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).
- 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
Pedal towards Safety: The Development and Evaluation of a Risk Index for Cyclists
Infrastructures 2024, 9(1), 14; https://doi.org/10.3390/infrastructures9010014 - 15 Jan 2024
Abstract
Cyclists are at a higher risk of being involved in accidents. To this end, a safer environment for cyclists should be pursued so that they can feel safe while riding their bicycles. Focusing on safety risks that cyclists may face is the main
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Cyclists are at a higher risk of being involved in accidents. To this end, a safer environment for cyclists should be pursued so that they can feel safe while riding their bicycles. Focusing on safety risks that cyclists may face is the main key to preserving safe mobility, reducing accidents, and improving their level of safety during their travel. Identifying and assessing risk factors, as well as informing cyclists about them may lead to an efficient and integrated transportation system. Therefore, the purpose of this research is to introduce a risk index that can be adapted to different road areas in order to measure the degree of how risky these areas are for biking. Cyclists’ behavior and demographics were integrated into the risk index calculation. The methodology followed to obtain the risk index composed of four phases: risk factor identification, risk factor weighting, risk index formulation, and risk index validation. Nineteen risk factors are categorized into four major groups: facility features, infrastructure features, cyclist behavior, and weather and traffic conditions.
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(This article belongs to the Special Issue Sustainable Infrastructures for Urban Mobility)
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Seepage Actions and Their Consequences on the Support Scheme of Deep-Buried Tunnels Constructed in Soft Rock Strata
Infrastructures 2024, 9(1), 13; https://doi.org/10.3390/infrastructures9010013 - 12 Jan 2024
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The stability of deep soft rock tunnels under seepage conditions is of particular concern. Aiming at thoroughly discussing seepage actions and their consequences on the support schemes of such structures, the host rocks of the Weilai Tunnel situated in the Guangxi province of
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The stability of deep soft rock tunnels under seepage conditions is of particular concern. Aiming at thoroughly discussing seepage actions and their consequences on the support schemes of such structures, the host rocks of the Weilai Tunnel situated in the Guangxi province of China are used as the research subject. Emphasis is placed on adequately examining the seepage conditions, stresses, displacements and plastic zone radii along the surrounding rocks of such tunnels, taking into consideration the Mogi–Coulomb strength criterion and the elastic-plastic theory. Explicitly, this article proposes analytical solutions for stresses, displacements and plastic radii around deep tunnels in soft rocks under seepage conditions by considering the aforesaid criterion and nonlinear elastoplastic approaches. Subsequently, based on the strain-softening model, the coupled actions of seepage and softening on the rocks surrounding the tunnel are studied. In order to investigate the effects of relevant influencing factors on tunnel stability, parametric studies are thoroughly examined. According to the results, it is revealed that the support scheme of deep soft rock tunnels must be of the highest resistance possible to better decrease the plastic zone and the tangential stress along the host rocks. Moreover, throughout the surrounding rocks, the dissemination of pore water pressure is strongly affected by the uneven permeability coefficient under anisotropic seepage states. The combined effects of softening and seepage are very dangerous for the surrounding rocks of deep-buried tunnels. It is also shown that the seepage pressure substantially affects the plastic radii and tunnel displacements. Under high seepage pressure, the surface displacements of the tunnel are excessive, easily exceeding 400 mm. To better guarantee the reasonable longevity of such tunnels, the long-term monitoring of their support structures with reliable remote sensors is strongly recommended.
