Search Results (763)

Aerodynamic performance is of critical importance to the design of long-span bridges. Computational fluid dynamics (CFD) modelling offers bridge designers an opportunity to investigate aerodynamic performance for long-span bridges during the design phase as well as during operation of the bridge. It offers distinct advantages when compared with the current standard practice of wind tunnel testing, which can have several limitations. The proposed revisions to the Eurocodes offer CFD as a methodology for wind analysis of bridges. Practicing engineers have long sought a computationally affordable, viable, and robust framework for industrial applications of using CFD to examine wind effects on long-span bridges. To address this gap in the literature and guidance, this paper explicitly presents a framework and demonstrates a workflow of analyzing wind effects on long-span bridges using open-source software, namely FreeCAD, OpenFOAM, and ParaView. Example cases are presented, and detailed configurations and general guidance are discussed during each step. A summary is provided of the validation of this methodology with field data collected from the structural health monitoring (SHM) systems of two long-span bridges. Full article

This paper examined the opportunities of composite double-layer grid superstructures in short-to-medium span bridge decks. It was empirically shown here that a double-layer grid deck system in composite action with a thin layer of two−way reinforced concrete slab introduced several structural advantages over the conventional composite plate-girder superstructure system. These advantages included improved seismic performance, increased structural rigidity, reduced deck vibration, increased failure capacity, and so on. Optimally proportioned space grid superstructures were found to be less prone to progressive collapse, increasing structural reliability and resilience, while reducing the risk of sudden failure. Through a set of dynamic time-series experiments, considerable enhancement in load transfer efficiency in the transverse direction under dynamic truck loading was gained. Furthermore, the multi-objective generative optimization of the proposed spatial grid bridge (with integral variable depth) using evolutionary optimization methods was examined. Finally, comprehensive discussions were given on: (i) mechanical properties, such as fatigue behavior, corrosion, durability, and behavior in cold environments; (ii) health monitoring aspects, such as ease of inspection, maintenance, and access for the installation of remote monitoring devices; (iii) sustainability considerations, such as reduction of embodied Carbon and energy due to reduced material waste, along with ease of demolition, deconstruction and reuse after lifecycle design; and (iv) lean management aspects, such as support for industrialized construction and mass customization. It was concluded that the proposed spatial grid system shows promise for building essential and sustainable infrastructures of the future. Full article

The nation’s transportation systems are complex and are some of the highest valued and largest public assets in the United States. As a result of repeated natural hazards and their significant impact on transportation functionality and the socioeconomic health of communities, transportation resilience has gained increasing attention in recent years. Previous studies on transportation resilience have heavily emphasized network functionality during and/or following a scenario hazard event by implicitly assuming that sufficient knowledge of structural capacity and environmental/service conditions is available at the time of an extreme event. However, such assumptions often fail to consider uncertainties that arise when an extreme hazard event occurs in the future. Thus, it is essential to quantify and reduce uncertainties to better prepare for extreme events and accurately assess transportation resilience. To this end, this paper proposes a dynamic Bayesian network-based resilience assessment model for a large-scale roadway network that can explicitly quantify uncertainties in all phases of the assessment and investigate the role of inspection and monitoring programs in uncertainty reduction. Specifically, the significance of data reliability is investigated through a sensitivity analysis, where various sets of data having different reliabilities are used in updating system resilience. To evaluate the effectiveness of the model, a benchmark problem involving a highway network in South Carolina, USA is utilized, showcasing the systematic quantification and reduction of uncertainties in the proposed model. The benchmark problem result shows that incorporating monitoring and inspection data on important variables could improve the accuracy of predicting the seismic resilience of the network. It also suggests the need to consider equipment reliability when designing monitoring and inspection programs. With the recent development of a wide range of monitoring and inspection techniques, including nondestructive testing, health monitoring equipment, satellite imagery, LiDAR, etc., these findings can be useful in assisting transportation managers in identifying necessary equipment reliability levels and prioritizing inspection and monitoring efforts. Full article

Over the next decades, people will continue moving to urban areas all over the world, increasing infrastructure needs to satisfy economic, environmental, and social demands. The connection between civil urban infrastructure and smart cities is strong due to the common goal of fulfilling public service demands. Infrastructure management contributes to the development, evolution, and sustainability of smart cities. The main problem with traditional approaches to the development, evolution, and sustainability of smart cities is the lack of a holistic, integrated vision of infrastructure management. The main objective of this research is to introduce an infrastructure management humanistic approach with a smart city conceptual model that also considers an educational perspective. A mixed research methodology that combines quantitative and qualitative approaches was used, applying inductive-deductive tools. The paper concludes with the development of an infrastructure management framework for smart cities with five dimensions: (1) Environmental, (2) financial-economic, (3) political-governance, (4) social-people, and (5) technological. Two case studies for the cities of Lima and Piura in Perú illustrate how to incorporate this framework into practice. The research products are relevant because they foster an inclusive better quality of life for all citizens by preserving civil infrastructure systems. Full article

