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: CiteScore - Q2 (Building and Construction)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 3.4 days (median values for papers published in this journal in the second half of 2023).
- 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:
2.6 (2022);
5-Year Impact Factor:
2.6 (2022)
Latest Articles
Building Information Modeling/Building Energy Simulation Integration Based on Quantitative and Interpretative Interoperability Analysis
Infrastructures 2024, 9(5), 84; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9050084 - 07 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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Open AccessArticle
Hierarchical SVM for Semantic Segmentation of 3D Point Clouds for Infrastructure Scenes
by
Mohamed Mansour, Jan Martens and Jörg Blankenbach
Infrastructures 2024, 9(5), 83; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9050083 - 06 May 2024
Abstract
The incorporation of building information modeling (BIM) has brought about significant advancements in civil engineering, enhancing efficiency and sustainability across project life cycles. The utilization of advanced 3D point cloud technologies such as laser scanning extends the application of BIM, particularly in operations
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The incorporation of building information modeling (BIM) has brought about significant advancements in civil engineering, enhancing efficiency and sustainability across project life cycles. The utilization of advanced 3D point cloud technologies such as laser scanning extends the application of BIM, particularly in operations and maintenance, prompting the exploration of automated solutions for labor-intensive point cloud modeling. This paper presents a demonstration of supervised machine learning—specifically, a support vector machine—for the analysis and segmentation of 3D point clouds, which is a pivotal step in 3D modeling. The point cloud semantic segmentation workflow is extensively reviewed to encompass critical elements such as neighborhood selection, feature extraction, and feature selection, leading to the development of an optimized methodology for this process. Diverse strategies are implemented at each phase to enhance the overall workflow and ensure resilient results. The methodology is then evaluated using diverse datasets from infrastructure scenes of bridges and compared with state-of-the-art deep learning models. The findings highlight the effectiveness of supervised machine learning techniques at accurately segmenting 3D point clouds, outperforming deep learning models such as PointNet and PointNet++ with smaller training datasets. Through the implementation of advanced segmentation techniques, there is a partial reduction in the time required for 3D modeling of point clouds, thereby further enhancing the efficiency and effectiveness of the BIM process.
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Open AccessArticle
Numerical Modeling and Performance Evaluation of Carbon Fiber-Reinforced Polymer-Strengthened Concrete Culverts against Water-Induced Corrosion
by
Hafiz Ahmed Waqas, Alireza Bahrami, Fayiz Amin, Mehran Sahil and Muhammad Saud Khan
Infrastructures 2024, 9(5), 82; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9050082 - 06 May 2024
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Culverts fulfill the vital function of safely channeling water beneath railway tracks, highways, and overpasses. They serve various purposes, including facilitating drainage in areas such as watercourses, drainage zones, and regions with restricted ground-bearing capacity. Precast reinforced concrete (RC) box culverts are a
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Culverts fulfill the vital function of safely channeling water beneath railway tracks, highways, and overpasses. They serve various purposes, including facilitating drainage in areas such as watercourses, drainage zones, and regions with restricted ground-bearing capacity. Precast reinforced concrete (RC) box culverts are a popular choice because they are strong, durable, rigid, and economical. However, culverts are prone to corrosion due to exposure to a range of environmental factors and aggressive chemicals. Therefore, enhancing the design and construction of this crucial infrastructure is imperative to effectively combat corrosion and to adhere to modern standards of reliability and affordability. In this study, carbon fiber-reinforced polymer (CFRP) was used to strengthen corroded culverts, with promising potential to improve safety and longevity in these structures. This study compared the behavior of corroded RC box culverts to CFRP-strengthened ones using the finite element method (FEM). It explored the impact of varying the damage thicknesses owing to corrosion, ranging from 0 mm to 20 mm, on the structural performance of the box culverts. The results showed that the CFRP model exhibited a substantial 25% increase in the capacity and reduced the damage compared to the reference model. Moreover, a parametric study was conducted for establishing a cost-effective design, in which numerous CFRP strip configurations were examined for a damaged-culvert model. The results indicated that a complete CFRP sheet was most effective for the maximum design capacity and repair effectiveness. The study’s outcomes provide valuable insights for professionals engaged in enhancing the strength of box culverts, aiming to increase the capacity, enhance the stability, and strengthen corroded culverts.
