Infrastructures, Volume 9, Issue 3 (March 2024) – 28 articles

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

Civil structural health monitoring (CSHM) tracks different aspects of an infrastructure system’s service and safety condition by utilizing reliably measured data and physics-based model simulations. Data and physical models are coupled with heuristic experience to proactively represent current and expected future performance. In the past two decades, more bridges and dams have been instrumented and monitored during and after construction to determine their performances and responses to various loading, material, boundary, and environmental conditions. Furthermore, bridge and dam owners increasingly utilize civionics systems to obtain essential data for developing data-driven asset management programs and addressing the state of good repair requirements. Full article

New or in-service truss bridges, with or without upper bracing systems, may display instability phenomena such as general lateral torsional buckling of the upper chord. The buckling of structural elements, particularly in the case of steel bridges, can be associated with the risk of collapse or temporary/permanent withdrawal from service. Such incidents have occurred in the case of several bridges in different countries: the collapse of the Dee bridge with truss girders in 1847 in Cheshire, England; the collapse of the semi-parabolic truss girder bridge near Ljubičevo over the Morava River in Serbia in 1892; the collapse of the Dysart bridge in Cambria County, Pennsylvania in 2007; the collapse of the Chauras bridge in Uttarakhand, India in 2012; and the collapse of a bridge in Nova Scotia, Canada (2020), and such examples may continue. Buckling poses a significant danger as it often occurs at lower load values compared to those considered during the design phase. Additionally, this phenomenon can manifest suddenly, without prior warning, rendering intervention for its prevention impossible or futile. In contemporary times, most research and design calculation software offer the capability to establish preliminary values for buckling loads, even for highly intricate structures. This is typically achieved through linear eigenvalue buckling analyses, often followed by significantly more complex large displacement nonlinear analyses. However, interpreting the results for complex bridge structures can be challenging, and their accuracy is difficult to ascertain. Consequently, this paper aims to introduce an original method for a more straightforward estimation of the buckling load of the upper chord in steel truss bridges. This method utilizes the theory of beams on discrete elastic supports. The buckling load of the upper chord was determined using both the finite element method and the proposed methodology, yielding highly consistent results. Full article

Creating new multimodal infrastructure in an existing transport network of an urban city is a challenging process. The responsible transport authorities have to pay special attention to the details regarding the accessibility and effectiveness of the new development, to avoid travelers’ confusion and network congestion. The subject of this paper is the assessment and optimization of the traffic network in the surroundings of the new multimodal depot of Thessaloniki’s future metro system with the use of the microsimulation software PTV VISSIM (version 2022). Five different scenarios were developed in collaboration with the city’s transport authority and evaluated into two stages, beginning with the whole traffic network, and then continuing with the analyzed intersections separately. The evaluation is based on Key Performance Indicators (KPIs), which were extracted by the software. According to the results of the base case scenario, the network functions satisfactorily, with slight delays. Regarding the future network, the operation of the new hub will strongly increase the traffic demand, while the proposed traffic network adjustments by the local authorities seem to cause significant delay problems. This paper aims to highlight the importance of using modeling tools during the design phase of a new infrastructure to create efficient, accessible, and sustainable infrastructures that enhance the public transport system. Full article

The railway industry is seeking high-performance and sustainable solutions for sub-ballast materials, particularly in light of increasing cargo transport demands and climate events. The meticulous design and construction of track bed geomaterials play a crucial role in ensuring an extended track service life. The global push for sustainability has prompted the evaluation of recycling ballast waste within the railway sector, aiming to mitigate environmental contamination, reduce the consumption of natural resources, and lower costs. This study explores materials for application and compaction using a formation rehabilitation machine equipped with an integrated ballast recycling system designed for heavy haul railways. Two recycled ballast-stabilised soil materials underwent investigation, meeting the necessary grain size distribution for the proper compaction and structural conditions. One utilised a low-bearing-capacity silty sand soil stabilised with recycled ballast fouled waste (RFBW) with iron ore at a 3:7 weight ratio, while the second was stabilised with 3% cement. Laboratory tests were conducted to assess their physical, chemical, and mechanical properties, and a non-linear elastic finite element numerical model was developed to evaluate the potential of these alternative solutions for railway sub-ballast. The findings indicate the significant potential of using soils stabilised with recycled fouled ballast as sub-ballast for heavy haul tracks, underscoring the advantages of adopting sustainable sub-ballast solutions through the reuse of crushed deteriorated ballast material. Full article

