is important for improving personnel selection, training, and safety-governance effectiveness. Drawing on dynamic capabilities theory, this study develops an exploratory competency framework for EPC safety directors in smart-construction contexts. A mixed-method [...] Read more.

In smart construction, identifying the competencies required of engineering–procurement–construction (EPC) safety directors is important for improving personnel selection, training, and safety-governance effectiveness. Drawing on dynamic capabilities theory, this study develops an exploratory competency framework for EPC safety directors in smart-construction contexts. A mixed-method design was adopted, combining a structured literature review, bibliometric mapping with CiteSpace, semistructured interviews, expert review, and questionnaire-based item screening. Questionnaire data from 189 valid respondents were analyzed using descriptive statistics, item analysis, Cronbach’s alpha, and KMO/Bartlett tests to preliminarily assess the internal consistency and structural suitability of the proposed indicators. The results indicate that the retained exploratory framework comprises three higher-order dimensions—sensing, seizing, and reconfiguring—covering six competency elements and eighteen indicators after the remaining trend-sensing indicator was integrated into data analytics. Compared with conventional safety-management competency frameworks, the proposed framework places greater emphasis on data analytics, intelligent systems application, and cross-departmental coordination in digitally enabled project environments. The framework can be implemented as a role-profile template for recruitment, training-needs diagnosis, and performance appraisal of EPC safety directors, while further empirical validation is required before it is used as a standardized measurement scale. Full article

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13 pages, 877 KB

Open AccessArticle

Network-Level Urban Pavement Optimization Using Priority-Based Genetic Algorithm Methodology

by Promothes Saha

Infrastructures 2026, 11(5), 168; https://doi.org/10.3390/infrastructures11050168 - 12 May 2026

Viewed by 250

Abstract

Pavement management systems (PMS) are essential for formulating a cost-effective capital improvement plan (CIP) that adheres to budget constraints. Optimization techniques are vital in enhancing the efficiency of these plans. Among the various methods available, genetic algorithms (GA) are particularly effective at identifying [...] Read more.

Pavement management systems (PMS) are essential for formulating a cost-effective capital improvement plan (CIP) that adheres to budget constraints. Optimization techniques are vital in enhancing the efficiency of these plans. Among the various methods available, genetic algorithms (GA) are particularly effective at identifying optimal solutions in complex scenarios. This study introduces a GA-based priority optimization model designed to select the most beneficial road improvement projects while staying within budgetary limits. The model was applied to the extensive road network of Fort Wayne, Indiana, considering critical factors such as budget allocation, roadway classification, PASERs, treatment options, and associated costs. The results demonstrate the model’s effectiveness in prioritizing projects, ensuring that available funds are utilized to achieve maximum impact on roadway conditions. By leveraging GA, this approach not only enhances decision-making processes but also provides a robust framework for future pavement management efforts. Overall, the integration of genetic algorithms into PMS can lead to more strategic and economically sound infrastructure improvements. Full article

(This article belongs to the Special Issue Sustainable and Digital Transformation of Road Infrastructures, 2nd Edition)

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1 pages, 129 KB

Open AccessRetraction

RETRACTED: Khedmatgozar Dolati et al. Guidelines for Nonlinear Finite Element Analysis of Reinforced Concrete Columns with Various Types of Degradation Subjected to Seismic Loading. Infrastructures 2024, 9, 227

by Seyed Sasan Khedmatgozar Dolati, Adolfo Matamoros and Wassim Ghannoum

Infrastructures 2026, 11(5), 167; https://doi.org/10.3390/infrastructures11050167 - 11 May 2026

Viewed by 251

Abstract

The journal retracts the article “Guidelines for Nonlinear Finite Element Analysis of Reinforced Concrete Columns with Various Types of Degradation Subjected to Seismic Loading” [...] Full article

(This article belongs to the Special Issue Structural Health Monitoring, Non-destructive Evaluation and Remedial Measures for Civil Infrastructures)

23 pages, 2115 KB

Open AccessArticle

Structural Analysis of Flexible Pavements with HMA Exposed to Short-Term Aging

by Taciano Oliveira da Silva, Klaus Henrique de Paula Rodrigues, Heraldo Nunes Pitanga, Francisco Aureliano Rocha de Vasconcelos Teixeira, Kelbia da Silva Santos, Paulo Roberto Borges, Gustavo Henrique Nalon and Karine de Oliveira Santos

Infrastructures 2026, 11(5), 166; https://doi.org/10.3390/infrastructures11050166 - 9 May 2026

Viewed by 332

Abstract

This study presents a comparative evaluation of the structural performance of flexible pavements made from different hot mix asphalt (HMA). HMAs were proportioned using the conventional Marshall method and HMAs subjected to short-term aging were analyzed. Grades B (binder course) and C (surface [...] Read more.