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Open AccessArticle
Aging Resistance Evaluation of an Asphalt Mixture Modified with Zinc Oxide
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Hugo Alexander Rondón-Quintana, Carlos Alfonso Zafra-Mejía and Carlos Felipe Urazán-Bonells
Infrastructures 2024, 9(5), 81; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9050081 - 04 May 2024
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The phenomenon of the oxidation and aging of asphalt binders affects the strength and durability of asphalt mixtures in pavements. Several studies are trying to improve the resistance to this phenomenon by modifying the properties of the binders with nano-particles. One material that
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The phenomenon of the oxidation and aging of asphalt binders affects the strength and durability of asphalt mixtures in pavements. Several studies are trying to improve the resistance to this phenomenon by modifying the properties of the binders with nano-particles. One material that shows promise in this field is zinc oxide (ZnO), especially in improving ultraviolet (UV) aging resistance. Few studies have evaluated the effect of these nano-particles on the thermo-oxidative resistance of asphalt binders, and, on hot-mix asphalt (HMA), studies are even more scarce and limited. Therefore, in the present study, the resistance to thermo-oxidative aging of an HMA manufactured with an asphalt binder modified with ZnO was evaluated. An asphalt cement (AC 60–70) was initially modified with 0, 1, 3, 5, 7.5, and 10% ZnO (percentage by weight of asphalt binder; ZnO/AC in wt%), and then exposed to aging in Rolling Thin-Film Oven tests (RTFOT) and a Pressure Aging Vessel (PAV). Penetration, viscosity, and softening point tests were performed on these binders, and aging indices were calculated and evaluated. Samples of HMAs were then manufactured using these binders and designed by the Marshall method, determining the optimum asphalt binder content (OAC) and the optimum ZnO/AC ratio. Control (unmodified) and modified HMA were subjected to short-term oven aging (STOA) and long-term oven aging (LTOA) procedures. Marshall, Indirect Tensile Strength (ITS), and resilient modulus (RM) tests were performed on these mixtures. LTOA/STOA results of the parameters measured in these tests were used as aging indices. In this study, ZnO was shown to increase the thermo-oxidative aging resistance of the asphalt binder and HMA. It also contributed to an increase in the resistance under monotonic loading in the Marshall and ITS tests, and under repeated loading in RM test. Likewise, it contributed to a slightly increasing resistance to moisture damage. The best performance is achieved using ZnO/AC = 5 wt%.
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Open AccessArticle
The Influence of Soil Deformability on the Seismic Response of 3D Mixed R/C–Steel Buildings
by
Paraskevi K. Askouni
Infrastructures 2024, 9(5), 80; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9050080 - 04 May 2024
Abstract
Following effective seismic codes, common buildings are considered to be made of the same material throughout the story distribution and based on an ideal rigid soil. However, in daily construction practice, there are often cases of buildings formed by a bottom part constructed
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Following effective seismic codes, common buildings are considered to be made of the same material throughout the story distribution and based on an ideal rigid soil. However, in daily construction practice, there are often cases of buildings formed by a bottom part constructed with reinforced concrete (r/c) and a higher steel part, despite this construction type not being recognized by code assumptions. In addition, soil deformability, commonly referred to as the Soil–Structure Interaction (SSI), is widely found to affect the earthquake response of typical residence structures, apart from special structures, though it is not included in the normative design procedure. This work studies the seismic response of in-height mixed 3D models, considering the effect of sustaining deformable ground compared to the common rigid soil hypothesis, which has not been clarified so far in the literature. Two types of soft soil, as well as the rigid soil assumption, acting as a reference point, are considered, while two limit interconnections between the steel part on the concrete part are included in the group analysis. The possible influence of the seismic orientation angle is explored in the analysis set. Selected numerical results of the dynamic nonlinear analyses under strong near-fault ground excitations were plotted through dimensionless parameters to facilitate an objective comparative discussion. The effect of SSI on the nonlinear performance of three-dimensional mixed models is identified, which serves as the primary contribution of this work, making it unique among the numerous research works available globally and pointing to findings that are useful for the enhancement of the seismic rules regarding the design and analysis of code-neglected mixed buildings.
