Infrastructures, Volume 9, Issue 9 (September 2024) – 28 articles

In recent years, three dimensional concrete printing (3DCP) has gained traction as a promising technology to mitigate the carbon footprint associated with construction industry. However, despite its environmental benefits, studies frequently overlook its impact on social sustainability and its overall influence on project success. This research investigates how strategic decisions by firms shape the tradeoffs between economic, environmental, and social sustainability in the context of 3DCP adoption. Through interviews with 20 Indian industry leaders, it was found that companies primarily invest in 3DCP for automation and skilled workforce development, rather than solely for environmental reasons. The lack of incentives for sustainable practices in government procurement regulations emerges as a significant barrier to the widespread adoption of 3DCP. Our study identifies five key strategies firms employ to promote sustainability through 3DCP and proposes actionable measures for government intervention to stimulate its advancement. Addressing these issues is crucial for realizing the full societal and environmental benefits of 3DCP technology. Full article

Pavement service life is an important factor that affects both the whole life cost and carbon footprint of a pavement. The service life of a pavement is affected by several different parameters which can be broadly classified into climate conditions, binder and mixture properties, pavement design, workmanship, and maintenance strategies. The current practice for determining service life of pavements involves the use of pavement design tools, which are used while constructing a new pavement or performing a reconstruction/resurfacing or pavement maintenance. In addition, field measurements using ground penetration radar, falling weight deflectometer, traffic speed deflectometer, and other techniques are also used to assess the condition of an existing pavement. The information from these measurements is then combined with pavement design software to predict potential pavement service life. The accuracy of the predicted pavement service life is affected by the associated uncertainties in the parameters that affect pavement life. The following paper presents various approaches that could be potentially used to determine the associated uncertainties in the estimation of pavement service life. The various uncertainty quantification techniques have been applied to a specific design, and the outcomes are discussed in this paper. The Monte Carlo simulation method, a system-level uncertainty quantification technique, can estimate a probabilistic pavement service life. The other uncertainty quantification schemes are software specific and provide probabilistic life factors by assumed statistical distributions. Hence, the Monte Carlo simulation technique could be one potential method that can be used for estimating a generalized pavement service utilizing predictions from various design software. Full article

Artificial intelligence (AI) has enabled several optimization techniques for structural design, including machine learning, evolutionary algorithms, as in the case of genetic algorithms, reinforced learning, deep learning, etc. Although the use of AI for weight optimization in steel and concrete buildings has been extensively studied in recent decades, multi-objective optimization for reinforced concrete (RC) and steel buildings remains challenging due to the difficulty in establishing independent objective functions and obtaining Pareto fronts. The well-known Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is an efficient genetic algorithm approach for multi-objective optimization. In this work, the NSGA-II approach is considered for the multi-objective structural optimization of three-dimensional RC buildings subjected to earthquakes. For the objective of this study, two function objectives are considered: minimizing total cost and the probability of structural failure, which are obtained via several nonlinear seismic analyses of the RC buildings. Beams and columns’ cross-sectional dimensions are selected as design variables, and the Mexican Building Code (MBC) specifications are imposed as design constraints. Pareto fronts are obtained for two RC-framed buildings located in Mexico City (soft soil sites), which demonstrate the efficiency and accuracy of NSGA-II for structural optimization. Full article

This article deals with the issue of diagnostics of the physical condition of earthen dams, taking into account seasonal changes in the water level of hydraulic structures using electrical exploration methods. The simplicity of the method, the accuracy of measurements of geophysical parameters, and the availability of software packages for the processing, interpretation, and visualization were the basis for the choice of method. The method of electrical resistivity and self-potential was chosen. The methodology, technique, technology of field surveys, processing, and geological interpretation of the study results are given. A comparative analysis of the obtained geophysical parameters of seasonal measurements is given. The research results are given in the form of sections of the resistivity model and self-potential isolines. Full article

