Journal Description
Infrastructures
Infrastructures
is an international, scientific, peer-reviewed open access journal on infrastructures published monthly online by MDPI. The journal collaborates with the Spanish Road Technology Platform /Plataforma Tecnológica Española de la Carretera (PTC). Infrastructures is affiliated to International Society for Maintenance and Rehabilitation of Transport Infrastructures (iSMARTi) and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), Inspec, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Civil) / CiteScore - Q1 (Building and Construction)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.8 days after submission; acceptance to publication is undertaken in 3.7 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.7 (2023);
5-Year Impact Factor:
2.8 (2023)
Latest Articles
Damage Detection in External Tendons of Post-Tensioned Bridges
Infrastructures 2024, 9(7), 103; https://doi.org/10.3390/infrastructures9070103 (registering DOI) - 30 Jun 2024
Abstract
This study investigates damage detection in the tendons of post-tensioned segmental box girder bridges, focusing on the vibration-based technique and its application in conjunction with the Precursor Transformation Matrix (PTM). Due to the critical role of bridge tendons in structural integrity, efficient and
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This study investigates damage detection in the tendons of post-tensioned segmental box girder bridges, focusing on the vibration-based technique and its application in conjunction with the Precursor Transformation Matrix (PTM). Due to the critical role of bridge tendons in structural integrity, efficient and timely detection methods are essential. The methodology combines theoretical modeling with Finite Element Method (FEM) simulations and empirical data collection to evaluate the PTM’s effectiveness in identifying tendon damage. Key results indicate that the PTM, when paired with vibration analysis, enhances the identification and localization of damage, proving to be a robust method in structural health monitoring. This approach not only speeds up damage detection but also potentially lowers maintenance costs by pinpointing specific damage sites, thereby preventing widespread structural failures. The findings offer a promising tool for ensuring the longevity and safety of post-tensioned bridges.
Full article
(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)
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Open AccessArticle
An Analysis of the Development Factors of Rail Freight Transport in Thailand: A Structural Equation Modeling Approach
by
Oranicha Buthphorm, Vatcharapol Sukhotu and Thammanoon Hengsadeekul
Infrastructures 2024, 9(7), 102; https://doi.org/10.3390/infrastructures9070102 (registering DOI) - 30 Jun 2024
Abstract
The railway infrastructure projects in Thailand aim to shift transportation from roads to railways. This is crucial for transporting goods in emerging economies and increasing the demand for rail freight transport. However, several dynamic uncertainties hinder sustainable rail freight transport in Thailand. This
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The railway infrastructure projects in Thailand aim to shift transportation from roads to railways. This is crucial for transporting goods in emerging economies and increasing the demand for rail freight transport. However, several dynamic uncertainties hinder sustainable rail freight transport in Thailand. This study aims to identify the key factors and validate their effects on the success of the modal shift from roads to railways in Thailand. A total of 200 participants filled out a questionnaire delivered online and via postal service. The key factors were categorized into the following categories: the rail freight transport system, demand, and development factors in Thailand. The inter-relationship and connection of these factors were analyzed using SEM (structural equation modeling). The SEM results showed that all causal factors in the model had a positive influence on rail freight development in Thailand, which explained 98.3% of the variance in the factors influencing development. This study’s findings underscore the influential significance of rail performance, rail infrastructure, the legal framework, pricing, mode choice, and technology on the expansion of rail freight transport in Thailand. The rail freight transport system, rail performance, rail infrastructure, and Thailand’s rail infrastructure development strategy were significant direct predictors of rail freight expansion. An expansion of the rail freight transport system also leads to rail freight demand. The results of this study have positive implications for the government, railway practitioners, and policymakers to prioritize their focus on achieving rail freight transport as the national target.
Full article
(This article belongs to the Section Sustainable Infrastructures)
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Open AccessArticle
Develo** Pavement Maintenance Strategies and Implementing Management Systems
by
Li-Ling Huang, Jyh-Dong Lin, Wei-Hsing Huang, Chun-Hung Kuo, Yi-Shian Chiou and Mao-Yuan Huang
Infrastructures 2024, 9(7), 101; https://doi.org/10.3390/infrastructures9070101 - 27 Jun 2024
Abstract
The traffic volume and maintenance demand on Taiwan’s provincial highways have been steadily increasing. One of the most challenging issues in maintenance is determining the optimal timing and allocation of funds to avoid duplicative investments and maximize resource utilization. Currently, provincial highway maintenance
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The traffic volume and maintenance demand on Taiwan’s provincial highways have been steadily increasing. One of the most challenging issues in maintenance is determining the optimal timing and allocation of funds to avoid duplicative investments and maximize resource utilization. Currently, provincial highway maintenance units rely heavily on manual processes and paper-based records, using experiential methods to formulate maintenance strategies and conduct maintenance operations. This indicates a lack of objective maintenance strategies and pavement management systems in these units. This study aims to address this gap by integrating domestic and international literature on pavement maintenance decision-making. Existing approaches typically fall into two categories: “Pavement Indicator Rating” and “Pavement Maintenance Prioritization”. However, there has not been research integrating these methods for decision-making. Therefore, this research integrates these two approaches to establish a comprehensive maintenance strategy for Taiwan’s provincial highways. The Analytic Hierarchy Process (AHP) is employed as the decision-making theory, involving expert interviews to calculate maintenance weights for different pavement maintenance indicators. The results show that the pothole count, International Roughness Index (IRI), and Pavement Condition Index (PCI) are the three most critical maintenance indicators. The first phase of the maintenance strategy uses the “Pavement Indicator Rating“ to directly assess the pothole count, IRI, and PCI to categorize pavement sections as “maintenance sections” or “observation sections”. The second phase employs “Pavement Maintenance Prioritization”, integrating maintenance weights for each indicator to calculate maintenance scores. This phase prioritizes maintenance activities based on the results of the first phase’s rating for “maintenance sections”. Additionally, a provincial highway pavement management system is proposed to implement these strategies, enhancing maintenance management efficiency and ensuring the overall quality and longevity of provincial highway maintenance efforts.