Full article
(This article belongs to the Special Issue Advances in Steel and Composite Steel–Concrete Bridges and Buildings)
Open AccessArticle
Warm-Mix Asphalt Containing Reclaimed Asphalt Pavement: A Case Study in Switzerland
by
Nicolas Bueche, Samuel Probst and Shahin Eskandarsefat
Infrastructures 2024, 9(5), 79; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9050079 - 29 Apr 2024
Abstract
Among the technologies proposed for achieving carbon neutralization in asphalt road pavements, warm-mix asphalt (WMA) has garnered increasing attention in recent years. While WMA holds the potential for various environmental and technical benefits, a comprehensive understanding of its implementation, technology selection, and additives
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Among the technologies proposed for achieving carbon neutralization in asphalt road pavements, warm-mix asphalt (WMA) has garnered increasing attention in recent years. While WMA holds the potential for various environmental and technical benefits, a comprehensive understanding of its implementation, technology selection, and additives is essential for successful application. This study presents a case where a bio-based chemical additive was employed to produce WMA containing 50% reclaimed asphalt pavement (RAP) for a surface course in Bern, Switzerland. To minimize additional variables during testing and analysis, no other additive or rejuvenator was introduced into the mixtures. The testing plan encompassed laboratory tests on samples collected during material placement and recompacted at varying temperatures in the laboratory, as well as cores extracted from the job site. As anticipated, the presence of the chemical WMA additive did not alter the rheological properties of the reference bitumen. Although in the mixture-scale tests, the WMA mixture exhibited comparable properties to the control hot-mix asphalt (HMA), it is not expected that the small dosage of the chemical additive functions the same grade after reheating and compaction. Nevertheless, the cores extracted from the job site proved the efficiency of the applied WMA technology. In addition, consistent with existing literature, the cracking tolerance (CT) index values of 62 for HMA and 114 and 104.9 for WMA mixtures indicated that the latter is less susceptible to cracking. Consequently, this characteristic could contribute to the enhanced durability of asphalt pavements.
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(This article belongs to the Special Issue Sustainable Low-Carbon Road Pavement Infrastructure: Methods and Challenges)
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Ensemble Learning Approach for Developing Performance Models of Flexible Pavement
by
Ali Taheri and John Sobanjo
Infrastructures 2024, 9(5), 78; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9050078 - 25 Apr 2024
Abstract
This research utilizes the Long-Term Pavement Performance database, focusing on devel-oping a predictive model for flexible pavement performance in the Southern United States. Analyzing 367 pavement sections, this study investigates crucial factors influencing asphaltic concrete (AC) pavement deterioration, such as structural and material
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This research utilizes the Long-Term Pavement Performance database, focusing on devel-oping a predictive model for flexible pavement performance in the Southern United States. Analyzing 367 pavement sections, this study investigates crucial factors influencing asphaltic concrete (AC) pavement deterioration, such as structural and material components, air voids, compaction density, temperature at laydown, traffic load, precipitation, and freeze–thaw cycles. The objective of this study is to develop a predictive machine learning model for AC pavement wheel path cracking (WpCrAr) and the age at which cracking initiates (WpCrAr) as performance indicators. This study thoroughly investigated three ensemble machine learning models, including random forest, extremely randomized trees (ETR), and extreme gradient boosting (XGBoost). It was observed that XGBoost, optimized using Bayesian methods, emerged as the most effective among the evaluated models, demonstrating good predictive accuracy, with an R2 of 0.79 for WpCrAr and 0.92 for AgeCrack and mean absolute errors of 1.07 and 0.74, respectively. The most important features influencing crack initiation and progression were identified, including equivalent single axle load (ESAL), pavement age, number of layers, precipitation, and freeze–thaw cycles. This paper also showed the impact of pavement material combinations for base and subgrade layers on the delay of crack initiation.
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(This article belongs to the Section Infrastructures and Structural Engineering)
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Wolf Rock Lighthouse Long-Term Monitoring
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James Brownjohn, Alison Raby, James Bassitt, Alessandro Antonini, Zuo Zhu and Peter Dobson
Infrastructures 2024, 9(4), 77; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040077 - 22 Apr 2024
Abstract
Wolf Rock Lighthouse is a Victorian era masonry structure located in an extreme environment facing the fiercest Atlantic storms off the southwest coast of England whose dynamic behaviour has been studied since 2016. Initially, a modal test was used to determine modal parameters;
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Wolf Rock Lighthouse is a Victorian era masonry structure located in an extreme environment facing the fiercest Atlantic storms off the southwest coast of England whose dynamic behaviour has been studied since 2016. Initially, a modal test was used to determine modal parameters; then, in 2017, a monitoring system was installed that has operated intermittently providing response data for a number of characteristic loading events. These events have included wave loads due to storms, a small UK earthquake, helicopters landing on the helideck, and the grounding of a ship on the reef. This is believed to be the most extensive experimental campaign on any structure of this type. This paper briefly describes a unique project involving the characterisation and measurement of dynamic behaviour due to different forms of dynamic loading.