Railway transportation is widely recognized as an environment-friendly and sustainable means for conveying freight and passengers over long distances. This article investigates the effectiveness of utilizing scrap tire rubber granules and geosynthetics to enhance track performance in response to the growing demands for railway transport and the consequent escalation of train-induced loading. A multi-faceted methodology, incorporating experimental, numerical, and analytical techniques, is employed to examine the efficacy of these sustainable approaches. Results from three-dimensional (3D) finite element (FE) analyses conducted on slab tracks for high-speed railways reveal that the addition of a resilient layer, comprising scrap tire rubber granules, reduces vertical stress within the track substructure. Laboratory investigations on an innovative composite material consisting of soil, scrap rubber granules, and polyurethane demonstrate its potential to enhance track performance. Findings from two-dimensional (2D) FE analyses conducted on pile-supported railway embankments highlight an enhanced transfer of load to the pile head following the installation of a geogrid layer at the embankment base. Finally, the results from the analytical approach indicate a reduction in track settlement and a decrease in the track geometry degradation rate on reinforcing the ballast layer with 3D cellular geoinclusion. The novelty of this study lies in the comprehensive assessment of the innovative composite material under drained and cyclic loading conditions, the investigation of the influence of train loading on geosynthetic tension and the load transfer mechanism in railway embankments, and the development of an innovative computational methodology capable of assessing the effectiveness of 3D cellular inclusions in improving the ballasted railway track performance. The findings from this article underscore the effectiveness of these sustainable approaches in mitigating the challenges posed by increased loads on railway tracks, providing valuable insights for the ongoing efforts to optimize railway transportation infrastructure. Full article

In recent years, the alarming number of terrorist attacks has highlighted the critical need for extensive research aimed at fortifying structures against explosion-induced loads. However, the insufficient energy absorption and brittleness of conventional concrete make it ineffective in withstanding blast loading, encouraging researchers to explore innovative strategies for augmenting the energy dissipation capabilities of construction materials. This study specifically delves into the incorporation of recycled rubber, a sustainable and environmentally friendly solution to the pressing issue of scrap tire disposal. The primary focus of this research revolves around the integration of rubber recycling and steel fibers into concrete, with the ultimate goal of enhancing the dynamic response of reinforced concrete (RC) beams. This novel approach not only contributes to the structural resilience required for resisting blast impacts, but also aligns with eco-friendly practices by reusing recycled rubber. A meticulous numerical investigation was undertaken to comprehensively assess the static and blast response of these augmented beams. The numerical study involved developing finite element (FE) models using ABAQUS version 6.14 for static implicit analysis and LS-DYNA R11 for blast explicit simulations. The ABAQUS model was validated against previous experimental testing for load–displacement and failure patterns. Similarly, the LS-DYNA model was validated for blast pressure in accordance with UFC-3-340 standards and for material response under blast loading, utilizing existing experimental data. The numerical models were designed to accommodate varying weight percentages of rubber, ranging from 5% to 20%, and a consistent 1.0% incorporation of steel fibers. This comprehensive analysis aims to provide valuable insights into the efficacy of these materials in improving the structural integrity and blast resistance of RC beams, thereby contributing to the development of more secure and sustainable construction practices. By reducing the reinforcement ratio in order to meet the minimum code requirements, it became evident that the failures of the rubberized RC beams tended to exhibit ductility on the tension side under static loading. In addition, the increase in the reinforcement ratio correlated with a higher failure load and decreased deflection. Furthermore, the findings indicated an optimal concrete mixture characterized by improved ductility, energy absorption, and blast load capacity, achieved by combining 5–10% rubber with steel fibers. Full article

To meet the United Nations and European Union goals of reducing road crash fatalities and injuries, it is also relevant to address the negative externalities due to mega-events on the road network and the local communities, to assess the safety of the road network involved, and to implement appropriate measures for different road environments. Despite their relevance, the literature often overlooks social costs and risks associated with mega-events. This study presents an operating framework for rapidly assessing the safety of the Milano–Cortina 2026—“Via Olimpica” road—which will host a significant proportion of the traffic during the Winter Olympic Games in 2026. The framework proposes a simplified Road Infrastructure Safety Management (RISM) to address the unique challenges posed by the limited time available for screening and implementation by local authorities. The framework integrates four data sources and follows a seven-step procedure. It provides recommendations for improving road safety by identifying critical road sections and blackspots. Road authorities, practitioners, and public administrations may all benefit from the framework, as it makes it easier to prioritise safety improvements within time constraints. Full article