Full article
(This article belongs to the Special Issue Road Systems and Engineering)
Open AccessArticle
Optimization Models for the Maintenance Management of Tropical Paved and Unpaved Roads
by
Taciano Oliveira da Silva, Heraldo Nunes Pitanga, Emerson Cordeiro Lopes, Laura Carine Pereira Ribeiro, Gustavo Henrique Nalon, Klaus Henrique de Paula Rodrigues, José Carlos Lopes Ribeiro and Khaled Ksaibati
Infrastructures 2024, 9(7), 100; https://doi.org/10.3390/infrastructures9070100 - 27 Jun 2024
Abstract
The degradation of paved and unpaved roads stands as a critical concern in contemporary infrastructure management. When faced with limited budgets, it is important to identify the optimal combination of road preservation strategies to minimize the lifecycle cost of the road network. Specific
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The degradation of paved and unpaved roads stands as a critical concern in contemporary infrastructure management. When faced with limited budgets, it is important to identify the optimal combination of road preservation strategies to minimize the lifecycle cost of the road network. Specific studies are necessary to improve the maintenance management systems and analyze the behavior of road surface deformation. To narrow these knowledge gaps, this study investigates a management system that focuses on the application of optimization techniques for managing both paved and unpaved tropical roads. Probabilistic deterioration models were constructed using the Markovian process, resulting in precise degradation curves in the context of 18 unpaved road segments in the Zona da Mata County of Minas Gerais (Brazil), along with 88 paved roads located in Minas Gerais. An optimization algorithm was proposed for the prediction of maintenance resources for unpaved and paved roads, emphasizing the cost-effectiveness of preventive and minor rehabilitation treatments over reconstruction. Comparisons between the maintenance costs of unpaved and paved roads indicated that the full rehabilitation costs of paved roads were approximately 10 times higher per kilometer compared to those of unpaved roads. The models effectively captured the trend wherein a major treatment leads to minor additional treatments being necessary for the subsequent several years in both scenarios. The findings of this study provide future directions for the optimized allocation of resources in the management of transportation infrastructures.
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)
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Open AccessArticle
Fatigue Consideration for Tension Flange over Intermediate Support in Skewed Continuous Steel I-Girder Bridges
by
Dariya Tabiatnejad, Seyed Saman Khedmatgozar Dolati, Armin Mehrabi and Todd A. Helwig
Infrastructures 2024, 9(7), 99; https://doi.org/10.3390/infrastructures9070099 - 26 Jun 2024
Abstract
Skewed supports complicate load paths in continuous steel I-girder bridges, causing secondary stresses and differential deformations. For a continuous bridge where tensile stresses are developed in the top flange of the steel girders over the intermediate supports, these effects may exacerbate potential fatigue
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Skewed supports complicate load paths in continuous steel I-girder bridges, causing secondary stresses and differential deformations. For a continuous bridge where tensile stresses are developed in the top flange of the steel girders over the intermediate supports, these effects may exacerbate potential fatigue issues for the top flanges. There is a gap in knowledge regarding the level of stress one can expect at these locations, and the stress level can render the problem either serious or trivial. This paper has been successful in providing this information, which was not available before. The study examines the fatigue performance of the top flange in girders over skewed supports. Results are presented from a detailed investigation consisting of 3D finite element modeling to evaluate 26 skewed bridges in the State of Florida that represent the wide range of geometries found in practice. The analysis focused on stress ranges in the top flanges and axial demands on end cross-frame members under fatigue truck loading. A preliminary analysis helped to select the appropriate element type and support conditions. The maximum factored stress range of 3.63 ksi obtained for the selected group of bridges remains below the 10 ksi fatigue threshold for an AASHTO Category C connection, alleviating the concerns about the fatigue performance of the continuous girder top flange over the intermediate pier. Hence, fatigue is unlikely to be a concern in the flanges at this location. Statistics on computed stress ranges and cross-frame forces that provide an understanding of the expected values and guidance for detailing practices are also presented. A limited comparative refined FE analysis on two different types of end cross-frame to girder connections also provided useful insight into the fatigue sensitivities of the skew connections. Half-Round Bearing Stiffener (HRBS) connections performed better than the customary bent plate connections. The HRBS connection reduces girder flange stress concentration range by at least 18% compared to the bent plate connection. The maximum stress concentration range in bent plate components is significantly higher than in the HRBS connection components. The work documented in this paper is important for understanding the fatigue performance of the cross-frames and girders in support regions in the upcoming 10th edition of the AASHTO Bridge Design Specifications that may include plate stiffeners oriented either normally or skewed to the girder web, or Half-Round Bearing Stiffeners.