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(This article belongs to the Special Issue Advances in Structural Health Monitoring of the Built Environment)
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Fuzzy Analysis of Financial Risk Management Strategies for Sustainable Public–Private Partnership Infrastructure Projects in Ghana
by
Isaac Akomea-Frimpong, Xiaohua Jin and Robert Osei-Kyei
Infrastructures 2024, 9(4), 76; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040076 - 18 Apr 2024
Abstract
Public–private partnership (PPP) is a prominent tool for sustainable infrastructure development. However, the positive contributions of PPPs toward the attainment of sustainable, climate resilience and zero-carbon infrastructure projects are hampered by poor financial risk management. This problem is more prevalent in developing countries
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Public–private partnership (PPP) is a prominent tool for sustainable infrastructure development. However, the positive contributions of PPPs toward the attainment of sustainable, climate resilience and zero-carbon infrastructure projects are hampered by poor financial risk management. This problem is more prevalent in developing countries like Ghana where private investment inflow has plummeted due to the COVID-19 recession and poor project performance. Thus, this study aims to assess the key financial risk management strategies in ensuring sustainable PPP infrastructure projects in Ghana. The study utilised primary data from PPP practitioners in Ghana solicited through survey questionnaires. Factor analysis, mean scores and fuzzy synthetic analysis are the data analysis techniques for this study. The results revealed that sustainable and green funding models, effective cost-reduction initiatives, a competent team with committed leadership and emerging technologies and regulations constitute the key strategies for managing the financial risks of sustainable PPP infrastructure projects. Although future studies must expand the scope of data gathering, the findings of the study enrich the theoretical understanding of financial risks in sustainable investments in PPP infrastructures. Relevant remedies that will aid the development of practical financial risk management guidelines are also provided in this study for PPP practitioners.
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(This article belongs to the Special Issue Smart Construction in Infrastructure Project Development)
Open AccessArticle
Navigating the Adoption of 5D Building Information Modeling: Insights from Norway
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Haidar Hosamo Hosamo, Christian Nordahl Rolfsen, Florent Zeka, Sigurd Sandbeck, Sami Said and Morten André Sætre
Infrastructures 2024, 9(4), 75; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040075 - 18 Apr 2024
Abstract
Exploring the integration of 5D Building Information Modeling (BIM) within the Norwegian construction sector, this study examines its transformative impact on cost estimation and project management, highlighting technological and skill-based adoption challenges. Through methodical case studies and interviews with industry experts, it is
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Exploring the integration of 5D Building Information Modeling (BIM) within the Norwegian construction sector, this study examines its transformative impact on cost estimation and project management, highlighting technological and skill-based adoption challenges. Through methodical case studies and interviews with industry experts, it is revealed that 5D BIM significantly enhances the precision of cost estimations and effectively reduces financial overruns in complex construction projects, indicating an industry shift towards its broader acceptance. The research sets out to explore current challenges and opportunities in 5D BIM, assess the usability and integration of software tools, and understand systemic barriers and skill gaps hindering further progress. These objectives lead to a detailed understanding of 5D BIM’s role in improving economic and procedural efficiencies in construction. Suggesting its pivotal role in the evolving construction management realm, the study contributes important insights into 5D BIM’s transformative potential and underscores its importance in advancing the construction industry’s digital transformation.
