Infrastructures

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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 (a_v/d), and reinforcement ratios (p_s, p_v, and p_h). 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. Full article

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. Full article

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. Full article

The theoretical and practical studies of the cyclic loads resulting from the movement and passage of trains on the unsaturated subgrade to determine the effect of the degree of saturation and moisture content on the foundations and infrastructure of the railway lines, especially the settlement in the railway lines as a result of the development of the train loads. Thirty-six laboratory experiments were carried out using models that simulate a railway with nearly half the scale of the real one, using an iron box of (1.5 × 1.0 × 1.0) meters and a layer of clay soil with a thickness of 0.5 m representing the base layer, were constructed inside it. Above it, there is a layer of crushed stone representing a 0.2 m thick ballast, topped by a rail line of 0.8 m long installed on three sleeper beams with dimensions of 0.9 m (0.1 × 0.1 m). The subgrade layer has been constructed at different saturation degrees as follows: 100, 80, 70, and 60%. The tests were carried out using different load amplitudes and frequencies. These experiments investigated the effect of the subgrade degree of saturation on the value of the stresses generated on the surface and the middle (vertical and lateral stresses) and the settlement of the subgrade. In the case of unsaturated subgrade soil, an increase in load frequency has a clear effect on increasing the generated stresses in the subgrade layer, especially with lower saturation levels. However, the results and measurements of these experiments found that the load frequency almost had no effect on the values of the stresses generated on the surface and inside the subgrade layer with a 100% degree of saturation. The results of the investigation demonstrated that, while load frequency had a minimal effect on track-panel settlement, it increased with the load amplitude and subgrade soil saturation degree. The change of settlement of the track panel with the number of cycles has a high rate at the beginning; after a while from that, it decreases gradually until, after some value of the number of cycles, the settlement changes at a very low rate and gradually. Full article

The remarkable impact that e-scooters have had on the transportation system drives research on this phenomenon. The widespread use of e-scooters also poses several new safety issues, which should be necessarily studied. The aim of this paper points in this direction, investigating the main contributing factors, causes, and patterns of recorded e-scooter crashes, considering also different crash types and severity, using the City of Bari (Italy) as a case study. The crash dataset based on police reports and referring to the period July 2020–November 2022 (i.e., the first period of e-scooter implementation in the City of Bari) was investigated. Crashes were clustered according to several variables. No fatal crashes occurred, even though crashes mostly resulted in injuries (70%). Considering road type, divided roads were found to be less safe than undivided ones, due to higher mean speeds than on other roads and to a less constrained e-scooter driving behavior. Calm (off-peak) daytime hours seem to lead to more frequent e-scooter crashes with respect to both peak and nighttime hours, even if the latter hours are associated with an increased severity. Once controlled for exposure, season, lighting conditions, and the private/sharing ratio do not seem influential. E-scooters are more prone to be involved in single-vehicle and pedestrian crashes at segments than other vehicles, but they show similar crash trends than other vehicles (i.e., angle crashes) at intersections. As emerged from traffic surveys, not all e-scooter users were found to use cycle paths. Combining this information with crash data, it seems that not using cycle paths is considerably less safe than using them. Besides engineering measures and policies, awareness campaigns should be promoted to elicit safe users’ behavior and to tackle the several violations and misbehaviors emerging from the crash data. Full article

Train configurations give rise to a primary wagon pass forcing frequency and their multiples. When any one of these frequencies coincides with the natural frequency of vibration of the bridge, a resonant response can occur. This condition can amplify the dynamic response of the bridge, leading to increased levels of displacement, stresses and acceleration. Increased stress levels on critical bridge structural elements increases the rate at which fatigue damage accumulates. Increased bridge acceleration levels can affect passenger comfort, noise levels, and can also compromise train safety. For older bridges the effects of fatigue, and being able to predict the remaining life, has become a primary concern for bridge engineers. Better understanding of the sensitivity of fatigue damage to the characteristics of the passing train will lead to more accurate remaining life predictions and can also help to identify optimal train speeds for a given train–bridge configuration. In this paper, a mathematical model which enables the dynamic response of railway bridges to be assessed for different train configurations is presented. The model is based on the well established closed from solution of the Euler–Bernoulli Beam (EBB) model, for a series of moving loads, using the inverse Laplace–Carson transform. In this work the methodology is adapted to allow different train configurations to be easily implemented into the formulation in a generalised form. A generalised equation, which captures the primary wagon pass frequency for any train configuration, is developed and verified by presenting the results of the bridge response in the frequency domain. The model, and the accuracy of the equation for predicting the primary wagon pass frequency, is verified using independently obtained measured field train–bridge response data. The main emphasis of this work is to enable the practicing engineer, railway operators and bridge asset owners, to easily and efficiently make an initial assessment of dynamic amplification, and the optimal train speeds, for a given bridge and train configuration. This is visually presented in this work using a Campbell diagram, which shows dynamic amplification and compares this with those calculated based on the design code, across a range of train speeds. The diagram is able to identify train speeds at which a resonance response can occur, and the wagon pass frequency, or its multiples, which are causing the increased dynamic amplification. The model is implemented in Matlab and demonstrated by analysing a range of short- to medium-single span simply supported plate girder railway bridges, typically found on the UK railway network, using the standard BS-5400 train configurations. The model does not consider the effects of the train mass and suspension system as this would require a non-closed form numerical solution of the problem which is not practical for the purposes of an initial assessment of the train–bridge interaction problem. Full article