When a wheel passes over a rail surface irregularity, the resulting vehicle excitations lead to the application of additional system forces to both the track and the vehicle. These forces contribute to an accelerated track geometry deterioration, which in turn results in increased costs. In a recent paper, a clear correlation between the presence of rail irregularities and poor track geometry quality was demonstrated. Rail surface irregularities thereby were quantified by raw data of a chord-based optical measurement system mounted on the regular track recording vehicle in Austria. This paper deals with deconvolution of the recorded data in order to guarantee irregularity quantification without any distortion. Two different deconvolution approaches are developed and validated by additional measurements. Using the deconvoluted data, previously published evaluations were repeated, and the impact of using deconvoluted data instead of chord values was analysed. The correlation between short-wave effects and track geometry quality can not only be confirmed; it is even stronger than predicted by the chord data. The results of the analysis demonstrate that irregularities with amplitudes exceeding 0.08 mm contribute to an accelerated deterioration in track geometry. Amplitudes of a greater severity result in track geometry levels that are up to 120% inferior to the average. Full article

Bridges, as vital infrastructure, require ongoing monitoring to maintain safety and functionality. This study introduces an innovative algorithm that refines bridge component performance assessment through the integration of modified K-means clustering, silhouette coefficient optimization, and cloud model theory. The purpose is to provide a reliable method for monitoring the safety and serviceability of critical infrastructure, particularly double-layer truss arch bridges. The algorithm processes large datasets to identify patterns and manage uncertainties in structural health monitoring (SHM). It includes field monitoring techniques and a model-driven approach for establishing assessment thresholds. The main findings, validated by case studies, show the algorithm’s effectiveness in enhancing clustering quality and accurately evaluating bridge performance using multiple indicators, such as statistical significance, cluster centroids, average silhouette coefficient, Davies–Bouldin index, average deviation, and Sign-Rank test p-values. The conclusions highlight the algorithm’s utility in assessing structural integrity and aiding data-driven maintenance decisions, offering scientific support for bridge preservation efforts. Full article

Although soil stabilization with cement and lime is widely used to overcome the low shear strength of soft clay, which can cause severe damage to the infrastructures founded on such soils, such binders have severe impacts on the environment in terms of increasing emissions of carbon dioxide and the consumption of energy. Therefore, it is necessary to investigate soil improvement using sustainable materials such as byproducts or natural resources as alternatives to conventional binders—cement and lime. In this study, the combination of cement kiln dust as a byproduct and zeolite was used to produce an alkali-activated matrix. The results showed that the strength increased from 124 kPa for the untreated clay to 572 kPa for clay treated with 30% activated stabilizer agent (activated cement kiln dust). Moreover, incorporating zeolite as a partial replacement of the activated cement kiln dust increased the strength drastically to 960 and 2530 kPa for zeolite ratios of 0.1 and 0.6, respectively, which then decreased sharply to 1167 and 800 kPa with further increasing zeolite/pr to 0.8 and 1.0, respectively. The soil that was improved with the activated stabilizer agents was tested under footings subjected to eccentric loading. The results of large-scale loading tests showed clear improvements in terms of increasing the bearing capacity and decreasing the tilt of the footings. Also, a reduction occurred due to the eccentricity decreasing as a result of increasing the thickness of the treated soil layer beneath the footing. Full article

The reconstruction of a standard at-grade intersection into a roundabout is very often motivated by the need to improve traffic safety, and the effects are usually monitored through before–after analyses based on traffic accidents. As in some countries, like Croatia, data on traffic accidents are not available, in this study, a methodology for the estimation of roundabout implementation effects based on measured operating speeds was developed and applied. This methodology enabled the analysis of the development of roundabouts designed according to the Croatian guidelines through the analysis of four roundabout case studies. Statistical analyses of before–after operating speed were performed, and speed time distribution variations, traffic volumes, and design elements were analyzed, compared, and correlated. Statistically significant differences were found between operating speeds before and after the reconstruction, although the expected effect of speed reduction of roundabouts was not observed. The weak correlations observed between the individual design elements of the roundabouts and operating speed highlight the need to analyze the combination of design elements with operational speed. The application of the developed methodology enabled systematic safety analyses of the selected roundabouts. The results of the analyses suggest a need to revise the guidelines. Full article