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(This article belongs to the Special Issue Building Information Modelling for Infrastructure Management)
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A Large-Crack Image-Stitching Method with Cracks as the Regions of Interest
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Szu-Pyng Kao, Jhih-Sian Lin, Feng-Liang Wang and Pen-Shan Hung
Infrastructures 2024, 9(4), 74; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040074 - 16 Apr 2024
Abstract
While crack detection is crucial for maintaining concrete structures, existing methods often overlook the analysis of large cracks that span multiple images. Such analyses typically rely on image stitching to create a complete image of a crack. Current stitching methods are not only
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While crack detection is crucial for maintaining concrete structures, existing methods often overlook the analysis of large cracks that span multiple images. Such analyses typically rely on image stitching to create a complete image of a crack. Current stitching methods are not only computationally demanding but also require manual adjustments; thus, a fast and reliable solution is still lacking. To address these challenges, we introduce a stitching method that leverages the advantages of crack image-segmentation models. This method first utilizes the Mask R-CNN model for the identification of crack regions as regions of interest (ROIs) within images. These regions are then used to calculate keypoints of the scale-invariant feature transform (SIFT), and descriptors for these keypoints are computed with the original images for image matching and stitching. Compared with traditional methods, our approach significantly reduces the computational time; by 98.6% in comparison to the Brute Force (BF) matcher, and by 58.7% with respect to the Fast Library for Approximate Nearest Neighbors (FLANN) matcher. Our stitching results on images with different degrees of overlap or changes in shooting posture show superior structural similarity index (SSIM) values, demonstrating excellent detail-matching performance. Moreover, the ability to measure complete crack images is indicated by the relative error of 7%, which is significantly better than that of traditional methods.
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(This article belongs to the Special Issue Advanced Technologies in Data Collection, Evaluation, and Visualization of Reinforced Concrete Structures)
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Enhancing Flexural Strength of RC Beams with Different Steel–Glass Fiber-Reinforced Polymer Composite Laminate Configurations: Experimental and Analytical Approach
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Arash K. Pour, Mehrdad Karami and Moses Karakouzian
Infrastructures 2024, 9(4), 73; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040073 - 12 Apr 2024
Abstract
This study intended to measure the efficiency of different strengthening techniques to advance the flexural characteristics of reinforced concrete (RC) beams using glass fiber-reinforced polymer (GFRP) laminates, including externally bonded reinforcement (EBR), externally bonded reinforcement on grooves (EBROG), externally bonded reinforcement in grooves
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This study intended to measure the efficiency of different strengthening techniques to advance the flexural characteristics of reinforced concrete (RC) beams using glass fiber-reinforced polymer (GFRP) laminates, including externally bonded reinforcement (EBR), externally bonded reinforcement on grooves (EBROG), externally bonded reinforcement in grooves (EBRIG), and the near-surface mounted (NSM) system. A new NSM technique was also established using an anchorage rebar. Then, the effect of the NSM method with and without externally strengthening GFRP laminates was studied. Twelve RC beams (150 × 200 × 1500 mm) were manufactured and examined under a bending system. One specimen was designated as the control with no GFRP laminate. To perform the NSM method, both steel and GFRP rebars were used. In the experiments, capability, as well as the deformation and ductileness of specimens, were evaluated, and a comparison was made between the experimental consequences and existing standards. Finally, a new regression was generated to predict the final resistance of RC beams bound with various retrofitting techniques. The findings exhibited that the NSM technique, besides preserving the strengthening materials, could enhance the load-bearing capacity and ductileness of RC beams up to 42.3% more than the EBR, EBROG, and EBRIG performances.
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(This article belongs to the Special Issue Advances in Steel and Composite Steel–Concrete Bridges and Buildings)
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Transportation System and the Improvement of Urban Vehicular Flow in the District of Huánuco-Perú 2022
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Yessica Julia Verastegui and Doris Esenarro
Infrastructures 2024, 9(4), 72; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040072 - 12 Apr 2024
Abstract
The objective of this research is to propose a public transport reorganization system that allows the improvement of urban vehicle flow. The lack of adequate transportation infrastructure and the existing disorder in the services provided by collective car, Microbus, Rural Public Transportation Van
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The objective of this research is to propose a public transport reorganization system that allows the improvement of urban vehicle flow. The lack of adequate transportation infrastructure and the existing disorder in the services provided by collective car, Microbus, Rural Public Transportation Van (Combi), Coaster, and mototaxis generate congestion in public transportation, especially during peak hours, resulting in environmental and noise pollution. The research was structured into four stages: data collection on the public and private transportation network, importing and creating the transportation network in the urban area of the Huánuco district, zoning and connectivity of the study area, and finally, creating the origin/destination (O/D) matrix for public transportation, supported by digital tools (ArcGIS 10.5, AutoCAD 2018, Excel 2017). To meet the demand of 135,343 passengers from South to North and 118,958 from North to South, the proposal includes establishing one main route and seven feeder routes, requiring 422 buses and road infrastructure, as depicted in the proposal This system will have exclusive lanes to operate the Mass Transit System, allowing it to accommodate 59% of users who prefer using public transportation. This proposal aims to offer an efficient and high-quality transportation system.