This study presents a comparative evaluation of the structural performance of flexible pavements made from different hot mix asphalt (HMA). HMAs were proportioned using the conventional Marshall method and HMAs subjected to short-term aging were analyzed. Grades B (binder course) and C (surface course), according to DNIT specifications, were used. After determining the aggregate gradation and asphalt content using the Marshall method, test specimens were produced and tested in the laboratory to determine the mechanical parameters characteristic of each HMA (stability, tensile strength by diametral compression, resilient modulus, fatigue behavior, and permanent strain). The Elsym5 software was used to carry out a structural analysis of an assumed pavement, whereby only the mechanical properties of the surface course and the binder course were varied. The results showed that short-term aging significantly affected the mechanical behavior of HMA and the structural response of flexible pavements. Better structural performance was observed in HMAs subjected to short-term aging. The aged specimens showed an improvement in mechanical properties compared to specimens produced by the conventional method, indicating a promising approach for optimizing pavement performance. These results provided new parameters for investigation and development in the field of road engineering. Full article

(This article belongs to the Special Issue Advances in Pavement Engineering: Materials, Performance, and Sustainability)

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37 pages, 6363 KB

Open AccessArticle

Experimental and Numerical Investigation of Sustainable Geopolymer Concrete Incorporating Eco-Friendly Materials for Geotechnical Applications

by Nour Bassim Frahat, Mohamed Samy, Mohamed Amin, Ibrahim Saad Agwa and Engy M. Kassem

Infrastructures 2026, 11(5), 165; https://doi.org/10.3390/infrastructures11050165 - 9 May 2026

Viewed by 253

Abstract

This study extends beyond traditional single-binder assessments by developing a mechanistic framework for interpreting the behavior of multi-component geopolymer systems. It systematically examines the roles of industrial by-products (granulated blast-furnace slag), agricultural residues (barley straw ash), and construction-derived materials (recycled granite powder) when [...] Read more.

This study extends beyond traditional single-binder assessments by developing a mechanistic framework for interpreting the behavior of multi-component geopolymer systems. It systematically examines the roles of industrial by-products (granulated blast-furnace slag), agricultural residues (barley straw ash), and construction-derived materials (recycled granite powder) when integrated into a metakaolin-based matrix, with particular emphasis on their influence on gel formation pathways, microstructural refinement, and macroscopic performance. A sustainable geopolymer concrete (SGC) system was formulated using multi-binder combinations at replacement levels ranging from 5% to 30%. Comprehensive evaluations were conducted, including fresh properties, mechanical performance, durability characteristics, thermal resistance, and microstructural features. The results demonstrate that the 70Mk–30GBFS composition facilitates the development of a dense hybrid C–(A)–S–H/N–A–S–H gel network, resulting in a 26.8% enhancement in compressive strength and a 32.0% decrease in chloride ion penetration. Rather than depending on empirical relationships, the study establishes a mechanistically grounded link between precursor chemistry, interfacial transition zone (ITZ) refinement, and performance limits. These findings contribute to a deeper understanding of multi-component geopolymer design and support the development of high-performance, sustainable concrete materials for structural applications. Full article

(This article belongs to the Special Issue From Material Testing to Structural Applications of Eco-Friendly Concrete)

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25 pages, 4429 KB

Open AccessArticle

Comparative Study of Modal Curvature and AI-Based Approaches for Vibration-Based Damage Detection in Structural Health Monitoring Systems of Prestressed Concrete Beams

by Antonio Bilotta, Andrea Pollastro, Ivan Di Cristinzi and Maria Rosaria Pecce

Infrastructures 2026, 11(5), 164; https://doi.org/10.3390/infrastructures11050164 - 8 May 2026

Viewed by 374

Abstract

Vibration-based damage detection methods are increasingly recognized as effective tools for monitoring the structural health of bridges. However, their reliability and applicability to various types of structural defects require further study, especially based on experimental tests, to correctly interpretate the results and compare [...] Read more.