In the 21st century, one of the key requirements is to develop and maintain our infrastructure facilities most efficiently using the available resources. Tramways are of significant national economic importance and represent an important national asset. There are currently seven different types of superstructure systems in Hungary, based on the national regulations and the related requirements currently in force. This paper compares the paved tramway superstructure systems in the context of track geometry, through-rolled axle tons of track, and the age of track sections. Paved tracks have many benefits, but the main ones are easier maintenance and road traffic use. Elastically supported continuous rail bedding (ESCRB; in Hungary, this is known as “RAFS”) and “large” slab superstructure systems are used to create paved superstructure systems. Road crossings use the latter systems, while heavily loaded lines use several ESCRB systems. This article examines the geometrical changes in several ESCRB superstructure systems. A TrackScan 4.01 instrument was used to take measurements in June and September 2021 and in April 2022, September 2022, and May 2023. Track gauge, alignment, and longitudinal level are examined. Regardless of the ESCRB superstructure system or age, a medium-loaded line’s track gauge trendline increases, which means that the track gauge is widening and, regardless of traffic load or age, the average longitudinal level is constantly increasing from year to year. When it is a medium-loaded line, the average value of alignment increases slightly, and the trendline is almost straight, but it decreases when it is an extremely heavily loaded line. The authors will analyze how the reference track section will change in the future. Based on the results, it is important to assess how subsequent measurements affect the trend lines. Because the data evaluations show similar results, comparing open tramway tracks to paved ones is crucial. Full article

Earthquake-induced soil liquefaction (EISL) can cause significant damage to structures, facilities, and vital urban arteries. Thus, the accurate prediction of EISL is a challenge for geotechnical engineers in mitigating irreparable loss to buildings and human lives. This research aims to propose a binary classification model based on the hybrid method of a wavelet neural network (WNN) and particle swarm optimization (PSO) to predict EISL based on cone penetration test (CPT) results. To this end, a well-known dataset consisting of 109 datapoints has been used. The developed WNN-PSO model can predict liquefaction with an overall accuracy of 99.09% based on seven input variables, including total vertical stress (${\sigma }_v$), effective vertical stress (${\sigma }_v^{\prime }$), mean grain size (D₅₀), normalized peak horizontal acceleration at ground surface (α_max), cone resistance (q_c), cyclic stress ratio (CSR), and earthquake magnitude (M_w). The results show that the proposed WNN-PSO model has superior performance against other computational intelligence models. The results of sensitivity analysis using the neighborhood component analysis (NCA) method reveal that among the seven input variables, q_c has the highest degree of importance and M_w has the lowest degree of importance in predicting EISL. Full article

The growing demand for transportation tunnels in densely populated urban areas has led to the widespread adoption of twin tunnel configurations in contemporary infrastructure projects. This research focuses on investigating the complex interaction between soil, structures, and the excavation of twin tunnels. The study employs the tunnel boring machine (TBM) method and utilizes two-dimensional numerical modeling based on the finite element method (FEM). The numerical model is validated by comparing its results with field measurements obtained from a twin tunnel project in Italy, specifically the New Milan Metro Line 5. A comprehensive parametric study is conducted to analyze various parameters that influence soil–structure interaction during tunnel excavation. These parameters include the positioning of the tunnels in relation to each other, the spacing between them, the presence of structures above the tunnels, eccentricity between the structure axis and tunnel axis, and tunnel depth and diameter. Moreover, a comparative analysis is performed between scenarios with and without structures to elucidate the impact of structure presence on the interaction phenomenon. The research findings provide valuable insights into the intricate behavior of twin tunnels and their interaction with the surrounding soil and structures. Full article