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(This article belongs to the Section Sustainable Infrastructures)
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Multi-Context Point Cloud Dataset and Machine Learning for Railway Semantic Segmentation
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Abderrazzaq Kharroubi, Zouhair Ballouch, Rafika Hajji, Anass Yarroudh and Roland Billen
Infrastructures 2024, 9(4), 71; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040071 - 09 Apr 2024
Abstract
Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations of existing algorithms. To address this challenge, we present Rail3D,
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Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations of existing algorithms. To address this challenge, we present Rail3D, the first comprehensive dataset for semantic segmentation in railway environments with a comparative analysis. Rail3D encompasses three distinct railway contexts from Hungary, France, and Belgium, capturing a wide range of railway assets and conditions. With over 288 million annotated points, Rail3D surpasses existing datasets in size and diversity, enabling the training of generalizable machine learning models. We conducted a generic classification with nine universal classes (Ground, Vegetation, Rail, Poles, Wires, Signals, Fence, Installation, and Building) and evaluated the performance of three state-of-the-art models: KPConv (Kernel Point Convolution), LightGBM, and Random Forest. The best performing model, a fine-tuned KPConv, achieved a mean Intersection over Union (mIoU) of 86%. While the LightGBM-based method achieved a mIoU of 71%, outperforming Random Forest. This study will benefit infrastructure experts and railway researchers by providing a comprehensive dataset and benchmarks for 3D semantic segmentation. The data and code are publicly available for France and Hungary, with continuous updates based on user feedback.
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(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
Analysis of Arch Bridge Condition Data to Identify Network-Wide Controls and Trends
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Kristopher Campbell, Myra Lydon, Nicola-Ann Stevens and Su Taylor
Infrastructures 2024, 9(4), 70; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040070 - 04 Apr 2024
Abstract
This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up
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This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.
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(This article belongs to the Topic AI Enhanced Civil Infrastructure Safety)
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Joint Behavior of Full-Scale Precast Concrete Pipe Infrastructure: Experimental and Numerical Analysis
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Abdul Basit, Safeer Abbas, Muhammad Mubashir Ajmal, Ubaid Ahmad Mughal, Syed Minhaj Saleem Kazmi and Muhammad Junaid Munir
Infrastructures 2024, 9(4), 69; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040069 - 03 Apr 2024
Abstract
This study undertakes a comprehensive experimental and numerical analysis of the structural integrity of buried RC sewerage pipes, focusing on the performance of two distinct jointing materials: cement mortar and non-shrinkage grout. Through joint shear tests on full-scale sewer pipes under single point
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This study undertakes a comprehensive experimental and numerical analysis of the structural integrity of buried RC sewerage pipes, focusing on the performance of two distinct jointing materials: cement mortar and non-shrinkage grout. Through joint shear tests on full-scale sewer pipes under single point loading conditions, notable effects on the crown and invert of the joint were observed, highlighting the critical vulnerability of these structures to internal and external pressures. Two materials—cement–sand mortar and non-shrinkage grout—were used in RC pipe joints to experimentally evaluate the joint strength of the sewerage pipes. Among the materials tested, cement–sand mortar emerged as the superior choice, demonstrating the ability to sustain higher loads up to 25.60 kN, proving its cost-effectiveness and versatility for use in various locations within RC pipe joints. Conversely, non-shrinkage grout exhibited the lowest ultimate failure load, i.e., 21.50 kN, emphasizing the importance of material selection in enhancing the resilience and durability of urban infrastructure. A 3D finite element (FE) analysis was also employed to assess the effect of various factors on stress distribution and joint deformation. The findings revealed a 10% divergence between the experimental and numerical data regarding the ultimate load capacity of pipe joints, with experimental tests indicating a 25.60 kN ultimate load and numerical simulations showing a 23.27 kN ultimate load. Despite this discrepancy, the close concordance between the two sets of data underscores the utility of numerical simulations in predicting the behavior of pipe joints accurately. This study provides valuable insights into the selection and application of jointing materials in sewerage systems, aiming to improve the structural integrity and longevity of such critical infrastructure.