Patching is a common technology used in repairing asphalt-pavement potholes. Due to the differences in material properties between patched- and unpatched-asphalt mixtures, significant strain and stress concentrations could be induced; thus, further cracks and interfacial debonding distress could be caused. As a remedy, the strain and stress concentrations can be alleviated by utilizing optimum patching shapes. Therefore, this paper employed finite element methods (FEM) to deeply analyze the mechanical performance of patched-asphalt pavements embedded with different patching shapes. Three patching shapes, these being rectangular, stair, and trapezoid, were considered for use in pavement pothole repairs based on two- and three-dimensional finite element models. In the two-dimensional models, Top-Down and Bottom-Up crack propagations were simulated to assess the anti-damage performance of the patched pavements with different patching shapes. In addition, the thermal stress behaviors within patched-asphalt pavements were simulated using the two-dimensional model to analyze the performance of the patched pavements during the cooling process in construction. In addition, interface-debonding performance was simulated for the patched-asphalt pavements using three-dimensional models. In light of the simulation results, engineers are expected to better understand the mechanism within patched pavements and to improve the quality of the pavement patching. Full article

The safety of roads in urban areas is a major concern for governments, demanding innovative solutions to enhance pedestrian safety. This paper introduces a novel approach to crosswalks by integrating resin with photoluminescent additives, offering a significant boost to road safety. A thorough methodology was employed to assess its effectiveness, covering mechanical, lighting, and vibroacoustic aspects, alongside a photogrammetric analysis of real-world experiments. The material exhibited noteworthy mechanical properties, displaying consistent tensile strength, load capacity, and strain values with a remarkable Shore A hardness. After 20 min, luminance values peaked at 68 mcd/m², surpassing standard vehicle headlights at 100 m. Additionally, vibroacoustic analysis highlighted a noticeable relationship between vehicle speed and sound bandwidth, indicating the system’s potential to alert pedestrians. Tests revealed that the proposed system significantly decreased the average vehicle speed by 36.96% compared to conventional crosswalks, with a 27.80% reduction when drivers yielded to pedestrians. Furthermore, a survey involving 35 participants, focusing on the knowledge of road safety regulations, behavior, signage, and visibility, found positive results regarding accident reduction. The estimations indicate potential decreases of 26.26% in injuries and 35.4% in fatalities due to improved road conditions, 26.58% in injuries and 53.16% in fatalities resulting from reduced average speeds, and 52.56% in injuries and 79.91% in fatalities through enhanced road education. This underscores the multifaceted impact of the system on urban road safety. Full article

To assess the safety performance of crash cushions, guidelines or standards are used. Real-life accident conditions might deviate substantially from the approval test conditions. The objective of this study is to evaluate occupant safety in passenger cars in the event of an impact against a crash cushion. Real-life accident configurations deviate significantly from the impact configurations used in the approval test EN 1317. In four different tests, two vehicles regularly used in EN 1317 and two vehicles with improved safety equipment (airbag, pretensioner, and load limiter) are used. The impact speed is 100 km/h, whereas the crash cushion is designed for an impact speed of 80 km/h. One configuration is defined as a full overlap, and one has a 50% offset. The ASI (Acceleration Severity Index), THIV/OIV (Theoretical Head Impact Velocity/Occupant Impact Velocity), and PHD/ORA (Post Head Deceleration/Occupant Ride down Acceleration) are calculated from the acceleration signals. The offset impact was more serious for both the regularly used vehicle and the vehicle with improved safety equipment. Vehicles with improved safety equipment do not have any influence on these criteria. It is apparent that new occupant safety technologies will not have any influence on occupant safety performance. The criteria currently in use are more likely to be of use for assessing vehicle performance rather than occupant safety. Full article

In the realm of transportation system management, various remote sensing techniques have proven instrumental in enhancing safety, mobility, and overall resilience. Among these techniques, Light Detection and Ranging (LiDAR) has emerged as a prevalent method for object detection, facilitating the comprehensive monitoring of environmental and infrastructure assets in transportation environments. Currently, the application of Artificial Intelligence (AI)-based methods, particularly in the domain of semantic segmentation of 3D LiDAR point clouds by Deep Learning (DL) models, is a powerful method for supporting the management of both infrastructure and vegetation in road environments. In this context, there is a lack of open labeled datasets that are suitable for training Deep Neural Networks (DNNs) in transportation scenarios, so, to fill this gap, we introduce ROADSENSE (Road and Scenic Environment Simulation), an open-access 3D scene simulator that generates synthetic datasets with labeled point clouds. We assess its functionality by adapting and training a state-of-the-art DL-based semantic classifier, PointNet++, with synthetic data generated by both ROADSENSE and the well-known HELIOS++ (HEildelberg LiDAR Operations Simulator). To evaluate the resulting trained models, we apply both DNNs on real point clouds and demonstrate their effectiveness in both roadway and forest environments. While the differences are minor, the best mean intersection over union (MIoU) values for highway and national roads are over 77%, which are obtained with the DNN trained on HELIOS++ point clouds, and the best classification performance in forested areas is over 92%, which is obtained with the model trained on ROADSENSE point clouds. This work contributes information on a valuable tool for advancing DL applications in transportation scenarios, offering insights and solutions for improved road and roadside management. Full article