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Open AccessArticle
The Road Network Design Problem for the Deployment of Automated Vehicles (RNDP-AVs): A Nonlinear Programming Mathematical Model
Infrastructures 2024, 9(1), 12; https://doi.org/10.3390/infrastructures9010012 - 10 Jan 2024
Abstract
Once trusted, automated vehicles (AVs) will gradually appear in urban areas. Such a transition is an opportunity in transport planning to control undesired impacts and possibly mitigate congestion at a time when both conventional vehicles (CVs) and AVs coexist. This paper deals with
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Once trusted, automated vehicles (AVs) will gradually appear in urban areas. Such a transition is an opportunity in transport planning to control undesired impacts and possibly mitigate congestion at a time when both conventional vehicles (CVs) and AVs coexist. This paper deals with the complex transport decision problem of designing part of the network that is exclusive for AVs through a nonlinear programming model. The objective function minimises the costs of travel times where vehicles circulate under user equilibrium. The model evaluates the benefits of having an AVs-dedicated infrastructure and the associated costs from the detouring of CVs. Three planning strategies are explored: incremental, long-term and hybrid planning. The first creates a subnetwork evolving incrementally over time. The second reversely designs a subnetwork from the optimal solution obtained at a ratio of 90% AVs. The third limits the incremental planning towards that optimal long-term solution. The model is applied to the city of Delft, in the Netherlands. Two scenarios are analysed, with and without AV-dedicated roads, at several AV penetration rates. We find that implementing dedicated roads for AVs reduces the overall costs and congestion up to 16%. However, CV detouring is inevitable at later network stages, increasing the total distance travelled (up to 8%) and congestion in the surroundings of AV subnetworks. Concerning the planning strategies, incremental planning is appropriate for starting in the initial stages and is the strategy that most tackles CV detouring. The hybrid or the long-term strategies are more suitable to be applied after a ratio of 50% AVs, and the hybrid planning is the strategy that most reduces delay.
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(This article belongs to the Special Issue Smart Mobility: Advancements and Innovations in Intelligent Transportation Systems)
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Exploring the Cyclic Behaviour of URM Walls with and without Damp-Proof Course (DPC) Membranes through Discrete Element Method
Infrastructures 2024, 9(1), 11; https://doi.org/10.3390/infrastructures9010011 - 06 Jan 2024
Abstract
Unreinforced masonry (URM) walls are common load-bearing structural elements in most existing buildings, consisting of masonry units (bricks) and mortar joints. They indicate a highly nonlinear and complex behaviour when subjected to combined compression–shear loading influenced by different factors, such as pre-compression load
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Unreinforced masonry (URM) walls are common load-bearing structural elements in most existing buildings, consisting of masonry units (bricks) and mortar joints. They indicate a highly nonlinear and complex behaviour when subjected to combined compression–shear loading influenced by different factors, such as pre-compression load and boundary conditions, among many others, which makes predicting their structural response challenging. To this end, the present study offers a discontinuum-based modelling strategy based on the discrete element method (DEM) to investigate the in-plane cyclic response of URM panels under different vertical pressures with and without a damp-proof course (DPC) membrane. The adopted modelling strategy represents URM walls as a group of discrete rigid block systems interacting along their boundaries through the contact points. A novel contact constitutive model addressing the elasto-softening stress–displacement behaviour of unit–mortar interfaces and the associated stiffness degradation in tension–compression regimes is adopted within the implemented discontinuum-based modelling framework. The proposed modelling strategy is validated by comparing a recent experimental campaign where the essential data regarding geometrical features, material properties and loading histories are obtained. The results show that while the proposed computational modelling strategy can accurately capture the hysteric response of URM walls without a DPC membrane, it may underestimate the load-carrying capacity of URM walls with a DPC membrane.
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(This article belongs to the Special Issue Advanced Structural Analysis of Masonry and Reinforced Concrete Structures)
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Modeling Variability in Seismic Analysis of Concrete Gravity Dams: A Parametric Analysis of Koyna and Pine Flat Dams
Infrastructures 2024, 9(1), 10; https://doi.org/10.3390/infrastructures9010010 - 05 Jan 2024
Abstract
This study addresses the vital issue of the variability associated with modeling decisions in dam seismic analysis. Traditionally, structural modeling and simulations employ a progressive approach, where more complex models are gradually incorporated. For example, if previous levels indicate insufficient seismic safety margins,
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This study addresses the vital issue of the variability associated with modeling decisions in dam seismic analysis. Traditionally, structural modeling and simulations employ a progressive approach, where more complex models are gradually incorporated. For example, if previous levels indicate insufficient seismic safety margins, a more advanced analysis is then undertaken. Recognizing the constraints and evaluating the influence of various methods is essential for improving the comprehension and effectiveness of dam safety assessments. To this end, an extensive parametric study is carried out to evaluate the seismic response variability of the Koyna and Pine Flat dams using various solution approaches and model complexities. Numerical simulations are conducted in a 2D framework across three software programs, encompassing different dam system configurations. Additional complexity is introduced by simulating reservoir dynamics with Westergaard-added mass or acoustic elements. Linear and nonlinear analyses are performed, incorporating pertinent material properties, employing the concrete damage plasticity model in the latter. Modal parameters and crest displacement time histories are used to highlight variability among the selected solution procedures and model complexities. Finally, recommendations are made regarding the adequacy and robustness of each method, specifying the scenarios in which they are most effectively applied.