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(This article belongs to the Special Issue Advances in Steel and Composite Steel–Concrete Bridges and Buildings)
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Corrosion of Steel Rebars in Construction Materials with Reinforced Pervious Concrete
by
Rosendo Lerma Villa, José Luis Reyes Araiza, José de Jesús Pérez Bueno, Alejandro Manzano-Ramírez and Maria Luisa Mendoza López
Infrastructures 2024, 9(4), 68; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040068 - 01 Apr 2024
Abstract
Pervious concrete has great potential for use in many practical applications as a part of urban facilities that can add value through water harvesting and mitigating severe damage from floods. The construction and agricultural industries can take direct advantage of pervious concrete’s characteristics
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Pervious concrete has great potential for use in many practical applications as a part of urban facilities that can add value through water harvesting and mitigating severe damage from floods. The construction and agricultural industries can take direct advantage of pervious concrete’s characteristics when water is a key factor included in projects as part of the useful life of a facility. Pervious concrete also has applications in vertical constructions, fountains, and pedestrian crossings. This work evidences that pervious concrete’s corrosion current increases with increasing aggregate size. Also, corrosion is a factor to consider only when steel pieces are immersed, aggravated by the presence of chlorine, but it drains water and does not retain moisture. Steel-reinforced pervious concrete was studied, and the grain size of the inert material and the corrosion process parameters were investigated. The electrochemical frequency modulation technique is proposed as a suitable test for a fast, reproducible assessment which, without damaging reinforced cement structures, particularly pervious concrete, indicates a trend of increasing corrosion current density as the size of the aggregate increases or density diminishes.
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(This article belongs to the Special Issue Advances in Steel and Composite Steel–Concrete Bridges and Buildings)
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Open AccessArticle
Comprehensive Empirical Modeling of Shear Strength Prediction in Reinforced Concrete Deep Beams
by
Eyad K. Sayhood, Nisreen S. Mohammed, Salam J. Hilo and Salih S. Salih
Infrastructures 2024, 9(4), 67; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040067 - 28 Mar 2024
Abstract
This paper presents comprehensive empirical equations to predict the shear strength capacity of reinforced concrete deep beams, with a focus on improving the accuracy of existing codes. Analyzing 198 deep beams imported from 15 existing investigations, this study considers various parameters such as
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This paper presents comprehensive empirical equations to predict the shear strength capacity of reinforced concrete deep beams, with a focus on improving the accuracy of existing codes. Analyzing 198 deep beams imported from 15 existing investigations, this study considers various parameters such as concrete compressive strength (f′c), the shear span-to-effective depth ratio (av/d), and reinforcement ratios (ps, pv, and ph). Introducing a novel predictive empirical equation, this study conducts a rigorous evaluation using statistical metrics and a linear regression analysis (MAE, RMSE, and R2). The proposed model demonstrates a significant reduction in the coefficient of variation (CV) to 27.08%, compared to the existing codes’ limitations. Comparative analyses highlight the accuracy of the empirical equation, revealing an improved convergence of data points and minimal sensitivity to variations in key parameters. The results proved that the proposed empirical equation enhanced the accuracy to predict the shear strength capacity of the reinforced concrete deep beams in various scenarios, making it a valuable tool for structural engineers. This research contributes to advancing the understanding of shear strength capacity in reinforced concrete deep beams, offering a reliable empirical equation with implications for refining design methodologies and enhancing safety with the efficiency of structural systems.