Bus lanes play a crucial role in urban areas as their primary objective is to increase public transport efficiency and help traffic and public transit systems flow more smoothly. This study starts with traffic and climate monitoring to verify asphalt bus lanes in Rome, Italy, according to the Italian Pavement Design Catalogue published in 1995. KENLAYER software calculated the stress-strain conditions under real traffic loads (i.e., hourly passages of urban buses, considering their axle load and seat occupancy rate), typical subgrade bearing capacity (i.e., resilient modulus equal to 90 MPa), current climate conditions, and road material properties. Then, the Mechanistic-Empirical Pavement Design Guide (MEPDG) was used to verify the response of the pavement structure. The fatigue verification of bound materials resulted in damage values much lower than 1 at the end of the 20-year service life (i.e., 0.12 with the Asphalt Institute and 0.31 with the Marchionna law, respectively) and highlights that the Italian catalogue’s sheets are overdesigned. On the other hand, the rutting verification according to MEPDG is not satisfied after an 11-year service life (i.e., the total rutting is equal to 1.50 cm), forcing frequent and expensive maintenance of wearing and binder courses. Therefore, the results confirm the validity of the Italian catalogue for fatigue service life and suggest the need for high-performance asphalt to prevent early rutting due to bus traffic increasing by load and frequency in previous decades. Full article

Tunnels are underground infrastructures intended for diverse community applications as well as military applications. During impact loading due to high-velocity projectiles such as ballistic missiles, materials experience a high strain rate. Moreover, there is a superficial augmentation of the dynamic strength when geomaterials such as rock are subjected to a high strain rate. Despite this strength enhancement, tunnels can get damaged by the impact load of a projectile hitting at a high velocity if they are present at a shallow depth. The present study is an effort to comprehend the response of a shallow tunnel in soft sandstone due to the impact load by a ballistic projectile using the FEM-based software ABAQUS/CAE 6.11. The Drucker–Prager damage model and the Johnson–Cook damage model were used to define the properties of the rock mass and steel tunnel lining, respectively. The crown of the 3 m diameter tunnel was kept at different depths from 1 m to 5 m from the surface. A striking velocity of 1000 m/s at a normal position to the target was given to the projectile. The projectile caused noticeable damage to the tunnel lining up to 3 m crown depth. Increasing the crown depth had a positive effect on the maximum depth of the projectile penetration up to 4 m tunnel crown depth, after which the effect reversed, making the tunnel safer. The maximum von Mises stress on the tunnel lining reduced in a logarithmic trend with an increase in the crown depth, gradually lowering to an impact load lesser than the yield stress of the tunnel lining material after a crown depth of 4.5 m. Full article

Running a numerical model for a cracked arch dam that takes into account all the particularities of the materials and dam with a high level of detail has a great computational cost involved. For this reason, it is usual to simplify such a model in search of a simpler solution while preserving the characteristic of being representative, with all the particularities that the model of an arch dam has. A common simplification lies in not considering open transverse joints in the construction phase of a cracked dam. An aim of this study is to propose a methodology that combines open joints and cracking, something on which, to the authors’ knowledge, no studies have been published. An additional goal is a study of the need and adequacy of different approaches on performance (computational time) and its consequences for model accuracy. For this purpose, an accurate methodology for a stationary finite element method numerical simulation of deformations in cracked arch dams is presented. Using a tetrahedron mesh of a real dam, different simplifications commonly used in numerical models are compared. It is concluded that some of the standard simplifications produce a significant effect on the computation time and accuracy of the results. Full article