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(This article belongs to the Special Issue Advances in Dam Engineering of the 21st Century)
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Open AccessTechnical Note
Smartphone-Based Cost-Effective Pavement Performance Model Development Using a Machine Learning Technique with Limited Data
by
and
Infrastructures 2024, 9(1), 9; https://doi.org/10.3390/infrastructures9010009 - 03 Jan 2024
Abstract
Road networks play a significant role in each country’s economy, especially in countries such as Afghanistan, which is strategically located in the international transit path from Europe to East Asia. In such a country, pavement performance models are fundamental for the pavement maintenance
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Road networks play a significant role in each country’s economy, especially in countries such as Afghanistan, which is strategically located in the international transit path from Europe to East Asia. In such a country, pavement performance models are fundamental for the pavement maintenance planning that provides high-quality infrastructure for transporting goods and travelers. However, due to the lack of a budget for pavement monitoring and maintenance in Afghanistan, transportation networks and pavement condition data have not been widely acquired for the development of a pavement performance model. The main aim of this study is to use a machine learning technique to, for the first time, develop a pavement performance model for Afghanistan that uses simple, cost-effective, and fairly accurate data—collected via smartphones—and that is based on a case study of over 550 km of Afghanistan’s highways. First, the current condition of Afghanistan’s road network is investigated using a smartphone. Then, collected data are prepared and analyzed so as to estimate the pavement condition index (PCI). Finally, a pavement performance model for PCI is developed using pavement age with an adequate coefficient of determination of 0.70 and successfully validated. It is concluded that the proposed approach is efficient and effective when developing a performance model in other developing countries encountering such data and budget limitations.
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(This article belongs to the Section Infrastructures Inspection and Maintenance)
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Open AccessReview
State of the Art Review of Ageing of Bituminous Binders and Asphalt Mixtures: Ageing Simulation Techniques, Ageing Inhibitors and the Relationship between Simulated Ageing and Field Ageing
Infrastructures 2024, 9(1), 8; https://doi.org/10.3390/infrastructures9010008 - 02 Jan 2024
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Asphalt mixtures age during service in the field, primarily as the result of chemical changes in the bituminous binder phase. The ageing phenomenon changes the properties of the asphalt mixture, including the stiffness modulus, the resistance to deformation and the resistance to cracking,
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Asphalt mixtures age during service in the field, primarily as the result of chemical changes in the bituminous binder phase. The ageing phenomenon changes the properties of the asphalt mixture, including the stiffness modulus, the resistance to deformation and the resistance to cracking, and it leads to surface weathering or erosion that often leads to pavement resurfacing. Consequently, many researchers have attempted to understand and to simulate the ageing of bituminous binders and asphalt mixtures in the laboratory. This review of bituminous binder and asphalt mixture ageing considers ageing simulation techniques, the effect of ageing on both bituminous binders and asphalt mixtures, the potential benefits of ageing inhibitors, and efforts to relate simulated laboratory ageing to observed field ageing. It is concluded that ageing has a significant effect on the properties of bituminous binders and asphalt mixtures, and that improved simulated ageing is important for comparing the effect of ageing on different materials and mixtures, as well as for quantifying the potential benefits of ageing inhibitors, which have generally been promising. It is also concluded that current ageing protocols are based on heat only, omitting the important contribution of solar radiation to the weathering and ageing of asphalt surfaces in the field. In the future, different simulated ageing protocols should be developed for binder and mixture samples. Similarly, a different ageing protocol is appropriate for understanding base-layer fatigue, compared to research on surface-layer weathering. Finally, it is concluded that a universal ageing protocol is unlikely to be found and that mixture- and climate-specific protocols need to be developed. However, given the importance of simulated ageing to asphalt researchers, the development of reliable, robust and calibrated laboratory ageing protocols is essential for the future.
