Search Results (899)

The incorporation of building information modeling (BIM) has brought about significant advancements in civil engineering, enhancing efficiency and sustainability across project life cycles. The utilization of advanced 3D point cloud technologies such as laser scanning extends the application of BIM, particularly in operations and maintenance, prompting the exploration of automated solutions for labor-intensive point cloud modeling. This paper presents a demonstration of supervised machine learning—specifically, a support vector machine—for the analysis and segmentation of 3D point clouds, which is a pivotal step in 3D modeling. The point cloud semantic segmentation workflow is extensively reviewed to encompass critical elements such as neighborhood selection, feature extraction, and feature selection, leading to the development of an optimized methodology for this process. Diverse strategies are implemented at each phase to enhance the overall workflow and ensure resilient results. The methodology is then evaluated using diverse datasets from infrastructure scenes of bridges and compared with state-of-the-art deep learning models. The findings highlight the effectiveness of supervised machine learning techniques at accurately segmenting 3D point clouds, outperforming deep learning models such as PointNet and PointNet++ with smaller training datasets. Through the implementation of advanced segmentation techniques, there is a partial reduction in the time required for 3D modeling of point clouds, thereby further enhancing the efficiency and effectiveness of the BIM process. Full article

Culverts fulfill the vital function of safely channeling water beneath railway tracks, highways, and overpasses. They serve various purposes, including facilitating drainage in areas such as watercourses, drainage zones, and regions with restricted ground-bearing capacity. Precast reinforced concrete (RC) box culverts are a popular choice because they are strong, durable, rigid, and economical. However, culverts are prone to corrosion due to exposure to a range of environmental factors and aggressive chemicals. Therefore, enhancing the design and construction of this crucial infrastructure is imperative to effectively combat corrosion and to adhere to modern standards of reliability and affordability. In this study, carbon fiber-reinforced polymer (CFRP) was used to strengthen corroded culverts, with promising potential to improve safety and longevity in these structures. This study compared the behavior of corroded RC box culverts to CFRP-strengthened ones using the finite element method (FEM). It explored the impact of varying the damage thicknesses owing to corrosion, ranging from 0 mm to 20 mm, on the structural performance of the box culverts. The results showed that the CFRP model exhibited a substantial 25% increase in the capacity and reduced the damage compared to the reference model. Moreover, a parametric study was conducted for establishing a cost-effective design, in which numerous CFRP strip configurations were examined for a damaged-culvert model. The results indicated that a complete CFRP sheet was most effective for the maximum design capacity and repair effectiveness. The study’s outcomes provide valuable insights for professionals engaged in enhancing the strength of box culverts, aiming to increase the capacity, enhance the stability, and strengthen corroded culverts. Full article

Following effective seismic codes, common buildings are considered to be made of the same material throughout the story distribution and based on an ideal rigid soil. However, in daily construction practice, there are often cases of buildings formed by a bottom part constructed with reinforced concrete (r/c) and a higher steel part, despite this construction type not being recognized by code assumptions. In addition, soil deformability, commonly referred to as the Soil–Structure Interaction (SSI), is widely found to affect the earthquake response of typical residence structures, apart from special structures, though it is not included in the normative design procedure. This work studies the seismic response of in-height mixed 3D models, considering the effect of sustaining deformable ground compared to the common rigid soil hypothesis, which has not been clarified so far in the literature. Two types of soft soil, as well as the rigid soil assumption, acting as a reference point, are considered, while two limit interconnections between the steel part on the concrete part are included in the group analysis. The possible influence of the seismic orientation angle is explored in the analysis set. Selected numerical results of the dynamic nonlinear analyses under strong near-fault ground excitations were plotted through dimensionless parameters to facilitate an objective comparative discussion. The effect of SSI on the nonlinear performance of three-dimensional mixed models is identified, which serves as the primary contribution of this work, making it unique among the numerous research works available globally and pointing to findings that are useful for the enhancement of the seismic rules regarding the design and analysis of code-neglected mixed buildings. Full article