Many studies and technology companies highlight the actual or potential value of Digital Twins, but they often fail to demonstrate this value or how it can be realised. This gap constitutes a barrier for infrastructure asset management organisations in their attempt to innovate and incorporate digital twinning opportunities in their decision-making processes and their asset management planning activities. Asset management planning activities often make use of existing value-based decision-support tools to select and prioritise investments in physical assets. However, these tools were not originally designed to consider digital twinning investments that also compete for funding. This paper addresses this gap and proposes a value-based analysis for digital twinning opportunities in infrastructure asset management. The proposed analysis method is tested with three rail and road infrastructure case studies: (i) real-time monitoring of a power transformer; (ii) BIM for the design, construction, and maintenance of a new railway line; and (iii) infrastructure displacement monitoring using satellite data (InSAR). The study shows that the proposed method provides a conceptual construct and a common language that facilitates the communication of digital twinning opportunities in terms of their relevance in different contexts. The proposed method can be used to support the investment decision-making process for investments in both physical and non-physical assets and help derive maximum value from the limited available resources. Full article

The Pavement Condition Index (PCI) is a prevalent metric for assessing the condition of rigid pavements. The PCI calculation involves evaluating 19 types of damage. This study aims to analyze how different types of damage impact the PCI calculation and the impact of the performance of prediction models of PCI by reducing the number of evaluated damages. The Municipality of León, Gto., Mexico, provided a dataset of 5271 records. We evaluated five different decision-tree models to predict the PCI value. The Extra Trees model, which exhibited the best performance, was used to assess the feature importance of each type of damage, revealing their relative impacts on PCI predictions. To explore the potential for reducing the complexity of the PCI evaluation, we applied Sequential Forward Search and Brute Force Search techniques to analyze the performance of models with various feature combinations. Our findings indicate no significant statistical difference in terms of Mean Absolute Error (MAE) and the coefficient of determination (R²) between models trained with 13 features compared to those trained with all 17 features. For instance, a model using only eight damages achieved an MAE of 4.35 and an R² of 0.89, comparable to the 3.56 MAE and 0.92 R² obtained with a model using all 17 features. These results suggest that omitting some damages from the PCI calculation has a minimal impact on prediction accuracy but can substantially reduce the evaluation’s time and cost. In addition, knowing the most significant damages opens up the possibility of automating the evaluation of PCI using artificial intelligence. Full article

A recently used material that shows environmental and technical advantages for use as an asphalt binder modifier is biochar (BC). Different biomasses can be converted into BC by pyrolysis. One agro-industrial biomass that is abundant in copious quantities is oil palm mesocarp fiber (OPMF) obtained from African palm cultivation. In the present study, the use of a BC obtained from OPMF (BC-OPMF) as a modifier of asphalt binder (AC type) to produce a hot mix asphalt (HMA) was evaluated. This type of BC has not been investigated or reported in the reference literature as a binder and/or asphalt mix modifier. Initially, AC was modified with BC in three ratios (BC/AC = 5, 10, and 15%, with respect to mass) to perform penetration, softening point, and rotational viscosity tests; rheological characterization at high and intermediate temperatures; and scanning electron microscope (SEM) visualization. Based on this experimental phase, BC/AC = 10% was chosen to manufacture the modified HMA. Resistance parameters under monotonic loading (stability—S, flow—F, S/F ratio of the Marshall test, and indirect tensile strength in dry—ITSD and wet—ITSC conditions) and cyclic loading (resilient modulus, permanent deformation, and fatigue resistance under stress-controlled conditions) were evaluated on the control HMA (AC unmodified) and the modified HMA. Additionally, the tensile strength ratio (TSR) was calculated to evaluate the resistance to moisture damage. Abrasion and raveling resistance were evaluated by performing Cantabro tests. BC-OPMF is shown to be a sustainable and promising material for modifying asphalt binders for those seeking to increase stiffness and rutting resistance in high-temperature climates, resistance to moisture damage, raveling, and fatigue without increasing the optimum asphalt binder content (OAC), changing the volumetric composition of the HMA or increasing the manufacturing and construction temperatures. Full article