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Open AccessArticle
Conceptual Design of Public Charging Stations for Freight Road Transport
by
, , , , , and
Infrastructures 2024, 9(1), 7; https://doi.org/10.3390/infrastructures9010007 - 27 Dec 2023
Abstract
We present a comprehensive methodology for a two-step approach to address the task at hand. The first step involves the optimal placement of charging stations, while the second step focuses on determining the necessary capacity of the charging stations based on traffic factors.
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We present a comprehensive methodology for a two-step approach to address the task at hand. The first step involves the optimal placement of charging stations, while the second step focuses on determining the necessary capacity of the charging stations based on traffic factors. This methodology is applicable to countries, states, or specific areas where the placement and optimization of charging stations for truck road transport are being considered. We identify the key inputs required for solving such a task. In the results section, we demonstrate the outcomes using a model example for the Czech Republic.
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(This article belongs to the Special Issue Sustainable and Digital Transformation of Road Infrastructures)
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On the Generation of Digital Data and Models from Point Clouds: Application to a Pedestrian Bridge Structure
Infrastructures 2024, 9(1), 6; https://doi.org/10.3390/infrastructures9010006 - 25 Dec 2023
Abstract
This study investigates the capture of digital data and the development of models for structures with incomplete documentation and plans. LiDAR technology is utilized to obtain the point clouds of a pedestrian bridge structure. Two different point clouds with varying densities, (i) fine
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This study investigates the capture of digital data and the development of models for structures with incomplete documentation and plans. LiDAR technology is utilized to obtain the point clouds of a pedestrian bridge structure. Two different point clouds with varying densities, (i) fine (11 collection locations) and (ii) coarse (4 collection locations), collected via terrestrial LiDAR, are analyzed to generate geometry and structural sections. This geometry is compared to the structural plans, which are then converted into numerical models (finite element—FE model) based on the point cloud data. Point cloud-based FE models (based on fine and coarse data) are compared with the structural plan-based FE model. It is observed that the static and dynamic responses are comparable within an acceptable range of a maximum difference of 5.5% for static deformation and an 8.23% frequency difference, with an average difference of less than 5%. Additionally, the dynamic properties of the fine and coarse point cloud FE models are compared with the operational modal analysis data obtained from the bridge. The fine and course point-cloud-based FE models, without model calibration, achieve an average accuracy of 8.76% and 9.94% for natural frequencies and a 0.89 modal assurance criterion value. The research found that the digital data generation yields promising results in this case for a bridge if documentation or plans are unavailable. With recent technologies and approaches such as digital twins, the connection between physical and virtual entities needs to be established by fusing digital models, sensorial information, and other data forms for better infrastructure management. Models such as those investigated and discussed in this paper can assist engineers with structural preservation in conjunction with monitoring data and utilization for digital twins.