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(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)
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Open AccessArticle
Enhancement Seismic Response of a Bored Tunnel Using Isolation for the Challenge of a Faulted Rock Crossing
by
Ahmed Elgamal and Nissreen Elfaris
Infrastructures 2024, 9(4), 66; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040066 - 27 Mar 2024
Abstract
The tunnel boring method (TBM) is a widely used and effective tunneling technology in various rock mass quality circumstances. A “faulted rock mass” can range from a highly fractured rock mass to a sheared weak rock mass, making the ground conditions challenging for
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The tunnel boring method (TBM) is a widely used and effective tunneling technology in various rock mass quality circumstances. A “faulted rock mass” can range from a highly fractured rock mass to a sheared weak rock mass, making the ground conditions challenging for tunneling, especially for TBMs. “Faulted rock” significantly affects hard rock TBMs, primarily due to the TBM’s high geological risk and poor flexibility. TBMs require careful planning and preparation, starting with preliminary assessments. This study investigates the impact of establishing an isolation material between a circular tunnel and the adjacent faulting rock on seismic response. The two parts of the parametric analysis for the isolation material utilized in the model look at how changes in the mechanical characteristics of the material, such as the shear modulus of the rock and the fault, affect the stresses created in the tunnel. The second section examines how changes in the isolation width concerning the fault width affect the stresses and displacements produced in the tunnel. Additionally, the effectiveness of isolating the tunnel during sudden changes in the characteristics of the rock was investigated under seismic loading perpendicular to the tunnel and parallel to the tunnel. The finite element approach was utilized to model the TBM tunnel and the neighboring rock with a fault or sudden change in the rock using Midas/GTS-NX, simulating the interactions between the rock and the tunnel. Time-history analysis using the El Centro earthquake was conducted to calculate the stresses in the tunnels during seismic events. Peak ground accelerations between 0.10 g and 0.30 g were utilized for excitation. A time step of 0.02 s and a length of 10 s for the seismic event were used in the analysis, with traditional grout pea gravel vs. the isolation layer. Comparisons were made between the absolute stresses (the greatest possible values) in the normal tunnel section (Sxx) and those induced in the tunnel with traditional grout and with isolation. Furthermore, the study of vertical displacement was taken into consideration. The seismic isolation method is highly effective in improving the seismic safety of bored tunnels. The results show that the significant values of the ratio between the shear modulus of isolation and the surrounding soil should be between 0.2% and 0.4%. Where parts of the tunnel run through a fault, the effective length of isolation should be between one and two times the fault width. The dynamic behavior of the tunnel with isolation is better than that with traditional grout. Generally, when isolation is used for any length, it reduces the stresses at the area of sudden change. Consequently, engineering assessments from both structural and geotechnical engineering viewpoints are now required for these unique constructions. An underground structure’s safety should be evaluated by the designer to ensure that it can sustain various applied loads, taking into account seismic loads in addition to construction and permanent static loads. Tunnels may be especially vulnerable in areas where the composition of the soil or rock varies.
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(This article belongs to the Section Infrastructures and Structural Engineering)
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Towards Sustainable Road Pavements: Sound Absorption in Rubber-Modified Asphalt Mixtures
by
Freddy Richard Apaza, Víctoriano Fernández Vázquez, Santiago Expósito Paje, Federico Gulisano, Valerio Gagliardi, Leticia Saiz Rodríguez and Juan Gallego Medina
Infrastructures 2024, 9(4), 65; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures9040065 - 25 Mar 2024
Abstract
In the last decade, various asphalt paving materials have undergone investigation for sound attenuation purposes. This research aims to delve into the innovative design of sustainable road pavements by examining sound absorption in rubber-modified asphalt mixtures. More specifically, the impact of alternative sustainable
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In the last decade, various asphalt paving materials have undergone investigation for sound attenuation purposes. This research aims to delve into the innovative design of sustainable road pavements by examining sound absorption in rubber-modified asphalt mixtures. More specifically, the impact of alternative sustainable materials on the sound absorption of asphalt mixtures across different temperatures, precisely crumb rubber (CR) derived from recycling of end-of-life tires, was investigated. The acoustic coefficient and its Gaussian fit parameters (Peak, BandWidth, and Area Under the Curve) were evaluated. Five different types of asphalt mixtures were studied, encompassing dense, discontinuous, and open mixtures with 0%, 0.75%, and 1.50% CR incorporated through the dry process (DP). The results of sound absorption indicated a slight influence of crumb rubber at temperatures ranging from 10 °C to 60 °C, particularly in mixtures with high void content. On the other hand, as expected, the void content proved to be highly correlated with sound absorption. These findings facilitated the establishment of predictive models that correlate acoustic absorption spectra with the characteristics of asphalt mixtures. As a result, these models will be valuable in the design of the next generation of sound-absorbing pavements.
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(This article belongs to the Special Issue Sustainable and Digital Transformation of Road Infrastructures)
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