Civil infrastructure systems cover large land areas and need frequent inspections to maintain their public service capabilities. Conventional approaches of manual surveys or vehicle-based automated surveys to assess infrastructure conditions are often labor-intensive and time-consuming. For this reason, it is worthwhile to explore more cost-effective methods for monitoring and maintaining these infrastructures. Fortunately, recent advancements in satellite systems and image processing algorithms have opened up new possibilities. Numerous satellite systems have been employed to monitor infrastructure conditions and identify damages. Due to the improvement in the ground sample distance (GSD), the level of detail that can be captured has significantly increased. Taking advantage of these technological advancements, this research evaluated pavement conditions using deep learning models for analyzing satellite images. We gathered over 3000 satellite images of pavement sections, together with pavement evaluation ratings from the TxDOT’s PMIS database. The results of our study show an accuracy rate exceeding 90%. This research paves the way for a rapid and cost-effective approach for evaluating the pavement network in the future. Full article

The influence of road infrastructure over the severity of road accidents, in particular some specific features of it, represents the subject of this study. Generally, when an accident occurs, its causes are represented by a number of factors such as driver experience, fatigue, driving under the influence of alcohol and other psychoactive substances, road configuration, weather conditions, speeding, distracted driving, and unsafe road infrastructure. Road design is a key factor regarding the safety of all traffic participants. In this paper, the influence of unsafe roadside element designs on the incidence of traffic accidents, the degree of vehicle passenger injury, and the level of car damage were investigated. The present study was inspired by the high number of accidents produced on European route E68 (DN1) in Romania, a significant part of which was generated and accentuated by the effects of improper roadside design. Full article

Promoting bicycling and making it attractive requires appropriate infrastructure. Sociodemographic characteristics, frequency and experiences of bike use, and purpose of bicycle trips can affect preferences towards bicycle infrastructure facilities in urban areas. Hence, this study aims to explore the heterogeneity in the perceived importance of bicycle infrastructure facility attributes in various cyclist groups based on gender, age, weekly biking frequency, daily cycling distance, cycling experience, and bicycle trip purpose. Data were collected from bicycle users through a questionnaire disseminated via social media platforms and QR code brochures distributed in Hasselt, Belgium. A 5-point Likert-type ordinal scale was used to collect data on the perceived importance of bicycle infrastructure facility indicators. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to rank the indicators. At the same time, Mann–Whitney U and Kruskal–Wallis tests were utilized to verify the heterogeneity among the groups. The findings reveal that bicycle infrastructure, i.e., bicycle lanes or paths, is the most critical variable, while the slope was considered the least important. No heterogeneity was found regarding the importance of bicycle infrastructure indicators based on gender. However, heterogeneity was observed based on age, daily bicycle use, cycling experience, weekly bicycle use, and bicycle trip purpose. The findings of this research help urban and transport planners develop improvement strategies for the city’s existing bicycling facilities and prioritize future developments by considering various cyclist groups’ preferences. Full article

Large-scale man-made linear structures like high-speed railway lines have become increasingly important in modern life as a faster and more comfortable transportation option. Subsidence or longitudinal levelling deformation problems along these railway lines can prevent the line from operating effectively and, in some cases, require speed reduction, continuous maintenance or repairs. In this study, the longitudinal levelling deformation of the high-speed railway line passing through Konya province (Central Turkey) was analyzed for the first time using the Persistent Scatter Synthetic Aperture Radar Interferometry (PS-InSAR) technique in conjunction with diagnostic train measurements, and the correlation values between them were found. In order to monitor potential levelling deformation along the railway line, medium-resolution, free-of-charge C-band Sentinel-1 (S-1) data and high-resolution, but paid, X-band Cosmo-SkyMed (CSK) Synthetic Aperture Radar (SAR) data were analyzed from the diagnostic train and reports received from the relevant maintenance department. Comparison analyses of the results obtained from the diagnostic train and radar measurements were carried out for three regions with different deformation scenarios, selected from a 30 km railway line within the whole analysis area. PS-InSAR measurements indicated subsidence events of up to 40 mm/year along the railway through the alluvial sediments of the Konya basin, which showed good agreement with the diagnostic train. This indicates that the levelling deformation of the railway and its surroundings can be monitored efficiently, rapidly and cost-effectively using the InSAR technique. Full article