Full article
(This article belongs to the Special Issue Advances in Steel and Composite Steel–Concrete Bridges and Buildings)
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Open AccessReview
Building Information Modelling in Hydropower Infrastructures: Design, Engineering and Management Perspectives
by
Jigme Wangchuk, Saeed Banihashemi, Hamidreza Abbasianjahromi and Maxwell Fordjour Antwi-Afari
Infrastructures 2024, 9(7), 98; https://doi.org/10.3390/infrastructures9070098 - 25 Jun 2024
Abstract
Abstract: Building Information Modelling (BIM) has emerged as a transformative force in the construction industry, gaining traction within the hydropower sector. This study critically examines the adoption and application of BIM throughout the entire lifecycle of hydropower projects, addressing a notable gap in
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Abstract: Building Information Modelling (BIM) has emerged as a transformative force in the construction industry, gaining traction within the hydropower sector. This study critically examines the adoption and application of BIM throughout the entire lifecycle of hydropower projects, addressing a notable gap in existing research, to encompass a holistic approach to the management and resilience of these critical infrastructures. The objective is to delineate the comprehensive range of BIM applications, use cases, and adoption, integrating technologies including Digital Twin, UAV, GIS, and simulation tools, across components of hydropower projects. Employing a systematic search paired with a critical review of the selected literature, this study meticulously evaluates significant contributions in this domain. Through thematic analysis, the multifaceted utility of BIM in hydropower structures, including an in-depth evaluation of its current adoption within the industry, is presented. This encompasses an analysis of both benefits and challenges inherent in BIM implementation for hydropower infrastructures. This study is a significant contribution to understanding how BIM can be leveraged to enhance the resilience of hydropower infrastructures. It provides a comprehensive view of BIM’s applications, challenges, and future potential, guiding stakeholders in adopting strategies that ensure these structures withstand, adapt, and recover from disruptions while maintaining sustainable and efficient operations.
Full article
(This article belongs to the Special Issue Smart Construction in Infrastructure Project Development)
Open AccessArticle
Improved Blob-Based Feature Detection and Refined Matching Algorithms for Seismic Structural Health Monitoring of Bridges Using a Vision-Based Sensor System
by
Luna Ngeljaratan, Mohamed A. Moustafa, Agung Sumarno, Agus Mudo Prasetyo, Dany Perwita Sari and Maidina Maidina
Infrastructures 2024, 9(6), 97; https://doi.org/10.3390/infrastructures9060097 - 14 Jun 2024
Abstract
The condition and hazard monitoring of bridges play important roles in ensuring their service continuity not only throughout their entire lifespan but also under extreme conditions such as those of earthquakes. Advanced structural health monitoring (SHM) systems using vision-based technology, such as surveillance,
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The condition and hazard monitoring of bridges play important roles in ensuring their service continuity not only throughout their entire lifespan but also under extreme conditions such as those of earthquakes. Advanced structural health monitoring (SHM) systems using vision-based technology, such as surveillance, traffic, or drone cameras, may assist in preventing future impacts due to structural deficiency and are critical to the emergence of sustainable and smart transportation infrastructure. This study evaluates several feature detection and tracking algorithms and implements them in the vision-based SHM of bridges along with their systematic procedures. The proposed procedures are implemented via a two-span accelerated bridge construction (ABC) system undergoing a large-scale shake-table test. The research objectives are to explore the effect of refined matching algorithms on blob-based features in improving their accuracies and to implement the proposed algorithms on large-scale bridges tested under seismic loads using vision-based SHM. The procedure begins by adopting blob-based feature detectors, i.e., the scale-invariant feature transform (SIFT), speeded-up robust features (SURF), and KAZE algorithms, and their stability is compared. The least medium square (LMEDS), least trimmed square (LTS), random sample consensus (RANSAC), and its generalization maximum sample consensus (MSAC) algorithms are applied for model fitting, and their sensitivity for removing outliers is analyzed. The raw data are corrected using mathematical models and scaled to generate displacement data. Finally, seismic vibrations of the bridge are generated, and the seismic responses are compared. The data are validated using target-tracking methods and mechanical sensors, i.e., string potentiometers. The results show a good agreement between the proposed blob feature detection and matching algorithms and target-tracking data and reference data obtained using mechanical sensors.