Recently, the bridge infrastructure in Ukraine has faced the problem of having a significant number of damaged bridges. It is obvious that the repair and restoration of bridges should be preceded by a procedure consisting of visual inspection and evaluation of the technical condition. The problem of fast and high-quality collection, processing and storing large datasets is gaining more and more relevance. An effective way to solve this problem is to use various machine learning methods in bridge infrastructure management. The purpose of this study was to create a model based on convolutional neural networks (CNNs) for classifying images of concrete bridge elements into four classes: “defect free”, “crack”, “spalling” and “popout”. The eight CNN models were created and used to conduct its training, validation and testing. In general, it can be stated that all CNN models showed high performance. The analysis of loss function (categorical cross-entropy) and quality measure (accuracy) showed that the model on the MobileNet architecture has optimal values (loss, 0.0264, and accuracy, 94.61%). This model can be used further without retraining, and it can classify images on datasets that it has not yet “seen”. Practical use of such a model allows for the identification of three damage types. Full article

During intense ground motion excitations, the pounding between adjacent buildings may result in extensive structural damage. Despite the provision of regulations regarding the minimum separation gap required to prevent structural collisions, the majority of existing structures are poorly separated. The modern seismic design and assessment of structures are based on the definition of acceptable response levels in relation to the intensity of seismic action, which is usually determined by an acceptable probability of exceedance. From this point of view, the seismic performance of a typical eight-storey reinforced concrete (RC) frame structure is evaluated in terms of pounding. In particular, the performance is evaluated using six different separation gap distances as a fraction of the EC8 minimum distance. As the height of the adjacent structure affected the required separation distance, the examined RC structure was assumed to interact with four idealized rigid structures of one to four storeys. The typical storey height was equal between the examined structures; therefore, collision could occur at the diaphragm level. To this end, incidental dynamic analyses (IDAs) were performed, and the fragility curves for different limit states were obtained for each case. Finally, the seismic fragility was combined with the hazard data to evaluate the seismic performance probabilistically. Full article

Considering the proposed strict new constraints of public authorities, decarbonization has become a key trend in recent years. Although several countries have started the process of decarbonization through the introduction of electric vehicles in their public services, for many countries, especially developing countries, transportation is still a hard sector to decarbonize. The presence of obsolete and polluting vehicles discourages citizens from using public transport and thus incentivizes the use of private vehicles, which create traffic congestion and increase emissions. Based on these considerations, this paper aimed to implement a simulation for a public service in Eritrea, evaluating whether it is possible to take a long trip using an electric minibus. A case study is implemented highlighting the barriers of electrifying transportation in this area, producing results on fuel consumption and service reliability. In the case study, four scenarios are presented to estimate the service. The scenarios evaluate the possibility to perform from three to five recharges. Fewer charges mean longer charging time, leading to a 2 h charging phase in Scenario 1, while recharging more than twice along the route will lead to shorter 30 min charges, as in Scenario 3. The case study also highlights the relevance of the slope in electric vehicle performance, as reported for the case of Asmara–Massawa travel ($E_{cons}=$ 6.688 kWh). Finally, an environmentally sustainable solution, such as a 92 kWh/day photovoltaic plant, is proposed to power the service. Full article

The assessment of concrete infrastructures’ functionality during natural hazards is fundamental in evaluating their performance and emergency response. In this work, the alkali–silica reaction (ASR) in concrete is evaluated under the climate change impact. The ASR is greatly influenced by the weather parameters, such as temperature and humidity. Climate change has led the quickening of global warming and has caused extreme weather events in recent years. These events can create anomalies in weather and thus convey potential threats to the concrete infrastructures affected by the ASR. Capturing these extreme events is the key prerequisite for the precise quantification of the ASR chemophysics. This work develops a novel stochastic approach to understand the influence of stochastic temperature and humidity on ASR expansion. To assess the stochastic weather impacts on concrete, a physics-informed domain is developed by capturing the variably saturated porous medium of concrete. This is an effort to analyze ASR kinetics that integrates chemo-physical damage under extreme weather events. Results elucidate that the ASR-affected concrete would experience 83.33% more damage in 10 years than from seasonal change due to the stochastic weather impacts from climate change. This improved predictive model will guide the durable infrastructure materials design practices and enhance the resiliency of concrete infrastructures. Full article

Connected and Autonomous Vehicles (CAV) will change how road engineers design road pavements because they can position themselves within a traffic lane, keeping their position in the lane more precisely than human-driven vehicles. These vehicles will have lower lateral wandering, which can induce more damage to pavements, such as cracking and permanent deformation, than the conventional vehicles, with consequences for the infrastructures due to the increased cracking and reduced safety due to the rutting. Thus, it is essential to assess the wander effect on pavement performance to define policies for its implementation on CAV. This paper studies the impact of the lateral wander of the traffic on pavement performance, considering its fatigue and permanent deformation resistance. This impact can be used to define limits for the wander to minimize distresses on the pavement. The results of this study allow us to conclude that for a pavement with a 10 cm asphalt layer, the wander effect is more significant for fatigue life. A pavement life increase of 20% was observed for a wander of 0.2 m, while for 0.6 m, the fatigue life can increase up to 48%. For the permanent deformation, a pavement life increase of 2% for a wander of 0.2 m was observed, but for 0.6 m, the pavement life can be increased up to 34%. Full article