This study develops an integrated methodology to incorporate public perspectives into the establishment and development of public transportation infrastructure systems. The approach involves surveying citizens to collect data, performing demographic analyses to identify differences between cities, and applying Multi-Criteria Decision-Making (MCDM) techniques to weight, scale, and integrate evaluation criteria in order to determine the optimal transportation option. The primary aim of this research is to incorporate public perspectives into transportation planning in developing countries and to promote stakeholder engagement for transportation initiatives in cities such as Baghdad, Iraq, and Tehran, Iran. First, an initial survey was conducted to identify the top three preferred criteria among 200 participants from both cities. The survey results revealed that the three most important criteria were safety, travel time, and reliability. Subsequently, a larger survey utilizing the Saaty scale was administered to capture citizens’ preferences, with a total sample size of 550 from Baghdad and 345 from Tehran. The weights of the criteria were then calculated using the Group Analytical Hierarchy Process (GAHP). Three transportation alternatives—monorail, Light Rapid Transit (LRT), and metrobus—were suggested by transportation experts to be evaluated and ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on the weighted citizen preferences. The results indicate that for Baghdad residents, transportation safety is the most important priority, followed by reliability and travel time. However, LRT is rated as the most optimal transportation solution (0.721), followed by monorail (0.596) and metrobus (0.078). In Tehran, travel time represents the most preferred transportation attribute, followed by reliability and safety. The residents of Tehran are shown to prefer LRT (0.843), followed by monorail (0.370) and metrobus (0.143). Despite the similar ranking of transportation alternatives in the two cities, the performance scores differ between them, highlighting the importance of tailoring transportation planning to the unique preferences and needs of local communities. The validation of the results was conducted through sensitivity analysis to determine how variations in the criteria weights and input parameters affected the final rankings. Additionally, a stated preference survey was employed as a practical method to evaluate the robustness of the final ranking of the alternatives. Full article

The inherent brittle behavior of cementitious composite is considered one of its weaknesses in structural applications. This study evaluated the impact strength and failure modes of composite U-shaped normal concrete (NC) specimens strengthened with polyurethane grout material (NC-PUG) subjected to repeated drop-weight impact loads (USDWIT). The experimental dataset was used to train and test three machine learning (ML) algorithms, namely decision tree (DT), Naïve Ba yes (NB), and K-nearest neighbors (KNN), to predict the three failure modes exhibited by U-shaped specimens during testing. The uncertainty of the failure modes under different uncertainty degrees was analyzed using Monte Carlo simulation (MCS). The results indicate that the retrofitting effect of polyurethane grout significantly improved the impact strength of concrete. During testing, U-shaped specimens demonstrated three major failure patterns, which included mid-section crack (MC), crushing foot (CF), and bend section crack (BC). The prediction models predicted the three types of failure modes with an accuracy greater than 95%. Moreover, the KNN model predicted the failure modes with 3.1% higher accuracy than the DT and NB models, and the accuracy, precision, and recall of the KNN model have converged within 300 runs of Monte Carlo simulation under different uncertainties. Full article

A versatile building material, foamed concrete is made of cement, fine aggregate, and foam combined with coarse aggregate. This study provides a description of how constant coarse aggregate replacement (50%) of LECA and foamed concrete, which are lightweight concrete types, by zeolite as a filler and PEG-400 as a plasticizer, water retention agent, and strength enhancer affect the mechanical properties of the cement. A study that examined the characteristics of cellular lightweight concrete in both its fresh and hardened forms was carried out for both foamed concrete and LECA concrete. In order to do this, a composite of zeolite and polyethylene glycol 400 was made using the direct absorption method, and no leakage was seen. Zeolite was loaded to a level of 10% and 20% of the total weight in cement, while 400 g/mol PEG was used at levels of 1%, 1.5%, and 2% of the cement’s weight. Various mixtures having a dry density of 1250 kg/m³ were produced. Properties like dry density, splitting tensile strength, and compressive strength were measured. An increase in the amount of PEG400–zeolite was seen to lower the workability, or slump, of both foamed and LECA concrete, while the replacement of aggregate by zeolite resulted in an exponential drop in both compressive and flexural strengths. Full article