Vibration-based damage detection methods are increasingly recognized as effective tools for monitoring the structural health of bridges. However, their reliability and applicability to various types of structural defects require further study, especially based on experimental tests, to correctly interpretate the results and compare the efficiency of different damage indexes. In the field of Structural Health Monitoring (SHM) by dynamic techniques, operational modal analysis (OMA) is of particular interest because only ambient signals are used, avoiding the service interruption of the infrastructures. However, the key issues of an efficient SHM are the possibility to have a quick alarm if an anomalous response is detected and the capability to localize the defect. Several methods can be applied for the anomaly detection considering machine learning, moving further than global modal parameters like the vibration frequency. Conversely for defect localization, local modal parameters, like modal curvature, can be efficient but also a different application of machine learning can be considered. In this paper, two approaches are compared for level 1 (detection) and 2 (localization) damage detection using acceleration measurements: the modal parameters and an Artificial Intelligence (AI)-based procedure using Variational Autoencoders (VAEs). The case study is a set of post-tensioned prestress concrete (PC) beams that represent a wide stock of existing bridges characterized by defects due to a reduction in the prestressing load, a lack of mortar in ducts, and corrosion of tendons. The results show that both methods can be effective, even if defects in PC beams are difficult to be detect with the dynamic response. Finally, the AI-based approach seems a promising solution because I allows for an earlier alarm, even with few sensors, while the modal curvature approach provides a better explanation of the identified anomaly, although it requires a greater number of sensors. 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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30 pages, 7153 KB

Open AccessArticle

Assessment of Integral Abutment Retrofit Performance for Steel Bridges Subjected to Thermal Loading

by Jawad H. Gull, Sana Amir and Qasim Shaukat Khan

Infrastructures 2026, 11(5), 163; https://doi.org/10.3390/infrastructures11050163 - 7 May 2026

Viewed by 265

Abstract

Integral abutment bridges (IABs) eliminate deck joints by rigidly connecting the superstructure to the abutments, reducing maintenance costs but introducing thermal restraint forces. When only one abutment is made integral, all thermally induced longitudinal movement concentrates at the remaining non-integral end, overloading bearings [...] Read more.

Integral abutment bridges (IABs) eliminate deck joints by rigidly connecting the superstructure to the abutments, reducing maintenance costs but introducing thermal restraint forces. When only one abutment is made integral, all thermally induced longitudinal movement concentrates at the remaining non-integral end, overloading bearings and concrete elements not designed for this condition. This paper investigates IAB behavior and evaluates two repair options for two, three-span continuous steel bridges on Interstate 635 in Kansas City, Kansas, which sustained progressive abutment damage following a unilateral integral conversion in 2005. A 2D finite element model was developed in LARSA 4D, incorporating composite superstructure elements, shell element abutments, beam element piles, and soil-structure interaction via distributed lateral springs. The model was analyzed under dead, live, braking, and thermal load combinations in accordance with AASHTO LRFD. Full integral conversion generates thermal restraint moments of approximately 813.5 kN-m (600 kip-ft) at the abutments, and pile stresses of 383.9 MPa (55.68 ksi) under Service I and 497.4 MPa (72.14 ksi) under Strength I combinations, both exceeding allowable limits. Elastomeric bearing pads at the non-integral abutment satisfied all stress limits without foundation modification and are recommended as a practical repair strategy for bridges in similar conditions. Full article

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

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23 pages, 5138 KB

Open AccessArticle

Translating Regional Air-Temperature Exposure into Thermal States of Pavement Materials: A Probabilistic Screening Framework

by Shuo Liu, Jingbo Qing and Jiabin Liu

Infrastructures 2026, 11(5), 162; https://doi.org/10.3390/infrastructures11050162 - 7 May 2026

Viewed by 238

Abstract

Meteorological archives often preserve abundant air-temperature records. However, verified pavement distress records are often unavailable. This makes it difficult to translate archive-scale temperature data into material thermal states that can support engineering screening and interpretation. This study develops a temperature-only probabilistic framework that [...] Read more.

Meteorological archives often preserve abundant air-temperature records. However, verified pavement distress records are often unavailable. This makes it difficult to translate archive-scale temperature data into material thermal states that can support engineering screening and interpretation. This study develops a temperature-only probabilistic framework that links a national daily air-temperature background with asphalt and concrete thermal states through site-specific calibration. Northeast China was selected as the case study region, where synchronous 5-min observations of air, concrete, and asphalt temperatures were available from 2024 to 2025. Nationwide daily records from 1951 to 2019 place the air-temperature exposure background of the case study region in a national context. The case study region does not emerge as a dominant national hot-tail regime. Instead, it is characterized by colder minima and larger daily air-temperature ranges than the pooled national background. Under the same air-temperature exposure, asphalt showed stronger amplification of thermal peaks and diurnal cycling than concrete. In the case study region, both materials show a consistently cold-dominant screening pattern, with fluctuation screening secondary and hot screening limited. This qualitative ordering is preserved across weighting, archive-window, and transfer model sensitivity analyses, although hot and fluctuation magnitudes are less stable than the cold side estimates. The framework should therefore be interpreted as a thermal screening tool calibrated at a single monitored site, rather than as a universally validated distress or failure model. Full article