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(This article belongs to the Special Issue Advances in Structural Health Monitoring of the Built Environment)
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Prediction of the Response of Masonry Walls under Blast Loading Using Artificial Neural Networks
Infrastructures 2024, 9(1), 5; https://doi.org/10.3390/infrastructures9010005 - 25 Dec 2023
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A methodology to predict key aspects of the structural response of masonry walls under blast loading using artificial neural networks (ANN) is presented in this paper. The failure patterns of masonry walls due to in and out-of-plane loading are complex due to the
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A methodology to predict key aspects of the structural response of masonry walls under blast loading using artificial neural networks (ANN) is presented in this paper. The failure patterns of masonry walls due to in and out-of-plane loading are complex due to the potential opening and sliding of the mortar joint interfaces between the masonry stones. To capture this response, advanced computational models can be developed requiring a significant amount of resources and computational effort. The article uses an advanced non-linear finite element model to capture the failure response of masonry walls under blast loads, introducing unilateral contact-friction laws between stones and damage mechanics laws for the stones. Parametric finite simulations are automatically conducted using commercial finite element software linked with MATLAB R2019a and Python. A dataset is then created and used to train an artificial neural network. The trained neural network is able to predict the out-of-plane response of the masonry wall for random properties of the blast load (standoff distance and weight). The results indicate that the accuracy of the proposed framework is satisfactory. A comparison of the computational time needed for a single finite element simulation and for a prediction of the out-of-plane response of the wall by the trained neural network highlights the benefits of the proposed machine learning approach in terms of computational time and resources. Therefore, the proposed approach can be used to substitute time consuming explicit dynamic finite element simulations and used as a reliable tool in the fast prediction of the masonry response under blast actions.
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Open AccessArticle
Topographic Measurements and Statistical Analysis in Static Load Testing of Railway Bridge Piers
Infrastructures 2024, 9(1), 4; https://doi.org/10.3390/infrastructures9010004 - 22 Dec 2023
Abstract
The aim of the paper is to identify a suitable method for assessing the deformation of structures (buildings, bridges, walls, etc.) by means of topographic measurements of significant targets positioned on the infrastructure under consideration. In particular, the paper describes an approach to
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The aim of the paper is to identify a suitable method for assessing the deformation of structures (buildings, bridges, walls, etc.) by means of topographic measurements of significant targets positioned on the infrastructure under consideration. In particular, the paper describes an approach to testing a bridge in a mixed structure (concrete and steel). The methodological approach developed can be schematised into the following main phases: (i) surveying using total stations (TSs) in order to obtain the spatial coordinates of the targets by means of the three-dimensional intersection technique (planimetric and altimetric measurements); (ii) least-squares compensation for the measurements performed; (iii) displacement analysis; and (iv) statistical evaluation of the reliability of the results. This method was evaluated on a case study of a newly built double-track railway bridge, located near the metropolitan area of the city of Bari, Italy, during various loading and unloading activities. The results obtained, evaluated by means of certain statistical tests, made it possible to verify the structural suitability of the bridge.
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(This article belongs to the Special Issue Advances in Structural Health Monitoring of the Built Environment)
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Deep Learning-Based Steel Bridge Corrosion Segmentation and Condition Rating Using Mask RCNN and YOLOv8
Infrastructures 2024, 9(1), 3; https://doi.org/10.3390/infrastructures9010003 - 20 Dec 2023
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The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application of convolutional neural networks (CNNs) for
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The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application of convolutional neural networks (CNNs) for corrosion detection and classification. However, current approaches primarily involve detecting corrosion within bounding boxes, lacking the segmentation of corrosion with irregular boundary shapes. As a result, it becomes challenging to quantify corrosion areas and severity, which is crucial for engineers to rate the condition of structural elements and assess the performance of infrastructures. Furthermore, training an efficient deep learning model requires a large number of corrosion images and the manual labeling of every single image. This process can be tedious and labor-intensive. In this project, an open-source steel bridge corrosion dataset along with corresponding annotations was generated. This database contains 514 images with various corrosion severity levels, gathered from a variety of steel bridges. A pixel-level annotation was performed according to the Bridge Inspectors Reference Manual (BIRM) and the American Association of State Highway and Transportation Officials (AASHTO) regulations for corrosion condition rating (defect #1000). Two state-of-the-art semantic segmentation algorithms, Mask RCNN and YOLOv8, were trained and validated on the dataset. These trained models were then tested on a set of test images and the results were compared. The trained Mask RCNN and YOLOv8 models demonstrated satisfactory performance in segmenting and rating corrosion, making them suitable for practical applications.