The Arctic Zone of Russia (AZR), due to its significant potential, for the implementation of which infrastructure projects and strategic plans are envisaged, is of great importance for the country. Particular attention is paid to the transport and related infrastructure development. The implementation of such projects requires the creation and implementation of modern integrated solutions based on new technical and technological solutions. The development of new territories is accompanied by problems such as urbanization and the disruption of ecosystems, which will have a particularly negative impact on the Arctic zone. The situation is complicated by the fact that the work must be carried out in difficult conditions, which are associated with a large number of risks, including environmental ones. Currently, many types of businesses are characterized by a transition to the implementation of the concepts of green and blue economy, as well as ESG principles when building strategic development plans that include risk reduction. Achieving this goal is possible through an environmental risk management system. To create a suchlike system, it is necessary to identify the most significant risk characteristics of each type of activity, taking into account their negative impact on the environment, after which it will be possible to plan measures to either prevent risks or minimize their consequences. Taking into account the above, we plan to develop the concept of an environmental risk management system (ERMS) as part of the region’s development strategy implementation. To reach this purpose, identifying the main groups of environmental risks depending on the danger source based on the scientific article review results, systematizing concepts aimed at improving the environmental situation under different types of anthropogenic impacts on the environment, developing an algorithm for implementing an environmental risk management system depending on the risk type, and proposing a concept for building an environmental risk management system are needed. The scientific novelty of the work lies in the fact that the main directions of negative anthropogenic impact on the environment are systematized, and possible ways to reduce environmental risks are outlined. The practical significance of the work lies in the fact that when implementing such a system, it will be possible to manage not only risks of a certain category, but also monitor the situation as a whole, identifying the consequences for related areas. Full article

A limited number of previous studies have focused on the selection of transportation routes considering sustainable development goals (SDGs). In this research, a methodology for selecting sustainable public transit (PT) routes is presented, consisting of generating a feasible initial route set, optimization, and assessment. Total welfare, road safety, and reduction in total emissions are indicators of the economic, social, and environmental dimensions, respectively. Based on the transportation model, the network structure, attributes, and emission rates are exported. The travel demand of PT is modified by modal share. Additionally, the safety performance function (SPF) is developed as a safety measure. Regarding optimization, the optimum routes are obtained by maximizing PT share and minimizing PT travel time. Then, the new routes are implemented, and the network is evaluated and compared with the existing scenario in light of sustainability indicators. The case study is Amman BRT. The results show that the new network is more sustainable than the existing BRT network and achieves better performance than the selected scenario of Amman city. The new network can reduce travel time by more than 13%, decrease total emissions by more than 17%, and alleviate the crash frequency by more than 14%. Full article

Improving the physico-mechanical characteristics of bitumen is a constant and pressing problem in road construction. The issue is solved by modifying bitumen with various additives, one of which is a nanostructured modifier. This paper examines the effect of adding a natural mineral, shungite, to bitumen from the Koksu deposit (Kazakhstan) after grinding under different conditions. The mechanochemical activation of shungite made it possible to obtain samples with an average particle diameter of up to 3 μm. Using scanning electron microscopy, nanostructured particles with sizes of up to 100 nm were discovered in their structure. The effect of nanostructured shungite on the rheological characteristics of bitumen—elasticity and loss moduli, and loss tangent at high and low temperatures—was studied. The transition temperatures of bitumen from the viscoelastic to the liquid state were established, and their shift to the region of elevated temperatures when modified with ground shungite are shown. The presence of organic and inorganic components in the composition of shungite—carbon, silica, and metal oxides—has a beneficial effect on the rheological properties of bitumen by forming bonds with resinous asphaltene components of bitumen. The use of bitumen modified with nanostructured shungite makes it possible to replace the polymer modifier with a natural mineral to improve the quality of the road surface. Full article

Corrosion negatively impacts the functionality of civil structures. This paper introduces a new methodology that combines the fractality of vibration signals with a data processing stage utilizing autoencoders to detect corrosion damage in a truss-type bridge. Firstly, the acquired vibration signals are analyzed using six fractal dimension (FD) algorithms (Katz, Higuchi, Petrosian, Sevcik, Castiglioni, and Box dimension). The obtained FD values are then used to generate a gray-scale image. Then, autoencoders analyze these images to generate a damage indicator based on the reconstruction error between input and output images. These indicators estimate the damage probability in specific locations within the structure. The methodology was tested on a truss-type bridge model placed at the Vibrations Laboratory from the Autonomous University of Queretaro, Mexico, where three damage corrosion levels were evaluated, namely incipient, moderate, and severe, as well as healthy conditions. The results demonstrate that the proposal is a reliable tool to evaluate the condition of truss-type bridges, achieving an accuracy of 99.8% in detecting various levels of corrosion, including incipient stages, within the elements of truss-type structures regardless of their location. Full article