Full article
(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)
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Open AccessArticle
Mass and Stiffness Correlation Using a Transformation Matrix
by
Natalia García Fernández, Pelayo Fernández Fernandez, Rune Brincker and Manuel Aenlle López
Infrastructures 2024, 9(6), 96; https://doi.org/10.3390/infrastructures9060096 - 13 Jun 2024
Abstract
Model correlation techniques are methods used to compare two different models, usually a numerical model and an experimental model. According to the structural dynamic modification theory, the experimental mode shapes estimated by modal analysis can be expressed as a linear combination of the
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Model correlation techniques are methods used to compare two different models, usually a numerical model and an experimental model. According to the structural dynamic modification theory, the experimental mode shapes estimated by modal analysis can be expressed as a linear combination of the numerical mode shapes through a transformation matrix . In this paper, matrix is proposed as a novel model correlation technique to detect discrepancies between the numerical and the experimental models in terms of mass. The discrepancies in stiffness can be identified by combining the numerical natural frequencies and the matrix . This methodology can be applied to correlate the numerical and experimental results of civil (bridges, dams, towers, buildings, etc.), aerospace and mechanical structures and to detect damage when using structural health monitoring techniques. The technique was validated by numerical simulations on a lab-scaled two-span bridge considering different degradation scenarios and experimentally on a lab-scaled structure, which was correlated with two numerical models.
Full article
(This article belongs to the Special Issue Sustainable Practices in Bridge Construction)
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Open AccessArticle
Flexible Permeable-Pavement System Sustainability: A Methodology for Stormwater Management Based on PM Granulometry
by
Vittorio Ranieri, Stefano Coropulis, Veronica Fedele, Paolo Intini and John Joseph Sansalone
Infrastructures 2024, 9(6), 95; https://doi.org/10.3390/infrastructures9060095 - 11 Jun 2024
Abstract
Permeable-pavement design methodologies can improve the hydrologic and therefore the environmental benefits of rural and urban roadway systems. By contrast, conventional impervious pavements perturb the hydrologic cycle, altering the relationship between the rainfall loading and runoff response. Impervious pavements create a hydraulically conductive
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Permeable-pavement design methodologies can improve the hydrologic and therefore the environmental benefits of rural and urban roadway systems. By contrast, conventional impervious pavements perturb the hydrologic cycle, altering the relationship between the rainfall loading and runoff response. Impervious pavements create a hydraulically conductive interface for the transport of traffic-generated chemicals and particulate matter (PM), deleteriously impacting their proximate environments. Permeable-pavement systems are countermeasures to mitigate hydrologic, chemical, and PM impacts. However, permeable pavements are not always equally implementable due to costs, PM loadings, and design constraints. A potential solution to facilitate environmental benefits while meeting the traffic load capacity is the combination of two filtration systems placed at the pavement shoulders and/or pedestrian sidewalks: a bituminous-pavement open-graded friction course (BPFC) and an aggregate-filled infiltration trench. This solution is presented in this manuscript together with the methodological framework and the first results of the investigations into designing and validating such a combined system. The research was conducted at the laboratories of the Polytechnic University of Bari and the University of Florida, while an operational and full-scale physical model was constructed in Bari, Italy. The first results presented characterize the PM deposition on public roads based on granulometry (particle size distributions (PSDs) and particle number densities (PNDs)). Samples (n = 16) were collected and analyzed at eight different sites with different land uses, traffic, and pavements from different cities (Bari and Taranto, Italy). The PM analysis showed similar distributions (PSDs and PNDs), except for two samples. The gravimetric-based PSDs of the PM had granulometric distributions in the sand-size range. In contrast, the PNDs, modeled by a Power Law Model (PLM) (R2 ≥ 0.92), illustrated an exponentially increasing number of particles in the fine silt and clay-size range, representing less than 10% of the PSD mass. Moreover, the results indicate that PM sourced from permeable-pavement systems has differing impacts on the pavement service life.
Full article
(This article belongs to the Special Issue Emerging Technologies for Effective and Intelligent Transport Infrastructure Monitoring)
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Open AccessReview
An Overview of Methods to Enhance the Environmental Performance of Cement-Based Materials
by
Daniel Suarez-Riera, Luciana Restuccia, Devid Falliano, Giuseppe Andrea Ferro, Jean-Marc Tuliani, Matteo Pavese and Luca Lavagna
Infrastructures 2024, 9(6), 94; https://doi.org/10.3390/infrastructures9060094 - 11 Jun 2024
Abstract
Urbanization and demographic growth have led to increased global energy consumption in recent years. Furthermore, construction products and materials industries have contributed significantly to this increase in fossil fuel use, due to their significant energy requirements, and consequent environmental impact, during the extraction
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Urbanization and demographic growth have led to increased global energy consumption in recent years. Furthermore, construction products and materials industries have contributed significantly to this increase in fossil fuel use, due to their significant energy requirements, and consequent environmental impact, during the extraction and processing of raw materials. To address this environmental problem, architectural design and civil engineering are trying to implement strategies that enable the use of high-performance materials while minimizing the usage of energy-intensive or toxic and dangerous building materials. These efforts also aim to make buildings less energy-consuming during their useful life. Using waste materials, such as Construction and Demolition Waste (CdW), is one of the most promising approaches to address this issue. In recent years, the European Union (EU) has supported recovery strategies focused on using CdW, as they account for more than 30% of the total waste production in the EU. In this regard, reuse techniques—such as incorporating concrete fragments and bricks as road floor fillers—have been the subject of targeted scientific research. This review will outline various strategies for producing green cement and concrete, particularly emphasizing the reuse of Construction and Demolition Waste (CdW).