The phenomenon of the oxidation and aging of asphalt binders affects the strength and durability of asphalt mixtures in pavements. Several studies are trying to improve the resistance to this phenomenon by modifying the properties of the binders with nano-particles. One material that shows promise in this field is zinc oxide (ZnO), especially in improving ultraviolet (UV) aging resistance. Few studies have evaluated the effect of these nano-particles on the thermo-oxidative resistance of asphalt binders, and, on hot-mix asphalt (HMA), studies are even more scarce and limited. Therefore, in the present study, the resistance to thermo-oxidative aging of an HMA manufactured with an asphalt binder modified with ZnO was evaluated. An asphalt cement (AC 60–70) was initially modified with 0, 1, 3, 5, 7.5, and 10% ZnO (percentage by weight of asphalt binder; ZnO/AC in wt%), and then exposed to aging in Rolling Thin-Film Oven tests (RTFOT) and a Pressure Aging Vessel (PAV). Penetration, viscosity, and softening point tests were performed on these binders, and aging indices were calculated and evaluated. Samples of HMAs were then manufactured using these binders and designed by the Marshall method, determining the optimum asphalt binder content (OAC) and the optimum ZnO/AC ratio. Control (unmodified) and modified HMA were subjected to short-term oven aging (STOA) and long-term oven aging (LTOA) procedures. Marshall, Indirect Tensile Strength (ITS), and resilient modulus (RM) tests were performed on these mixtures. LTOA/STOA results of the parameters measured in these tests were used as aging indices. In this study, ZnO was shown to increase the thermo-oxidative aging resistance of the asphalt binder and HMA. It also contributed to an increase in the resistance under monotonic loading in the Marshall and ITS tests, and under repeated loading in RM test. Likewise, it contributed to a slightly increasing resistance to moisture damage. The best performance is achieved using ZnO/AC = 5 wt%. Full article

Among the technologies proposed for achieving carbon neutralization in asphalt road pavements, warm-mix asphalt (WMA) has garnered increasing attention in recent years. While WMA holds the potential for various environmental and technical benefits, a comprehensive understanding of its implementation, technology selection, and additives is essential for successful application. This study presents a case where a bio-based chemical additive was employed to produce WMA containing 50% reclaimed asphalt pavement (RAP) for a surface course in Bern, Switzerland. To minimize additional variables during testing and analysis, no other additive or rejuvenator was introduced into the mixtures. The testing plan encompassed laboratory tests on samples collected during material placement and recompacted at varying temperatures in the laboratory, as well as cores extracted from the job site. As anticipated, the presence of the chemical WMA additive did not alter the rheological properties of the reference bitumen. Although in the mixture-scale tests, the WMA mixture exhibited comparable properties to the control hot-mix asphalt (HMA), it is not expected that the small dosage of the chemical additive functions the same grade after reheating and compaction. Nevertheless, the cores extracted from the job site proved the efficiency of the applied WMA technology. In addition, consistent with existing literature, the cracking tolerance (CT) index values of 62 for HMA and 114 and 104.9 for WMA mixtures indicated that the latter is less susceptible to cracking. Consequently, this characteristic could contribute to the enhanced durability of asphalt pavements. Full article

This research utilizes the Long-Term Pavement Performance database, focusing on devel-oping a predictive model for flexible pavement performance in the Southern United States. Analyzing 367 pavement sections, this study investigates crucial factors influencing asphaltic concrete (AC) pavement deterioration, such as structural and material components, air voids, compaction density, temperature at laydown, traffic load, precipitation, and freeze–thaw cycles. The objective of this study is to develop a predictive machine learning model for AC pavement wheel path cracking (WpCrAr) and the age at which cracking initiates (WpCrAr) as performance indicators. This study thoroughly investigated three ensemble machine learning models, including random forest, extremely randomized trees (ETR), and extreme gradient boosting (XGBoost). It was observed that XGBoost, optimized using Bayesian methods, emerged as the most effective among the evaluated models, demonstrating good predictive accuracy, with an R² of 0.79 for WpCrAr and 0.92 for AgeCrack and mean absolute errors of 1.07 and 0.74, respectively. The most important features influencing crack initiation and progression were identified, including equivalent single axle load (ESAL), pavement age, number of layers, precipitation, and freeze–thaw cycles. This paper also showed the impact of pavement material combinations for base and subgrade layers on the delay of crack initiation. Full article

Wolf Rock Lighthouse is a Victorian era masonry structure located in an extreme environment facing the fiercest Atlantic storms off the southwest coast of England whose dynamic behaviour has been studied since 2016. Initially, a modal test was used to determine modal parameters; then, in 2017, a monitoring system was installed that has operated intermittently providing response data for a number of characteristic loading events. These events have included wave loads due to storms, a small UK earthquake, helicopters landing on the helideck, and the grounding of a ship on the reef. This is believed to be the most extensive experimental campaign on any structure of this type. This paper briefly describes a unique project involving the characterisation and measurement of dynamic behaviour due to different forms of dynamic loading. Full article

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