Recently, in Chile, infrastructure asset value has been incorporated into highway concession contracts. However, the current valuation model used for rigid pavements is not adapted to the standards and conditions of such projects. This study develops a valuation model for rigid pavements of interurban highway concessions and evaluates it in a case study. The proposed model captures the loss in asset value associated with the performance degradation over time, considering a typical Jointed Plain Concrete Pavement (JCPC) configuration. The value is calculated using performance indicators that represent the structural capacity and level of service provided to road users. The model represents a significant improvement compared to current asset valuation models used in highway concessions. It enables the public agency to objectively evaluate the preservation of asset value carried out by the private partner during the concession. Additionally, it could also be used as a tool to establish payments between infrastructure stakeholders. Some of the concepts applied could also be relevant for other highway assets existing in Public–Private Partnership (PPP) projects. Full article

This work presents a discussion of the basic properties of broken mineral limestone aggregates with the specification of the properties affecting the fracture toughness of concretes made with these aggregates. To determine the influence of the grain-size distribution of coarse aggregates for each concrete series, two types of aggregate grain were used, with maximum grain sizes of 8 mm (series of concrete L1) and 16 mm (series of concrete L2). Fracture-toughness tests were carried out using mode I fractures in accordance with the RILEM Draft recommendations, TC-89 FMT. During the experiments the critical stress-intensity factor $\left(K_{\mathrm{I}\mathrm{c}}^{\mathrm{S}}\right)$ and crack-tip-opening displacements ($CTOD\mathrm{c}$) were determined. The main mechanical parameters, i.e., the compressive strength (f_cm) and splitting tensile strength (f_ctm), were also assessed. Based on the obtained results, it was found that the grain-size distribution of the limestone aggregate influenced the concrete’s mechanical and fracture-mechanics parameters. The obtained results showed that the series-L2 concrete had higher strength and fracture-mechanics parameters, i.e.,: f_cm—45.06 MPa, f_ctm—3.03 MPa, $K_{\mathrm{I}\mathrm{c}}^{\mathrm{S}}$—1.22 MN/m^3/2, and $CTOD\mathrm{c}$ —12.87 m10⁻⁶. However, the concrete with a maximum grain size of 8 mm (series of concrete L1) presented lower values for all the analyzed parameters, i.e.,: f_cm—39.17 MPa, f_ctm—2.57 MPa, $K_{\mathrm{I}\mathrm{c}}^{\mathrm{S}}$—0.99 MN/m^3/2, and $CTOD\mathrm{c}$ —10.02 m10⁻⁶. The main reason for the lower fracture toughness of the concretes with smaller grain sizes was the weakness of the ITZ in this composite compared to the ITZ in the concrete with a maximum grain size of 16 mm. The obtained test results can help designers, concrete producers, and contractors working with concrete structures to ensure the more conscious composition of concrete mixes with limestone aggregates, as well as to produce precise forecasts for the operational properties of concrete composites containing fillers obtained from carbonate rocks. Full article

The Department of Highways (DOH), Thailand, has adopted both empirical and mechanistic approaches for flexible pavement analysis and design. Recently, the deflection-based design approach has been comprehensively reviewed by the DOH for the possible adoption of national design standards and practices. One of the key reasons is that Thailand’s road authorities, i.e., the DOH and the Department of Rural Roads (DRR), have considered the falling weight deflectometer (FWD) for the new construction and rehabilitation of road pavements. In addition, the FWD is widely accepted as the non-destructive test for deflection measurement and structural capacity evaluation. Ultimately, the implication of FWD deflections for in-house pavement analysis and design shall be developed and proposed to Thailand’s road authorities. Therefore, this study presents the deflection-based approach of flexible pavement design in Thailand. The FWD and a standard Thai truck were selected as the main loading applications in this study. A typical FWD loading stress of 700–800 kPa was practically adopted by the DOH and compared with a standard 10-wheel 25-ton truck with a tandem axle-dual wheel configuration with a tire pressure of 690 kPa. The layered elastic analysis was performed to calculate the pavement responses. The results suggest that the flexible pavement design based on a deflection-based approach is simple, practical, and conservative. Full article