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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
A Generic Component for Analytic Hierarchy Process-Based Decision Support and Its Application for Postindustrial Area Management
Infrastructures 2024, 9(1), 2; https://doi.org/10.3390/infrastructures9010002 - 20 Dec 2023
Abstract
This paper presents a generic component for Analytic Hierarchy Process (AHP)-based decision support in risk management. The component was originally dedicated to railway transportation issues; however, its generality enabled it to extend its functionality for other domains too. To show the generality of
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This paper presents a generic component for Analytic Hierarchy Process (AHP)-based decision support in risk management. The component was originally dedicated to railway transportation issues; however, its generality enabled it to extend its functionality for other domains too. To show the generality of the module and possibility of its application in other domains, an environmental case was run. Its goal was to select methods for planning the post-mining heap revitalization process, especially decision-making focusing on the selection of the most advantageous revitalization option on the basis of the Analytic Hierarchy Process and different, non-financial factors, e.g., social, environmental, technological, political, etc. Taking into account expert responses, the suggested solution was related to energy production.
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(This article belongs to the Special Issue Railway in the City (RiC))
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Stochastic Simulation of Construction Methods for Multi-purpose Utility Tunnels
Infrastructures 2024, 9(1), 1; https://doi.org/10.3390/infrastructures9010001 - 19 Dec 2023
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The traditional method of installing underground utilities (e.g., water, sewer, gas pipes, electrical cables) by burying them under roads has been used for decades. However, the repeated excavations related to this method cause problems, such as traffic congestion and business disruption, which can
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The traditional method of installing underground utilities (e.g., water, sewer, gas pipes, electrical cables) by burying them under roads has been used for decades. However, the repeated excavations related to this method cause problems, such as traffic congestion and business disruption, which can significantly increase financial and social costs. Multi-purpose Utility Tunnels (MUTs) are a good alternative for buried utilities. Although the initial cost of MUTs is higher than that of the traditional method, social cost savings make them more feasible, especially in dense urban areas. Different factors, such as the specifications of utilities, the location of the MUTs, and the construction method, should be investigated to determine if MUTs can be an economical and practical alternative. The construction method is one of the most important factors to assess to have a successful MUT project and reduce its impact on the surrounding area. Simulation can be used to investigate the different construction methods of MUTs. In this paper, two Stochastic Discrete Event Simulation models depicting two MUT construction methods (i.e., microtunneling and cut-and-cover) are developed to analyze the duration and cost of the MUT projects. Also, 4D simulation models of these methods are developed for constructability assessment of these projects.
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(This article belongs to the Section Infrastructures Materials and Constructions)
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A Practical Data Extraction, Cleaning, and Integration Method for Structural Condition Assessment of Highway Bridges
Infrastructures 2023, 8(12), 183; https://doi.org/10.3390/infrastructures8120183 - 18 Dec 2023
Abstract
The success of regional bridge condition assessment, a crucial component of systematic maintenance strategies, relies heavily on comprehensive, well-structured regional bridge databases. This study proposes the data extraction, cleaning, and integration method for the construction of such databases. First, this research proposes an
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The success of regional bridge condition assessment, a crucial component of systematic maintenance strategies, relies heavily on comprehensive, well-structured regional bridge databases. This study proposes the data extraction, cleaning, and integration method for the construction of such databases. First, this research proposes an extraction method tailored for unstructured data often present in inspection reports. Additionally, this paper meticulously outlines a cleaning procedure designed to rectify two distinct categories of typical errors that are present within the inspection data. Subsequently, this study takes a holistic approach by establishing integration rules that harmonize data from various sources, including inspection records, monitoring data, traffic statistics, as well as design and construction blueprints. The architectural framework of the regional bridge information database is then meticulously laid out. To validate and demonstrate the effectiveness of the method, this study applies them to a set of representative highway bridges situated within Shandong Province. The results show that this approach can be used to successfully establish a functional regional bridge database. The database plays a pivotal role in harnessing the latent potential of an extensive range of multi-source information and propels the field of bridge condition assessment forward by providing a solid basis for informed decision making and strategic planning in the realm of infrastructure maintenance.