Full article
(This article belongs to the Special Issue Innovative Solutions for Concrete Applications)
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Open AccessArticle
Bond Stress Behavior of a Steel Reinforcing Bar Embedded in Geopolymer Concrete Incorporating Natural and Recycled Aggregates
by
Qasim Shaukat Khan, Haroon Akbar, Asad Ullah Qazi, Syed Minhaj Saleem Kazmi and Muhammad Junaid Munir
Infrastructures 2024, 9(6), 93; https://doi.org/10.3390/infrastructures9060093 - 31 May 2024
Abstract
The rise in greenhouse gases, particularly carbon dioxide (CO2) emissions, in the atmosphere is one of the major causes of global warming and climate change. The production of ordinary Portland cement (OPC) emits harmful CO2 gases, which contribute to sporadic
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The rise in greenhouse gases, particularly carbon dioxide (CO2) emissions, in the atmosphere is one of the major causes of global warming and climate change. The production of ordinary Portland cement (OPC) emits harmful CO2 gases, which contribute to sporadic heatwaves, rapid melting of glaciers, flash flooding, and food shortages. To address global warming and climate change challenges, this research study explores the use of a cement-less recycled aggregate concrete, a sustainable approach for future constructions. This study uses fly ash, an industrial waste of coal power plants, as a 100% substitute for OPC. Moreover, this research study also uses recycled coarse aggregates (RCAs) as a partial to complete replacement for natural coarse aggregates (NCAs) to preserve natural resources for future generations. In this research investigation, a total of 60 pull-out specimens were prepared to investigate the influence of steel bar diameter (9.5 mm, 12.7 mm, and 19.1 mm), bar embedment length, (4 and 6 ), and percentage replacements of NCA with RCA (25%, 50%, 75%, and 100%) on the bond stress behavior of cement-less RA concrete. The test results exhibited that the bond stress of cement-less RCA concrete decreased by 6% with increasing steel bar diameter. Moreover, the bond stress decreased by 5.5% with increasing bar embedment length. Furthermore, the bond stress decreased by 7.6%, 7%, 8.8%, and 20.4%, respectively, with increasing percentage replacements (25%, 50%, 75%, and 100%) of NCA with RCA. An empirical model was developed correlating the bond strength to the mean compressive strength of cement-less RCA concrete, which matched well with the experimental test results and predictions of the CEB-FIP model for OPC. The CRAC mixes exhibited higher costs but significantly lower embodied CO2 emissions than OPC concrete.
Full article
(This article belongs to the Special Issue Advances in Steel and Composite Steel–Concrete Bridges and Buildings)
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Open AccessArticle
Using Multiple Machine Learning Models to Predict the Strength of UHPC Mixes with Various FA Percentages
by
Hussam Safieh, Rami A. Hawileh, Maha Assad, Rawan Hajjar, Sayan Kumar Shaw and Jamal Abdalla
Infrastructures 2024, 9(6), 92; https://doi.org/10.3390/infrastructures9060092 - 28 May 2024
Abstract
Ultra High-Performance Concrete (UHPC) has shown extraordinary performance in terms of strength and durability. However, having a cost-effective and sustainable UHPC mix design is a challenge in the construction sector. This study aims on building a predictable model that can help in determining
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Ultra High-Performance Concrete (UHPC) has shown extraordinary performance in terms of strength and durability. However, having a cost-effective and sustainable UHPC mix design is a challenge in the construction sector. This study aims on building a predictable model that can help in determining the compressive strength of UHPC. The research focuses on applying multiple machine learning (ML) models and evaluating their performance in predicting the strength prediction of UHPC. Two reliable metrics are used to evaluate the performance of the model which are the coefficient of determination and mean squared error (MSE). The parameters that are affecting the compressive strength of UHPC are fly ash percentage levels (FA%), superplasticizer content, water to binder ratio (w/b), and curing period. A total of 54 ML models were used, consisting of Linear Regression, Support Vector Machines (SVM), Neural Networks, and Random forests algorithms. Among these models, Random Forest proved to be the most effective in capturing the relationships in UHPC’s behaviour with an R squared score of 0.8857. The Random Forest ML model is also used in this paper to conduct a parametric study that will help in obtaining the compressive strength of UHPC with higher content of FA%, which is not sufficiently studied in the literature.