This research utilises statistical modelling to explore the impact of roadway infrastructure elements, primarily those related to cross-section design, on crash occurrences in urban areas. Cross-section design is an important step in the roadway geometric design process as it influences key operational characteristics like capacity, cost, safety, and overall functionality of the transport system entity. Evaluating the influence of cross-section design on these factors is relatively straightforward, except for its impact on safety, especially in urban areas. The safety aspect has resulted in inconsistent findings in the existing literature, indicating a need for further investigation. Negative binomial (NB) models are typically employed for such investigations, given their ability to account for over-dispersion in crash data. However, the low sample mean and under-dispersion occasionally exhibited by crash data can restrict their applicability. The generalised Poisson (GP) models have been proposed as a potential alternative to NB models. This research applies GP models for developing crash prediction models for urban road segments. Simultaneously, NB models are also developed to enable a comparative assessment between the two modelling frameworks. A six-year dataset encompassing crash counts, traffic volume, and cross-section design data reveals a significant association between crash frequency and infrastructure design variables. Specifically, lane width, number of lanes, road separation, on-street parking, and posted speed limit are significant predictors of crash frequencies. Comparative analysis with NB models shows that GP models outperform in cases of low sample mean crash types and yield similar results for others. Overall, this study provides valuable insights into the relationship between road infrastructure design and crash frequency in urban environments and offers a statistical approach for predicting crash frequency that maintains a balance between interpretability and predictive power, making it more viable for practitioners and road authorities to apply in real-world road safety scenarios. Full article

The recent emphasis on sustainable development in the construction industry has made it essential to develop construction and building materials that are not only affordable, but have minimal negative impact on the environment. This study investigates the valorisation of steel slag, which is mostly considered to be a waste material in several parts of the world, by blending with calcined impure kaolinitic clay to partially replace ordinary Portland cement (OPC) in the preparation of self-compacting concrete (SCC). OPC was substituted with steel slag at a constant level of 10%, whereas calcined clay replaced OPC at varying levels, ranging from 10 to 30% in a ternary blended mix. The hardened properties evaluated include compressive and flexural strengths. Samples containing only calcined clay showed a lower fluidity, which was significantly improved when steel slag was added to the mix. SCC containing 10% steel slag and 20% calcined clay obtained 28 days compressive strength, which was 3.6% higher than the reference cement concrete. An XRD analysis revealed a significant decrease in the peak heights of portlandite in mixtures containing steel slag and calcined clay, regardless of their replacement percentage. Generally, all the blended cement samples performed appreciably in resisting sulphate attack. The results of this study demonstrate that using steel slag and calcined clay together can significantly improve the fresh and hardened properties of SCC without compromising its mechanical properties. Full article

This study determines the equivalent stress intensity factor (SIF) model that best fits the experimental behavior of low-carbon steel under mixed modes ($I$ and $II$). The study assessed Tanaka, Richard, and Pook’s equivalent SIF models. The theoretical values used for comparison correspond to the experimental results in a modified C(T) geometry by machining a hole ahead of the crack tip subjected to fatigue loads with a load ratio of R = 0.1. The comparison involved the SIF for six experimental points and the values computed through the numerical simulation. The Paris, Klesnil, and Modified Forman–Newman crack growth models were used with each equivalent SIF to analyze the prediction in the estimated number of cycles. The Klesnil model showed the closest prediction since the error between the calculated and experimentally recorded number of cycles is the lowest. However, the material behavior reflects a reduced crack propagation rate attributed to plasticity in the crack tip. The results suggest that Asaro equivalent SIF conservatively estimates the element lifespan with increasing errors from 2.3% at the start of growth to 27% at the end of the calculation. This study sheds light on the accuracy and limitations of different equivalent SIF models, providing valuable insights for structural integrity assessments in engineering applications. Full article

Most recent tunnel designs rely on more thorough analyses of the intricate rock interactions. The three principal techniques for excavating rock tunneling are drill-and-blast for complete or partial cross-sections, TBM only for circular cross-sections with full faces, and road header for small portions. Tunnel-boring machines (TBM) are being utilized to excavate an increasing number of tunnels. Newer studies have demonstrated that subterranean structures such as tunnels produce a variety of consequences during and after ground shaking, challenging the long-held belief that they are among the most earthquake-resistant structures. Consequently, engineering assessment has become crucial for these unique structures from both the geotechnical and structural engineering standpoints. The designer should evaluate the underground structure’s safety to ensure it can sustain various applied loads, considering both seismic loads and temporary and permanent static loads. This paper investigates how adding elastic, soft material between a circular tunnel and the surrounding rock affects seismic response. To conduct the study, Midas/GTS-NX was used to model the TBM tunnel and the nearby rock using the finite element (F.E.) method to simulate the soil–tunnel interactions. A time–history analysis of the El Centro (1940) earthquake was used to calculated the stresses accumulated in the tunnels during seismic episodes. Peak ground accelerations of 0.10–0.30 g, relative to the tunnel axis, were used for excitation. The analysis utilized a time step of 0.02 s, and the duration of the seismic event was set at 10 s. Numerical models were developed to represent tunnels passing through rock, with the traditional grout pea gravel vs. isolation layer. A parametric study determined how isolation material characteristics like shear modulus, Poisson’s ratio, and unit weight affect tunnel-induced stresses. In the meantime, this paper details the effects of various seismic isolation materials, such as geofoam, foam concrete, and silicon-based isolation material, to improve protection against seismic shaking. The analysis’s findings are discussed, and how seismic isolation affects these important structures’ performance and safety requirements is explained. Full article