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(This article belongs to the Topic AI Enhanced Civil Infrastructure Safety)
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Open AccessReview
Demolition Waste Glass Usage in the Construction Industry
Infrastructures 2023, 8(12), 182; https://doi.org/10.3390/infrastructures8120182 - 17 Dec 2023
Abstract
Waste glass is an endless issue for the majority of the countries in the world with a linear economy of usage of materials. Demolition waste is counted as part of total construction and demolition waste (CDW). Even today, there are some statistical problems
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Waste glass is an endless issue for the majority of the countries in the world with a linear economy of usage of materials. Demolition waste is counted as part of total construction and demolition waste (CDW). Even today, there are some statistical problems with the quantification of demolition waste and dividing it from total CDW, since most countries do not provide such a division of waste types. The current review shows possible ways of utilizing waste glass in some useful products in the construction industry. It is elaborated using PRISMA@ methodology with bibliometric and qualitative methods to provide a systematical overview of the publications in the period from 2000 to 2023. The bibliometric search was handled with the application RStudio© using sources in the biggest database, Scopus. Most of the published research items are mainly focused on using waste glass in concrete applications. However, there are seven possible areas of waste glass application in the construction industry: concrete products, gypsum–cement composites, asphalt or concrete pavement, geopolymer mortars, foamed glass ceramics, glass ceramics, and soil foundation strengthening/stabilization. In its turn, the circular economy should be applied since it provides a prolonged turnaround of materials throughout their life cycle.
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(This article belongs to the Section Infrastructures Materials and Constructions)
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Open AccessArticle
Indexing the Maintenance Priority of Road Safety Barriers in Urban and Peri-Urban Contexts: Application of a Ranking Methodology in Bologna, Italy
by
, , , , and
Infrastructures 2023, 8(12), 181; https://doi.org/10.3390/infrastructures8120181 - 16 Dec 2023
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The need for clear and updated information is pivotal when authorities plan and perform routinary, periodic and emergency maintenance of both road network and their roadside assets, e.g., curbs, signals, and barriers. With particular regard to road barriers, the development of remote sensing
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The need for clear and updated information is pivotal when authorities plan and perform routinary, periodic and emergency maintenance of both road network and their roadside assets, e.g., curbs, signals, and barriers. With particular regard to road barriers, the development of remote sensing technologies, such as Laser Imaging Detection and Ranging (LiDAR), has played a disruptive role in acquiring information, so the surveys today are predominantly automatic, faster, and less biased than the traditional (i.e., visual and manual) inventorying methodologies. However, even though they are accurate, these emerging procedures usually focus only on the surveyed elements and do not provide any other information about the surrounding environment or about the qualitative degradation of the elements. The primary objective of this research effort was to present a ranking methodology for enhancing road safety in urban contexts. Due to an innovative synthetic index which takes into account both the deterioration and the location of the surveyed elements, maintenance priority of road barriers was outlined in Bologna, Italy. All the collected information was georeferenced in a Geographic Information System (GIS) environment and hence plotted in thematic maps for an easier analysis. In addition, compliance to the norm was verified. The research was tested to provide public authorities with an effective tool in the evaluation of maintenance activities and road safety policies.
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Open AccessArticle
Predicting Trajectories of Plate-Type Wind-Borne Debris in Turbulent Wind Flow with Uncertainties
Infrastructures 2023, 8(12), 180; https://doi.org/10.3390/infrastructures8120180 - 15 Dec 2023
Abstract
Debris poses multifaceted risks and jeopardizes various aspects of the environment, human health, safety, and infrastructure. The debris trajectory in turbulent wind flow is more dispersed due to the inherent randomness of the turbulent winds. This paper investigates the three-dimensional trajectories of plate-type
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Debris poses multifaceted risks and jeopardizes various aspects of the environment, human health, safety, and infrastructure. The debris trajectory in turbulent wind flow is more dispersed due to the inherent randomness of the turbulent winds. This paper investigates the three-dimensional trajectories of plate-type wind-borne debris in turbulent wind fields via the method of numerical simulation. A 3D probabilistic trajectory model of plate-type wind-borne debris is developed. The debris trajectories are numerically calculated by solving the governing equation of debris motion and by introducing turbulent wind flows based on the near-ground wind field measured in the wind tunnel to account for the probability characteristics of the debris trajectory. The dimensionless velocities and displacements of the debris trajectory show good agreement with the experimental data in wind tunnel tests, confirming the rationality of the probabilistic trajectory model. Based on the validated trajectory model, the probability characteristics of the debris impact position, impact velocity, and kinetic energy, debris angular displacement, and angular velocity are analyzed in detail under five different wind attack angles. The proposed probabilistic model of plate-type debris in turbulent wind flow provides an accurate and effective method for predicting debris trajectory in three-dimensional space.