(This article belongs to the Special Issue Advances in Pavement Engineering: Materials, Performance, and Sustainability)

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18 pages, 2950 KB

Open AccessArticle

A Target-Free Vision-Based Method for Measuring Girder Rigid-Body Displacement Under Long-Distance Imaging Conditions

by Guangyu Li, Hai-Bin Huang, Shengzhi Ai, Yuan Cheng and Dong Liang

Infrastructures 2026, 11(5), 161; https://doi.org/10.3390/infrastructures11050161 - 6 May 2026

Viewed by 297

Abstract

The rigid-body displacement of bridge girders, particularly the lateral displacement of curved girder bridges, is a critical indicator reflecting the structural safety reserve and durability of bridges. However, under long-distance imaging conditions, the inherent scale ambiguity and perspective distortion in monocular vision measurement, [...] Read more.

The rigid-body displacement of bridge girders, particularly the lateral displacement of curved girder bridges, is a critical indicator reflecting the structural safety reserve and durability of bridges. However, under long-distance imaging conditions, the inherent scale ambiguity and perspective distortion in monocular vision measurement, coupled with environmental interferences such as weakened natural edges and varying illumination, pose severe challenges to target-free, high-precision, and real-time displacement measurement. To this end, this paper proposes a target-free visual method for measuring rigid-body displacement of bridge girders under long-distance imaging. By fusing optical flow and Hough transform to extract seismic block edges and adopting hierarchical NCC matching for stable girder tracking, the method achieves millimeter-level accuracy, real-time performance, and strong illumination robustness. Model tests and field validation confirm its effectiveness for low-cost bridge health monitoring. Full article

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

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22 pages, 2743 KB

Open AccessArticle

Optimal Monitoring Section Layout for iFEM-Based Strain Reconstruction of Subsea Pipelines via Greedy Search

by Xueyu Ren, Jiawang Chen, Shang Sun, Jianling Zhou, Zhonghui Zhou and Yuan Lin

Infrastructures 2026, 11(5), 160; https://doi.org/10.3390/infrastructures11050160 - 6 May 2026

Viewed by 357

Abstract

Subsea oil and gas pipelines are critical infrastructure in marine engineering, and strain monitoring is essential for their safe operation. However, due to the complexity of the marine environment and the constraints practical deployment, engineering applications often rely on sparse monitoring points, making [...] Read more.

Subsea oil and gas pipelines are critical infrastructure in marine engineering, and strain monitoring is essential for their safe operation. However, due to the complexity of the marine environment and the constraints practical deployment, engineering applications often rely on sparse monitoring points, making it difficult to directly obtain full-field strain information. To address this issue, this paper proposes a strain field reconstruction method for subsea suspended pipelines based on the inverse finite element method (iFEM) and a greedy search strategy, and provides the corresponding optimal layout of monitoring cross-sections. Using a constructed numerical simulation library under multiple load cases, algorithm validation and parameter calibration are performed. On this basis, a comprehensive evaluation framework incorporating both global and peak errors is established. Results show that under the greedy-optimized monitoring section scheme, the comprehensive reconstruction error of iFEM ranges from 0.030 to 0.035, the axial strain error is significantly lower than the circumferential strain error, and the peak relative error stabilizes when the number of monitoring sections reaches seven. The proposed method overcomes the difficulty of acquiring full-field strain information under sparse monitoring conditions, and can provide technical support for the structural health monitoring and safety assessment of subsea oil and gas pipelines. Full article

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

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20 pages, 1072 KB

Open AccessSystematic Review

Computer Vision and Machine Learning Approaches for Defect Detection in 3D-Printed Cementitious Materials: A Systematic Review

by Muhammad Ali Musarat, Ruben Paul Borg, Jingjie Wei, Carl James Debono and Kamal Khayat

Infrastructures 2026, 11(5), 159; https://doi.org/10.3390/infrastructures11050159 - 4 May 2026

Viewed by 1063

Abstract

3D printing is evolving at a fast pace in both the manufacturing and construction sectors. These advancements can greatly benefit these industries. However, the 3D printing of concrete structures presents some challenges due to defects in the 3D concrete printed elements. Hence, this [...] Read more.