Dams play a pivotal role in providing essential services such as energy generation, water supply, and flood control. However, their stability is crucial, and continuous monitoring is vital to mitigate potential risks. The Mosul Dam is one of the most interesting infrastructures in Iraq because it was constructed on alternating beds of karstified and gypsum which required continuous grouting due to water seepage. Therefore, the ongoing maintenance issues raised international concerns about its stability. For several years the dam indicated a potential for disastrous failure that could cause massive flooding downstream and pose a serious threat to millions of people. This research focuses on comprehensive statistical assessments of the dam geodetic network points across multiple epochs of long duration. Through the systematic application of three statistical tests and the predictive capabilities of the Kalman filter, safety and long-term stability are aimed to be enhanced. The analysis of the dam’s geodetic network points shows a consistent trend of upstream-to-downstream movement. The Kalman filter demonstrates promising outcomes for displacement prediction compared to least squares adjustment. This research provides valuable insights into dam stability assessment, aligns with established procedures, and contributes to the resilience and safety of critical infrastructure. The outcome of this paper can encourage future studies to build upon the foundation presented. Full article

The substantial influences of masonry infills used as partition walls on the seismic behavior of multistory reinforced concrete (RC) structures have long been recognized. Thereupon, in this study, considering open-ground floors due to a lack of infills (pilotis configuration), the structural pounding phenomenon between adjoining RC buildings with unequal story levels and unequal total heights is investigated. Emphasis is placed on the impact of the external columns of the higher structure, which suffer from the slabs of adjoining shorter buildings. The developing maximum shear forces of the columns due to the impact are discussed and compared with the available shear strength. Furthermore, it is stressed that the structures are partially in contact, as is the case in most real adjacent structures; therefore, the torsional vibrations brought about due to the pounding phenomenon are examined by performing 3D nonlinear dynamic analyses (asymmetric pounding). In this study, an eight-story RC frame structure that is considered to be fully infilled or has an open-ground floor interacts with shorter buildings with n_s stories, where n_s = 6, 3, and 1. Two natural seismic excitations are used, with each one applied twice—once in the positive direction and once in the negative direction—to investigate the influence of seismic directionality on the asymmetric pounding effect. Finally, from the results of this study, it is concluded that the open-ground story significantly increases the shear capacity demands of the columns that suffer the impact and the inelastic rotation demands of the structure, whereas these demands further increase as the stories of the adjoining shorter building increase. Full article

Cold-formed steel channel (CFSC) sections have gained widespread adoption in building construction due to their advantageous properties, including superior energy efficiency, expedited construction timelines, environmental sustainability, material efficiency, and ease of transportation. This study presents a numerical investigation into the axial compressive behavior of CFSC section columns. A rigorously developed finite element model for CFSC sections was validated against existing experimental data from the literature. Upon validation, the model was employed for an extensive parametric analysis encompassing a dataset of 208 CFSC members. Furthermore, the efficacy of the design methodologies outlined in the AISI Specification and AS/NZS Standard were evaluated by comparing the axial load capacities obtained from the numerically generated data with the results of four previously conducted experimental tests. The findings reveal that the codified design equations, based on nominal compressive resistances determined using the current direct strength method, exhibit a conservative bias. On average, these equations underestimate the actual load capacities of CFSC section columns by approximately 11.5%. Additionally, this investigation explores the influence of eccentricity, cross-sectional dimensions, and the point-of-load application on the axial load capacity of CFSC columns. The results demonstrate that a decrease in section thickness, an increase in column length, and a higher degree of eccentricity significantly reduce the axial capacity of CFSC columns. Full article