The design of road geometry is based on a rather elementary assumption that the user strictly follows the lane axis. Based on this hypothesis, the ideal trend of some factors related to the driver’s performance, such as steering angle and speed, can be derived to optimize the most appropriate design choices. In practice, driving behavior differs from the assumed one and produces trends in these variables, which are very different from the ideal functions. The purpose of this research is therefore to propose synthetic performance indicators useful for highlighting the real characteristics of users’ driving behavior during road travel. Toward this aim, some driving experiments along four different curves in a simulated environment were studied in order to evidence possible criticisms. The proposed indicators showed a remarkable ability to represent and synthesize even very complex performance function trends. The proposed performance indicators can have multiple uses, such as, for example, in statistical analyses—which are generally carried out at a later stage—or constitute sufficient information to guide the decisions of infrastructure managers. In the long term, in a “smart road” perspective, they can be used by road administrators for information exchange among users (with each other and with the infrastructure) to improve road operation and safety. Full article

This paper describes the first results of the application of an innovative methodology for the development of a walkability overall index for urban street infrastructure, aimed at the application of urban design techniques to improve the urban form and its use by pedestrians. The general objective of the research is to identify the performance of the current city walkable network, to structure public policies and strategies consistent with it aimed at rebalancing settlements and infrastructure, and above all at the development of active mobility. The methodology defined integrates three approaches on walkability analysis: geometric–morphological, proximity, and sociality. In this paper, the analysis process related to the geometric–morphological component and partly to that of proximity will be described. It will be applied to the case study of the city of L’Aquila (Italy), a city undergoing reconstruction after the 2009 earthquake. From the first results of the application of the methodology to the case study, it emerges that the urban area analyzed is not capable of hosting walkable infrastructures unless urban design interventions are aimed at structuring an efficient network of pedestrian paths. In the future development of the study, it is expected to conclude the analysis of the proximity and social components, the other two groups of analysis considerations for walkability, which will complete the experimentation of the general methodology. Full article

This paper presents a concept for a universal tram driver console that has been developed based on research results regarding the review of tram control panels. These efforts were carried out as part of the project “Innovative training system for tram drivers, based on a full-cab simulator with the application of cognitive science” POIR.01.01.01-00-0135/22, with funding from the Smart Growth Operational Programme. This project involves the development of a tram driver training system based on a full-cabin tram simulator mounted on a motion platform, integrated with eye-tracking technologies and skin conductance response analysis for tram drivers’ assessment. The presented research results regarding the development of a universal control panel structure for a tram simulator have led to the creation of a panel based on interchangeable panels. The arrangement of individual switches was determined based on the identification, selection, critical evaluation, and analysis of data from current solutions. Full article

Most damage-assessment strategies for dynamic systems only distinguish between undamaged and damaged conditions without recognizing the level or type of damage or considering unseen conditions. This paper proposes a novel framework for structural health monitoring (SHM) that combines supervised and unsupervised learning techniques to assess damage using a system’s structural response (e.g., the acceleration response of big infrastructures). The objective is to enhance the benefits of a supervised learning framework while addressing the challenges of working in an SHM context. The proposed framework uses a Linear Discriminant Analysis (LDA)/Probabilistic Linear Discriminant Analysis (PLDA) strategy that enables learning the distributions of known classes and the performance of probabilistic estimations on new incoming data. The methodology is developed and proposed in two versions. The first version is used in the context of controlled, conditioned monitoring or for post-damage assessment, while the second analyzes the single observational data. Both strategies are built in an automatic framework able to classify known conditions and recognize unseen damage classes, which are then used to update the classification algorithm. The proposed framework’s effectiveness is first tested considering the acceleration response of a numerically simulated 12-degree-of-freedom system. Then, the methodology’s practicality is validated further by adopting the experimental monitoring data of the benchmark study case of the Z24 bridge. Full article