3D printing is evolving at a fast pace in both the manufacturing and construction sectors. These advancements can greatly benefit these industries. However, the 3D printing of concrete structures presents some challenges due to defects in the 3D concrete printed elements. Hence, this study systematically reviews Artificial Intelligence (AI)-driven techniques, such as Computer Vision and Machine Learning, to identify surface defects that can occur in 3D-printed cementitious material structures. The adopted methodology was the PRISMA statement with the aim of reporting the systematic review and meta-analysis. Two well-known databases, Web of Science and Scopus, were utilised for data extraction of articles published during the past 10 years, between 2014 and May 2025. The initial search provided 110 articles, both conference and journal papers; after screening, only 11 were left for the final review assessment. The smaller number of the final articles shows that much work is still needed in this area. It has been observed that various computer vision and machine learning-based methodologies were employed to classify defects in 3D concrete printed structures. Deep learning algorithms, such as YOLO and RT-DETR, were featured as the most efficient in real-time defect detection and quality monitoring. It was also observed that real-time monitoring systems attached to 3D printers help in reducing the material wastage, which is essential to meet the sustainable goals. However, more work is still required to underline the defects of 3D-printed cementitious material, probably with the involvement of AI image processing tools and techniques. This can help to automate the defects in 3D-printed structures, and by this, the productivity could be enhanced. Full article

(This article belongs to the Special Issue Recent Advances in Enhancing Sustainability and Durability of Cement and Concrete)

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46 pages, 1692 KB

Open AccessSystematic Review

Materials Pathways for Low-Carbon Construction: A Systematic Review of Bio-Based, Recycled, and Alternative Cementitious Systems

by Hugo Martínez Ángeles, Cesar Augusto Navarro Rubio, José Gabriel Ríos Moreno, Margarita G. Garcia-Barajas, Roberto Valentín Carrillo-Serrano, José Luis Reyes Araiza, Ernesto Chavero-Navarrete and Mario Trejo Perea

Infrastructures 2026, 11(5), 158; https://doi.org/10.3390/infrastructures11050158 - 3 May 2026

Viewed by 376

Abstract

The construction sector is responsible for significant global energy consumption and CO₂ emissions, largely driven by carbon-intensive materials such as ordinary Portland cement and steel. In response to increasing decarbonization and circular economy demands, several strategically relevant categories of sustainable construction materials [...] Read more.

The construction sector is responsible for significant global energy consumption and CO₂ emissions, largely driven by carbon-intensive materials such as ordinary Portland cement and steel. In response to increasing decarbonization and circular economy demands, several strategically relevant categories of sustainable construction materials have been developed, particularly natural and bio-based systems, recycled and waste-derived materials, low-carbon cementitious binders, and emerging multifunctional composites. However, research remains fragmented across material classes and performance metrics. This systematic review evaluates advances published between 2018 and 2026 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 methodology. Peer-reviewed studies were systematically identified and analyzed to compare mechanical performance, durability, embodied carbon reduction, and life-cycle environmental impacts across these selected material pathways. The results indicate substantial decarbonization potential. Low-carbon cementitious materials report CO₂ reductions of approximately 10–75% relative to conventional systems, while engineered timber and bamboo demonstrate 28–70% lower carbon footprints due to reduced embodied energy and biogenic carbon storage. Recycled aggregates and industrial by-products enhance circularity but remain sensitive to transport distance and processing intensity. Trade-offs between mechanical capacity and environmental performance are evident in lightweight and bio-based systems. Overall, sustainability gains are maximized through integrated hybrid construction strategies rather than isolated material substitution. This review provides a comparative evidence-based synthesis and identifies key research gaps and implementation challenges for accelerating low-carbon construction. Full article

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

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29 pages, 11291 KB

Open AccessArticle

A State-of-the-Art Engineering Synthesis of Port Pavement Infrastructure Systems

by Christina N. Tsaimou and Vasiliki K. Tsoukala

Infrastructures 2026, 11(5), 157; https://doi.org/10.3390/infrastructures11050157 - 1 May 2026

Viewed by 343

Abstract

Ports are complex infrastructure systems operating under adverse marine environments, diverse loading regimes, and significant economic pressures. Among their critical assets are pavement infrastructures that serve multiple functional domains, including container handling and storage areas, internal circulation corridors, passenger–vehicle interfaces, and auxiliary parking [...] Read more.