This research investigates the lane width standards and guidelines implemented by various State Departments of Transportation (DOTs) to reduce vehicle speeds and enhance road safety. Lane width reduction is often perceived as a strategy to mitigate speed and improve safety. Still, its effectiveness and implications vary across different contexts, including regions, urban/rural settings, or other geometric design features. Drawing from interviews with five State DOTs and a review of their road design manuals, this study aims to identify suggested lane widths depending on the contexts, design exception process when narrowing or widening lane widths, and introduce representative before/after studies. The findings indicate that State DOTs tend to have lower recommended lane widths in urban areas than in rural areas. Moreover, lane width standards among these states vary due to several factors, including the geographical location of roadways (urban or rural areas), design or posted speeds, traffic volume, road classification, and geometric road design features. Design exceptions are required if the existing or proposed design element is incompatible with both AASHTO and department governing criteria. In conclusion, the findings will provide valuable insights and recommendations for policymakers, transportation planners, and road engineers to inform optimal lane width and decision-making processes. Full article

Flooding and consequential scouring are the primary causes of bridge failures, making the detection of such events crucial for structural safety. This study investigates the characteristics of accelerometer data from bridge pier vibrations and proposes a flood detection method with deep learning-based models based on ResNet18 and 1D Convolution architectures. These models were comprehensively evaluated for (1) detecting vehicles passing on bridges and (2) detecting flood events based on axis-specific accelerometer data under various traffic conditions. Continuous Wavelet Transform (CWT) was employed to convert the accelerometer data into richer time-frequency representations, enhancing the detection of passing vehicles. Notably, when vehicles are passing over bridges, the vertical direction exhibits a magnified and more sustained energy distribution across a wider frequency range. Additionally, under flooding conditions, time-frequency representations from the bridge direction reveal a significant increase in energy intensity and continuity compared with non-flooding conditions. For detection of vehicles passing, ResNet18 outperformed the 1D Convolution model, achieving an accuracy of 97.2% compared with 91.4%. For flood detection without vehicles passing, the two models performed similarly well, with accuracies of 97.3% and 98.3%, respectively. However, in scenarios with vehicles passing, the 1D Convolution model excelled, achieving an accuracy of 98.6%, significantly higher than that of ResNet18 (81.6%). This suggests that high-frequency signals, such as vertical vibrations induced by passing vehicles, are better captured by more complex representations (CWT) and models (e.g., ResNet18), while relatively low-frequency signals, such as longitudinal vibrations caused by flooding, can be effectively captured by simpler 1D Convolution over the original signals. Consequentially, the two model types are deployed in a pipeline where the ResNet18 model is used for classifying whether vehicles are passing the bridge, followed by two 1D Convolution models: one trained for detecting flood events under vehicles-passing conditions and the other trained for detecting flood events under no-vehicles-passing conditions. This hierarchical approach provides a robust framework for real-time monitoring of bridge response to vehicle passing and timely warning of flood events, enhancing the potential to reduce bridge collapses and improve public safety. Full article

There are curved bridge structures in the intercity rail line. During the operation of bridges, they are subjected to train loads, resulting in stress amplitudes of the construction materials; during operation, when the train interval is short, the fatigue performance of the bridge should be emphasized. Unlike straight bridges, when a train travels on a curved bridge, it tends to move in the original direction, which undoubtedly causes the train to deviate from the track. Therefore, it is necessary to set the track deflection to limit this movement trend, which will also impart radial forces on the track structure, and the reaction force of this force is called centripetal force. Under the action of centripetal force, the train generates a virtual force called centrifugal force. The material stress amplitude caused by centrifugal force and the vertical force both need to be considered. Therefore, a curved train–bridge coupled system was established to simulate the dynamic stress of the train passing through a curved bridge, and the stress amplitude and cycle number of the dynamic stress time–history curve were analyzed based on the rain-flow method. The cumulative damage of the bridge under different curve radii, different train speeds, different lengths of span, and different operation interval times was analyzed, and the fatigue life was calculated. The results show that the influence of centrifugal force at a small curve radius cannot be ignored. In addition, the cumulative damage and service life are greatly affected by the train speed and bridge span; especially when the train speed is close to the resonance speed, the service life is significantly reduced. Finally, the recommended values for the train passing speed for curved bridges with different spans are given. It was suggested that the design speed of a curved bridge with a span of 25 m, 30 m, and 35 m should be set in the range of 70 to 106 km/h, 78 to 86 km/h, and about 75 km/h, respectively. Full article