Full article
(This article belongs to the Special Issue Inspection, Assessment, Retrofitting & Strengthening of Civil Infrastructure)
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Open AccessArticle
Experiences Using MEMS Accelerometers on Railway Bearers at Switches and Crossings to Obtain Displacement—Awkward Situations
by
Jou-Yi Shih, Paul Weston, Mani Entezami, Clive Roberts and Mark O’Callaghan
Infrastructures 2024, 9(6), 91; https://doi.org/10.3390/infrastructures9060091 - 28 May 2024
Abstract
A sleeper, or more generally a “bearer”, moves vertically under a passing train load. The extent of this motion depends on the static and dynamic load of the train, the train speed, and the support conditions at the bearer and its neighbours. Excessive
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A sleeper, or more generally a “bearer”, moves vertically under a passing train load. The extent of this motion depends on the static and dynamic load of the train, the train speed, and the support conditions at the bearer and its neighbours. Excessive motion, typically from voiding see-sawing, low support stiffness or possibly excessive stiffness, or even too little stiffness, are all of interest to maintainers. Typically, problems arise around transition zones, switches and crossings, but plain track with poor support can also be a problem. Within the last decade, low-cost micro-electro-mechanical system (MEMS) accelerometers have been used to capture the time history of vertical motion for use in condition monitoring. Existing condition monitoring systems often overlook or sometimes even ignore the possibility of problematic data, which seem to be common in monitored locations. It is essential to understand whether such “bad” data require further attention. Three problematic sites are presented, focussing on examples where the acceleration was higher than expected or the computed displacement was not as expected. Potential causes include wheel defects, hammering of the ballast by a hanging bearer, or high acceleration at some structural resonant frequency. The present paper aims to show the challenges of using MEMS accelerometers to collect data for condition monitoring and offers insights into the sort of problematic data that may be collected from real sites.
Full article
(This article belongs to the Special Issue Emerging Technologies for Effective and Intelligent Transport Infrastructure Monitoring)
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Open AccessReview
Civil Integrated Management (CIM) for Advanced Level Applications to Transportation Infrastructure: A State-of-the-Art Review
by
Ali Taheri and John Sobanjo
Infrastructures 2024, 9(6), 90; https://doi.org/10.3390/infrastructures9060090 - 24 May 2024
Abstract
The recent rise in the applications of advanced technologies in the sustainable design and construction of transportation infrastructure demands an appropriate medium for their integration and utilization. The relatively new concept of Civil Integrated Management (CIM) is such a medium; it enhances the
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The recent rise in the applications of advanced technologies in the sustainable design and construction of transportation infrastructure demands an appropriate medium for their integration and utilization. The relatively new concept of Civil Integrated Management (CIM) is such a medium; it enhances the development of digital twins for infrastructure and also embodies various practices and tools, including the collection, organization, and data-management techniques of digital data for transportation infrastructure projects. This paper presents a comprehensive analysis of advanced CIM tools and technologies and categorizes its findings into the following research topics: application of advanced surveying methods (Advanced Surveying); geospatial analysis tools for project planning (Geospatial Analysis); multidimensional virtual design models (nD Modeling); Integrated Geospatial and Building Information Modeling (GeoBIM); and transportation infrastructure maintenance and rehabilitation planning (Asset Management). Despite challenges such as modeling complexity, technology investment, and data security, the integration of GIS, BIM, and artificial intelligence within asset-management systems hold the potential to improve infrastructure’s structural integrity and long-term performance through automated monitoring, analysis, and predictive maintenance during its lifetime.
Full article
(This article belongs to the Special Issue Recent Progress in Transportation Infrastructures)
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Open AccessArticle
Analysis of Traffic Injury Crash Proportions Using Geographically Weighted Beta Regression
by
Alan Ricardo da Silva and Roberto de Souza Marques Buffone
Infrastructures 2024, 9(6), 89; https://doi.org/10.3390/infrastructures9060089 - 23 May 2024
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The classical linear regression model allows for a continuous quantitative variable to be modeled simply from other variables. However, this model assumes independence between observations, which, if ignored, can lead to methodological issues. Additionally, not all data follow a normal distribution, prompting the
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The classical linear regression model allows for a continuous quantitative variable to be modeled simply from other variables. However, this model assumes independence between observations, which, if ignored, can lead to methodological issues. Additionally, not all data follow a normal distribution, prompting the need for alternative modeling methods. In this context, geographically weighted beta regression (GWBR) incorporates spatial dependence into the modeling process and analyzes rates or proportions using the beta distribution. In this study, GWBR was applied to the traffic injury (fatal and non-fatal) crash proportions in Fortaleza, Ceará, Brazil, from 2009 to 2011. The results demonstrated that the local approach using the beta distribution is a viable model for explaining the traffic injury crash proportions, due to its flexibility in handling both symmetric and skewed distributions. Therefore, when analyzing rates or proportions, the use of the GWBR model is recommended.