Ports are complex infrastructure systems operating under adverse marine environments, diverse loading regimes, and significant economic pressures. Among their critical assets are pavement infrastructures that serve multiple functional domains, including container handling and storage areas, internal circulation corridors, passenger–vehicle interfaces, and auxiliary parking zones. However, existing port pavement research remains predominantly concentrated on heavy-duty container applications, while other functional categories are comparatively underexplored. This study develops a structured engineering synthesis of port pavement infrastructure assets by integrating bibliometric mapping, conducted using Scopus-indexed publications, with a functional–structural analysis of worldwide practices. Following the identification of research trends, additional insights from engineering-oriented studies and technical guidance documents were incorporated to strengthen the practical relevance of the investigation. These findings indicate that functional classification should precede structural design decisions, enabling the systematic identification of loading conditions, serviceability requirements, and transition demands across port environments. Heavy-duty operational zones require high-stiffness systems capable of resisting concentrated and repetitive loads, while circulation areas are particularly sensitive to low-speed traffic effects. In contrast, passenger and mixed-use zones necessitate hybrid design strategies that balance structural adequacy with serviceability and long-term durability under marine exposure, whereas auxiliary areas are primarily governed by cost-efficiency and maintenance considerations. The overall research provides a rational basis for investment prioritization, material selection, lifecycle planning, and performance-based pavement management within multifunctional port environments. Full article

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24 pages, 21710 KB

Open AccessArticle

Adobe Walls Subjected to Monotonic In-Plane Loading: Effect of Moisture, Fiber Type, and Openings

by Eduardo Dávila, Brad D. Weldon, Paola Bandini, Michael J. McGinnis and Brittany K. Bullard

Infrastructures 2026, 11(5), 156; https://doi.org/10.3390/infrastructures11050156 - 30 Apr 2026

Viewed by 457

Abstract

This study tested quarter-scale adobe masonry walls under monotonic in-plane loading, considering the effect of water content at the foundation–wall interface, fiber type, and openings (i.e., door, window). Seven walls were constructed with unstabilized adobe bricks containing either cut straw or sisal fibers [...] Read more.

This study tested quarter-scale adobe masonry walls under monotonic in-plane loading, considering the effect of water content at the foundation–wall interface, fiber type, and openings (i.e., door, window). Seven walls were constructed with unstabilized adobe bricks containing either cut straw or sisal fibers and mud mortar. Gravimetric water content (w_b) at the foundation–wall interface (i.e., wall base) varied by test wall, ranging from 2.4 to 4.9% by dry mass. The walls were instrumented to measure in-plane and out-of-plane displacements and vertical deflections during the load tests. Greater water contents at and near the wall base shifted cracking toward the lower courses and along the foundation–wall interface; however, the peak load capacity did not vary significantly with w_b but was strongly influenced by crack trajectory, including whether cracking diverted into the foundation or propagated rapidly along the foundation–wall interface. Peak loads ranged from 1928 N (433 lb) to 6517 N (1465 lb). Fiber type influenced deformation behavior of the walls, with sisal-brick walls generally developing larger vertical deflections and, in some instances, larger peak in-plane displacements than straw-brick walls. Window and door openings altered crack initiation and propagation by concentrating cracking at opening corners and producing segmented mechanisms, increasing in-plane displacements in some cases, but still sustaining comparatively large peak loads. Full article

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16 pages, 3976 KB

Open AccessArticle

Physics-Based Energy Modeling and Electrification Scenarios for Bus Transit Systems: Evidence from Real-World Data

by Sofia Borgosano, Andrea Di Martino and Michela Longo

Infrastructures 2026, 11(5), 155; https://doi.org/10.3390/infrastructures11050155 - 29 Apr 2026

Viewed by 331

Abstract

The decarbonization of urban public transport requires robust tools to evaluate the operational feasibility and energy implications of bus electrification. This study presents a physics-based modeling framework for estimating the energy consumption of urban bus operations using real-world telemetry data. GPS measurements collected [...] Read more.