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(This article belongs to the Topic AI Enhanced Civil Infrastructure Safety)
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Open AccessArticle
Improvements in Urban Rapid Transit Boarding and Alighting Safety during System Modernization
by
and
Infrastructures 2023, 8(12), 179; https://doi.org/10.3390/infrastructures8120179 - 15 Dec 2023
Abstract
Urban rail transport has advantages that determine its particular usefulness. However, despite decades of technical development, it is still difficult to speak about satisfactory solutions. Safe, independent access to this transport and public infrastructure for passengers with reduced mobility (PRM) is an essential
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Urban rail transport has advantages that determine its particular usefulness. However, despite decades of technical development, it is still difficult to speak about satisfactory solutions. Safe, independent access to this transport and public infrastructure for passengers with reduced mobility (PRM) is an essential element of civil rights and an interesting subject of scientific research. In relation to that, the interface between rail vehicle and platform, despite multiple efforts aiming at improving this situation, is one of the hardest problems to overcome. This paper presents a summary and analyses of distinctive features of selected transit systems that are interesting from the viewpoint of finding various solutions to improve the safety of passengers on platforms. This analysis led to preparation of a new, improved standard of the vehicle–platform interface, illustrated with an example of the city of Wrocław, as discussed further in this paper. Some of the main conclusions of this paper are that insufficient progress has been made with developing the vehicle–platform interface, there are a multitude of systems and ways of (more or less effectively) ensuring independent access for PRM, and further research and development work is needed to optimize engineering solutions in this domain so they are both sustainable and economical.
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(This article belongs to the Special Issue Railway in the City (RiC))
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Battery Electric Buses or Fuel Cell Electric Buses? A Decarbonization Case Study in the City of Brescia, Italy
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Infrastructures 2023, 8(12), 178; https://doi.org/10.3390/infrastructures8120178 - 11 Dec 2023
Abstract
Nowadays, designing and adopting sustainable and greener transport systems is of upmost interest. The European Commission and different EU countries are developing plans and programs—but also delivering resources—aimed at the decarbonization of cities and transport by 2030. In this paper, the case study
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Nowadays, designing and adopting sustainable and greener transport systems is of upmost interest. The European Commission and different EU countries are developing plans and programs—but also delivering resources—aimed at the decarbonization of cities and transport by 2030. In this paper, the case study of the city of Brescia, a city of about 200,000 inhabitants located in northern Italy, is addressed. Specifically, a preliminary operational and financial feasibility study is performed assuming the replacement of the entire compressed natural gas (CNG) powered bus fleet of a specific line; the two alternatives considered are battery electric buses (BEBs) and fuel cell electric buses (FCEBs). For the comparison and evaluation of the two alternatives, specific economic parameters of the three alternatives (BEB, FCEB and the current solution CNGB) were considered: CAPEX (CAPital EXpenditure) and OPEX (OPerational EXpenditure). This allowed us to determine the TCO (total cost of ownership) and TCRO (total cost and revenues of ownership) along three annuities (2022, 2025 and 2030). For the BEB alternative, the TCO and TCRO values are between EUR 0.58/km and EUR 0.91/km. In the case of the FCEB solution, the values of TCO and TCRO are between EUR 1.75/km and EUR 2.15/km. Considering the current CNGB solution, the TCO and TCRO values range between EUR 1.43/km and EUR 1.51/km.
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(This article belongs to the Special Issue Sustainable Infrastructures for Urban Mobility)
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