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Open AccessArticle
Evaluation of Pigment-Modified Clear Binders and Asphalts: An Approach towards Sustainable, Heat Harvesting, and Non-Black Pavements
by
Gul Badin, Naveed Ahmad, Ying Huang and Yasir Mahmood
Infrastructures 2024, 9(5), 88; https://doi.org/10.3390/infrastructures9050088 - 17 May 2024
Abstract
Pavement construction practices have evolved due to increasing environmental impact and urban heat island (UHI) effects, as pavements, covering over 30% of urban areas, contribute to elevated air temperatures. This study introduces heat-reflective pavements, by replacing conventional black bitumen with a clear binder
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Pavement construction practices have evolved due to increasing environmental impact and urban heat island (UHI) effects, as pavements, covering over 30% of urban areas, contribute to elevated air temperatures. This study introduces heat-reflective pavements, by replacing conventional black bitumen with a clear binder and pigment-modified clear binders. Titanium dioxide white, zinc ferrite yellow, and iron oxide red pigments are used to give asphalt corresponding shades. The asphalt and bitumen specimens were subjected to thermal analysis in heat sinks, under varying solar fluxes. The pigment dosage was maintained at 4%, according to the weight of the total mix, for all pigment types. The samples were heated and cooled for 3 h and 2 h, respectively. Mechanical testing was conducted to ascertain the impact of temperature variations on both the neat clear binder (C.B) and pigmented C.B and asphalt mixture samples. Wheel tracking and dynamic modulus tests were conducted to evaluate their performance under high temperatures. The results indicate that non-black asphalt mixtures exhibit significant temperature reductions, up to 9 °C, which are further enhanced by pigmented binders, up to 11 °C. It was found that asphalt with a clear or transparent binder demonstrated lower temperatures and faster heat dissipation in extreme conditions. Moreover, C.B asphalt mixtures displayed a rut resistance of 15%, with the pigmented C.B asphalt mixture showing a remarkable rut resistance of 73%, outperforming conventional asphalt. Non-black mixtures, especially C.B + zinc ferrite, showed improved resistance to permanent deformation in dynamic modulus tests.
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(This article belongs to the Special Issue Sustainable and Digital Transformation of Road Infrastructures)
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Open AccessArticle
Traffic Flow Optimization at Toll Plaza Using Proactive Deep Learning Strategies
by
Habib Talha Hashmi, Sameer Ud-Din, Muhammad Asif Khan, Jamal Ahmed Khan, Muhammad Arshad and Muhammad Usman Hassan
Infrastructures 2024, 9(5), 87; https://doi.org/10.3390/infrastructures9050087 - 15 May 2024
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Global urbanization and increasing traffic volume have intensified traffic congestion throughout transportation infrastructure, particularly at toll plazas, highlighting the critical need to implement proactive transportation infrastructure solutions. Traditional toll plaza management approaches, often relying on manual interventions, suffer from inefficiencies that fail to
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Global urbanization and increasing traffic volume have intensified traffic congestion throughout transportation infrastructure, particularly at toll plazas, highlighting the critical need to implement proactive transportation infrastructure solutions. Traditional toll plaza management approaches, often relying on manual interventions, suffer from inefficiencies that fail to adapt to dynamic traffic flow and are unable to produce preemptive control strategies, resulting in prolonged queues, extended travel times, and adverse environmental effects. This study proposes a proactive traffic control strategy using advanced technologies to combat toll plaza congestion and optimize traffic management. The approach involves deep learning convolutional neural network models (YOLOv7–Deep SORT) for vehicle counting and an extended short-term memory model for short-term arrival rate prediction. When projected arrival rates exceed a threshold, the strategy proactively activates variable speed limits (VSLs) and ramp metering (RM) strategies during peak hours. The novelty of this study lies in its predictive and adaptive capabilities, ensuring efficient traffic flow management. Validated through a case study at Ravi Toll Plaza Lahore using PTV VISSIMv7, the proposed method reduces queue length by 57% and vehicle delays by 47% while cutting fuel consumption and pollutant emissions by 28.4% and 34%, respectively. Additionally, by identifying the limitations of conventional approaches, this study presents a novel framework alongside the proposed strategy to bridge the gap between theory and practice, making it easier for toll plaza operators and transportation authorities to adopt and benefit from advanced traffic management techniques. Ultimately, this study underscores the importance of integrated and proactive traffic control strategies in enhancing traffic management, minimizing congestion, and fostering a more sustainable transportation system.
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Open AccessReview
Track Deterioration Model—State of the Art and Research Potentials
by
Ursula Ehrhart, Dieter Knabl and Stefan Marschnig
Infrastructures 2024, 9(5), 86; https://doi.org/10.3390/infrastructures9050086 - 14 May 2024
Abstract
Track deterioration models (TDMs) help to allocate maintenance work (direct costs) to vehicle runs. Furthermore, these models demonstrate the impact of rolling stock properties on infrastructure. This paper review provides an overview of the state of the art in railway track deterioration modelling
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Track deterioration models (TDMs) help to allocate maintenance work (direct costs) to vehicle runs. Furthermore, these models demonstrate the impact of rolling stock properties on infrastructure. This paper review provides an overview of the state of the art in railway track deterioration modelling and outlines the research potential in this domain. The main focus lies on ballast degradation, rail surface wear and fatigue, and their description in an empiric analytic wear formula. The basis for discussion is the wear formula of the Graz University of Technology. While the TDM demonstrates effectiveness, enhancements are sought, particularly with regard to adjusting the track parameters that vary across railway networks. Further exploration aims to refine the description of rail surface wear and rolling contact fatigue (RCF), incorporating factors such as traction energy and short-wave effects and adapting mathematical functions such as the t-Gamma function. This review underscores the need for ongoing research to develop TDMs that are both simple and detailed enough to encourage track-friendly rolling stock design.