The decarbonization of urban public transport requires robust tools to evaluate the operational feasibility and energy implications of bus electrification. This study presents a physics-based modeling framework for estimating the energy consumption of urban bus operations using real-world telemetry data. GPS measurements collected onboard operating buses are used to reconstruct vehicle speed profiles and driving dynamics. The methodology is applied to a representative urban bus route operating in the city centre of Milan, characterized by dense traffic, closely spaced stops, and a high density of signalized intersections. Two operational improvement scenarios are investigated: traffic signal coordination through a “green wave” strategy and the integration of opportunity flash charging (OC) at selected stops. The results show that reducing traffic-related stops improves commercial speed and decreases energy demand, while OC can support battery operation within the constraints of urban service conditions. The proposed framework provides a transferable decision-support methodology for transit agencies planning the electrification of urban bus services and the deployment of supporting infrastructure. Full article

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

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28 pages, 31083 KB

Open AccessArticle

Mechanistic Interpretation of Field-Measured Pavement Response Under Heavy-Vehicle Loading

by Suphawut Malaikrisanachalee, Auckpath Sawangsuriya, Phansak Sattayhatewa, Ponlathep Lertworawanich, Apiniti Jotisankasa, Susit Chaiprakaikeow and Narongrit Wongwai

Infrastructures 2026, 11(5), 154; https://doi.org/10.3390/infrastructures11050154 - 29 Apr 2026

Viewed by 513

Abstract

This study presents a data-driven framework for the mechanistic interpretation of asphalt pavement responses using an integrated smart sensing and monitoring system deployed on a national highway in Thailand. A fully instrumented pavement test section was developed, incorporating a multi-sensor embedded network and [...] Read more.

This study presents a data-driven framework for the mechanistic interpretation of asphalt pavement responses using an integrated smart sensing and monitoring system deployed on a national highway in Thailand. A fully instrumented pavement test section was developed, incorporating a multi-sensor embedded network and a field data acquisition platform integrated with weigh-in-motion (WIM) technology. The system consists of 54 sensors, including strain gauges, pressure cells, moisture sensors, and thermocouples, installed at multiple depths to capture high-resolution stress–strain responses under controlled heavy-vehicle loading. Field measurements were analyzed and compared with classical mechanistic models, including Boussinesq’s theory, Odemark’s equivalent thickness method, and Burmister’s multilayer elastic theory. The results demonstrate good agreement for vertical stress predictions in deeper layers, while significant discrepancies were observed in strain responses, particularly in the asphalt layer, where measured tensile strains were up to 2.5 times higher than theoretical estimates. The findings indicate that conventional elastic models provide useful first-order approximations; however, discrepancies were observed in representing the viscoelastic behavior of asphalt materials under real loading conditions. Furthermore, the integration of sensor data with traffic loading information confirms that axle load magnitude is the dominant factor governing pavement responses, whereas vehicle speed primarily influences load duration. The proposed framework demonstrates the potential of smart sensing systems for enabling automated, data-driven pavement analysis and supporting digital twin-based infrastructure management. Full article

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34 pages, 6638 KB

Open AccessArticle

Ternary Gypsum–Cement–Pozzolanic Compositions for 3D Printing: Mix Design, Rheology and Long-Term Performance

by Genadijs Sahmenko, Girts Bumanis, Maris Sinka, Peteris Slosbergs, Alise Sapata, Diana Bajare and Vjaceslavs Lapkovskis

Infrastructures 2026, 11(5), 153; https://doi.org/10.3390/infrastructures11050153 - 28 Apr 2026

Viewed by 334

Abstract

Ternary gypsum–cement–pozzolan (GCP) binders represent a promising low-carbon alternative to traditional Portland cement-based systems for additive 3D printing (3DP). This study presents a systematic three-stage experimental framework for the development of printable and durable GCP mixtures: (i) optimisation of gypsum–cement–metakaolin binder proportions based [...] Read more.

Ternary gypsum–cement–pozzolan (GCP) binders represent a promising low-carbon alternative to traditional Portland cement-based systems for additive 3D printing (3DP). This study presents a systematic three-stage experimental framework for the development of printable and durable GCP mixtures: (i) optimisation of gypsum–cement–metakaolin binder proportions based on a ternary diagram for 25 formulations, (ii) comparative evaluation of different pozzolanic additives and secondary gypsum sources alongside comprehensive durability testing, and (iii) adaptation of the optimised mixtures for 3DP, focusing on rheological properties. The optimal composition was determined with 55 wt% gypsum, 22.5 wt% Portland cement, and 22.5 wt% metakaolin, achieving a 28-day wet compressive strength of 36.2 MPa and a softening coefficient of 0.85. Successful integration of secondary gypsum sources was demonstrated. The GCP 3DP mixtures were developed with water/binder ratios of 0.38–0.45 and sand/binder ratios of 0.5–1.4, with an open time of 20–40 min. The mixtures exhibit pronounced thixotropic behaviour, characterised by increasing yield stress over time and relatively stable plastic viscosity. Printability tests confirmed the stable application of 29–39 layers before structural buckling. 3DP under laboratory conditions successfully demonstrated the feasibility of producing architectural and structural elements from sustainable GCP compositions. Full article