In recent years, the increased use of heavy commercial vehicles with higher axle weights has required the development of innovative technologies to improve the mechanical properties of asphalt concrete conglomerates, such as fatigue resistance and rutting. This study offers a comprehensive comparative analysis of different types of asphalt concrete tested in four trial sections (S1, S2, S3, S4) of the SP3 Ardeatina rural road in Rome, under actual traffic and operational conditions. More precisely, the pavement technologies applied include modified asphalt concrete with graphene and recycled hard plastics for S1, asphalt concrete modified with styrene–butadiene–styrene (SBS) for S2, asphalt concrete with a standard polymeric compound for S3, and traditional asphalt concrete for S4. The evaluation approach involved visual inspections in order to calculate the pavement condition index (PCI) and falling weight deflectometer (FWD) tests. In addition, back-calculation analyses were performed using ELMOD software to assess the mechanical properties. The laboratory tests revealed superior properties of M1 in terms of its resistance to permanent deformations (+13%, +15%, and +19.5% compared to M2, M3, and M4, respectively) and stiffness (10,758 MPa for M1 vs. 9259 MPa, 7643 MPa, and 7289 MPa for M2, M3, and M4, respectively). These findings were further corroborated by the PCI values (PCI_S1 = 65; PCI_S2 = 17; PCI_S3 = 28; PCI_S4 = 29) as well as the FWD test results after 5 years of investigation, which suggests greater durability and resistance than the other sections. Full article

Resilience of systems to natural hazards has become an interesting concept in civil engineering and it is based on the determination of the losses due to the impacts of natural hazards. In the last decades, many contributions have focused on the assessment of losses that may occur at the time of the event, as generally assumed for earthquakes. However, this assumption may be incorrect when the interval between the time of occurrence and the time when the system functionality reaches the minimum value needs to be considered. This paper aims to propose a novel method to quantify this interval, which is called disruption time, by proposing a novel formulation of the loss model based on infrastructure redundancy. The proposed method was herein applied to a case study that considers landslides in Sri Lanka. The main goal of the paper is to propose a formulation that can be implemented in a more comprehensive framework to calculate more realistically the resilience of systems to natural hazards. Full article

This paper introduces a novel nothing-on-road (NOR) bridge weigh-in-motion (BWIM) approach with deep learning (DL) and non-invasive ground-based radar (GBR) time-series data. BWIMs allow site-specific structural health monitoring (SHM) but are usually difficult to attach and maintain. GBR measures the bridge deflection contactless. In this study, GBR and an unmanned aerial vehicle (UAV) monitor a two-span bridge in Germany to gather ground-truth data. Based on the UAV data, we determine vehicle type, lane, locus, speed, axle count, and axle spacing for single-presence vehicle crossings. Since displacement is a global response, using peak detection like conventional strain-based BWIMs is challenging. Therefore, we investigate data-driven machine learning approaches to extract the vehicle configurations directly from the displacement data. Despite a small and imbalanced real-world dataset, the proposed approaches classify, e.g., the axle count for trucks with a balanced accuracy of 76.7% satisfyingly. Additionally, we demonstrate that, for the selected bridge, high-frequency vibrations can coincide with axles crossing the junction between the street and the bridge. We evaluate whether filtering approaches via bandpass filtering or wavelet transform can be exploited for axle count and axle spacing identification. Overall, we can show that GBR is a serious contender for BWIM systems. Full article

The prediction of the water film depth (WFD) on the road surface can help with road skid resistance research and reduce the risk associated with driving on rainy days. At present, there are many empirical and analytical models based on drainage length, slope, rainfall intensity and other parameters. Considering the influence of road surface runoff and starting from the Reynolds number formula of road surface water flow, a new road surface WFD calculation formula that considers the movement state of laminar water flow is derived. The results show that the changing trends of various parameters in the prediction model (drainage length, rainfall intensity, road slope) affecting WFD are consistent with those of the existing model. It is also found that the initial water film depth, initial speed of rainwater, and rainfall angle have little impact on WFD. The predicted value of the model has a suitable matching degree compared with the classical empirical model, which provides a new approach to the prediction of road water film depth. Full article