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(This article belongs to the Special Issue Recent Advances in Railway Engineering)
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Open AccessArticle
Microstructural and Residual Properties of Self-Compacting Concrete Containing Waste Copper Slag as Fine Aggregate Exposed to Ambient and Elevated Temperatures
by
Bypaneni Krishna Chaitanya, Ilango Sivakumar, Yellinedi Madhavi, Daniel Cruze, Chava Venkatesh, Yenigandla Naga Mahesh and Chereddy Sonali Sri Durga
Infrastructures 2024, 9(5), 85; https://doi.org/10.3390/infrastructures9050085 - 13 May 2024
Cited by 2
Abstract
In recent times, with rapid development in the construction sector, the use of enormous amounts of materials is required for the production of concrete. Fire penetrates concrete, leading to chemical contamination, small cracks, and lightening. These effects can significantly change the properties of
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In recent times, with rapid development in the construction sector, the use of enormous amounts of materials is required for the production of concrete. Fire penetrates concrete, leading to chemical contamination, small cracks, and lightening. These effects can significantly change the properties of concrete’s structure, reduce its strength and durability, and also change the behavior of the structure and lead to effects on the environment. An attempt was made to study the effects of elevated temperature on the mechanical characteristics of self-compacting concrete (SCC) with by-products including fly ash as a partial replacement for cement and waste copper slag as a partial replacement for fine aggregate at 0%, 10%, 20%, 30%, 40%, 50%, 60%, and 70%. The SCC specimens were subjected to elevated temperatures ranging from 200, 400, 600, and 800 °C, respectively, for a steady-state of two hours in a digital muffle furnace. The residual compressive strength, mass loss, ultrasonic pulse velocity, and residual density along with a visual inspection of cracks and color changes were observed. In this study, with over 400 °C temperatures, surface fractures appeared. The residual compressive strength (R-CMS) of all the individual temperatures of the SCC-WCS% mixes exhibited a gain in strength range from 31 to 34 MPa at 400 °C, 26 to 35 MPa at 600 °C, and 22.5 MPa to 33.5 MPa at 800 °C, respectively. Microstructural analysis of SCC-WCS% mixtures subjected to elevated ambient temperatures is carried out with a scanning electron microscope (SEM) and X-ray diffraction (XRD).
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(This article belongs to the Section Infrastructures Materials and Constructions)
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Open AccessArticle
Building Information Modeling/Building Energy Simulation Integration Based on Quantitative and Interpretative Interoperability Analysis
by
Carolina Fernandes Vaz, Luísa Lopes de Freitas Guilherme, Ana Carolina Fernandes Maciel, André Luis De Araujo, Bruno Barzellay Ferreira Da Costa and Assed Naked Haddad
Infrastructures 2024, 9(5), 84; https://doi.org/10.3390/infrastructures9050084 - 7 May 2024
Abstract
The integration between the building information modeling (BIM) methodology and the building energy simulation (BES) can contribute to a thermo-energetic analysis since the model generated and fed into BIM is exported to simulation software. This integration, also called interoperability, is satisfactory when the
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The integration between the building information modeling (BIM) methodology and the building energy simulation (BES) can contribute to a thermo-energetic analysis since the model generated and fed into BIM is exported to simulation software. This integration, also called interoperability, is satisfactory when the information flow is carried out without the loss of essential information. Several studies point out interoperability flaws between the methodologies; however, most of them occur in low-geometry-complexity models during quantitative experiments. The purpose of this research was to analyze the BIM/BES integration based on a quantitative and interpretative interoperability analysis of two buildings with complex geometries located on the UFU Campus (library and Building 5T) in Uberlândia, Brazil. To accomplish this, two geometries of each building were modeled, detailed, and simplified to analyze the data import, workflow, and model correction in the BES software. In the case of the library, the integration of Revit with DesignBuilder and IES-VE was analyzed, and in Block 5T, Revit was used with DesignBuilder and eQUEST. The BES software that presented the best integration with Revit for complex geometries was DesignBuilder, with the best performance being in the interpretative criteria. It was concluded that the simplification of complex geometries is essential for better data transfers. To determine the BES software that has better integration with BIM, a comprehensive evaluation is necessary, considering not only data transfers but also ease of working within BES software, the possibility of corrections in these, as well as the availability of tutorials and developer support.
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(This article belongs to the Special Issue Smart, Sustainable and Resilient Infrastructures, 2nd Edition)
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