(This article belongs to the Special Issue Recent Advances in Enhancing Sustainability and Durability of Cement and Concrete)

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54 pages, 16571 KB

Open AccessArticle

A Counterfactual AI-Based System for Spatio-Temporal Traffic Risk Prediction and Intelligent Safety Intervention in Smart Transportation Systems

by Nawal Louzi, Areen M. Arabiat and Mahmoud AlJamal

Infrastructures 2026, 11(5), 152; https://doi.org/10.3390/infrastructures11050152 - 28 Apr 2026

Viewed by 299

Abstract

This paper presents a novel system-oriented counterfactual deep learning framework, termed Hybrid Prediction–Intervention Neural Architecture (HPINA) for intelligent traffic accident risk prediction and proactive safety intervention in smart transportation systems. Unlike conventional data-driven models that rely solely on observational correlations, the proposed system [...] Read more.

This paper presents a novel system-oriented counterfactual deep learning framework, termed Hybrid Prediction–Intervention Neural Architecture (HPINA) for intelligent traffic accident risk prediction and proactive safety intervention in smart transportation systems. Unlike conventional data-driven models that rely solely on observational correlations, the proposed system integrates multi-domain data fusion, temporal deep representation learning, a continuous spatio-temporal risk field, and a latent-space counterfactual reasoning module within a unified decision-support architecture. The framework enables accurate prediction of traffic accident risk and simulation of “what-if” intervention scenarios to support real-time safety optimization in intelligent transportation environments. By leveraging heterogeneous inputs, including traffic dynamics, environmental conditions, road attributes, and temporal patterns, the system constructs a high-dimensional representation that captures complex nonlinear dependencies and evolving risk propagation across the network. A key innovation lies in the integration of a causal intervention mechanism and policy-guided decision layer, which jointly quantify intervention impact and identify optimal strategies for minimizing risk. The experimental results demonstrate that HPINA achieves a Test F1-score of 0.958 and an AUC of 0.989, outperforming strong baselines by up to 5.0% and 3.4%, while achieving a relative risk reduction of 0.091 and improved convergence stability with a validation loss of 0.042. These findings highlight the effectiveness of the proposed framework as an intelligent, scalable, and deployable system for real-world traffic safety management and smart city applications. Full article

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31 pages, 4674 KB

Open AccessArticle

Deep Learning-Based Prediction of the Axial Capacity of CFRP-Strengthened Concrete Columns

by Nasim Shakouri Mahmoudabadi, Charles V. Camp and Afaq Ahmad

Infrastructures 2026, 11(5), 151; https://doi.org/10.3390/infrastructures11050151 - 28 Apr 2026

Viewed by 428

Abstract

Fiber-reinforced polymer (FRP) composites are widely used to strengthen reinforced concrete (RC) columns due to their high strength, durability, and ease of installation. Accurate prediction of the axial capacity of CFRP-strengthened concrete columns is essential for reliable structural design. Yet conventional empirical models [...] Read more.

Fiber-reinforced polymer (FRP) composites are widely used to strengthen reinforced concrete (RC) columns due to their high strength, durability, and ease of installation. Accurate prediction of the axial capacity of CFRP-strengthened concrete columns is essential for reliable structural design. Yet conventional empirical models often exhibit limited accuracy due to the complex interactions among structural parameters. This study develops a deep learning-based model to predict the axial capacity of CFRP-wrapped RC columns using a database of 469 experimental tests collected from published studies. A deep neural network (DNN) was optimized using the Optuna hyperparameter tuning framework and k-fold cross-validation to enhance model accuracy and robustness. Model performance was evaluated using statistical indicators, including R², RMSE, MAE, MAPE, and the a20-index. The results show excellent predictive performance with R² values approaching 0.99 and an a20-index of 0.98, demonstrating strong agreement between predicted and experimental results. Comparisons with the ACI 440.2R-17 and CSA S806-12 design codes indicate that the proposed DNN model provides significantly improved prediction accuracy, with lower errors. The developed approach offers a reliable and efficient tool for estimating the axial capacity of CFRP-strengthened concrete columns. Full article

(This article belongs to the Topic Advances in Structural Engineering Using AI and Sustainable Materials)

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