Bridge Research Articles

Surface Morphology and Remaining Geometric Parameters of Corroded Members on Bailey Truss

Abstract Bailey truss has been widely used in temporary constructional structures of bridges, and is reusable. In the service duration, Bailey truss is commonly exposed to corrosion threats due to the failure of anti-corrosion coatings, resulting in corrosion damage on members which induces degradation of its structural behavior. This paper presents an investigation on the corrosion damage of a Bailey truss which had been in service for eight years in the Northeast China. A total of 18 member segments were obtained from the chords, diagonals, and verticals of the Bailey truss, and were scanned by a 3D laser scanner after clearing the paint and rust. Then reverse modeling was performed based on the 3D coordinates of the specimen surfaces. The surface topography was discussed for different members on the basis of the separated roughness component, the residual thickness was analyzed for plates, and the residual cross-sectional area and moment of inertia about axes of the members were calculated and discussed. Coupon tests were carried out on corroded specimens from chords, diagonals, and verticals to quantitatively analyze the degradation of corroded Bailey truss. It was found that the corrosion damage on flanges was more severe than that on webs, in terms of the surface roughness and thickness loss. The corrosion status can be influenced by the microstructures and serving location. Upon the true values of the remaining cross-sections, it was concluded that the chords, diagonals, and verticals of the Bailey truss all exhibited the largest loss ratio in moment of inertia about y axis and the smallest loss ratio in cross-sectional area. The vertical member had the largest dispersion of average nominal loss rates, especially for moment of inertia about y axis, whose maximum and minimum values differed by 157.1%. A practical method for estimating the residual cross-sectional area and moment of inertia was validated. In addition, the engineering mechanical parameters (the elastic modulus, yield strength, ultimate strength, and the elongation after fracture) of each member basically show linear degradation. The mechanical parameters of diagonal web are most affected by corrosion. There is 10% thickness loss in chord web with up to 27% loss bearing capability in 8 years, and the factor of safety with respect to a reference parameter is lowered.

Mathematical modeling of occlusion load on a screw-retained bridge prosthesis on straight universal conical and flat abutments

In this mathematical experiment, a comparative study of microdeformations and von Mises equivalent stresses arising in the elements of two orthopedic bridge structures with different abutment shapes was conducted using the finite element method. The strength limits of both structures were also compared. The structures under study had the same external geometry and corresponded to two premolars and the first molar. The difference between the models under study was in the superstructures that are inserted and fixed in the implants and serve as a support for artificial crowns. The first model used flat superstructures (or flat abutments), while the second model used conical superstructures (or universal multi-units). The data obtained indicate the clinical significance of choosing the optimal abutment shape when planning surgical interventions and predicting subsequent patient treatment results.

A Fast Identification Method for Seismic Responses of Bridge Structures by Integrating Digital Signal Features and Deep Learning

A method of bridge structure seismic response identification combining signal processing technology and deep learning technology is proposed. The short-time energy method is used to intelligently extract the non-smooth segments in the sensor acquired signals, and the short-time Fourier transform, continuous wavelet transform, and Meier frequency cestrum coefficients are used to analyze the spectrum of the non-smooth segments of the response of the bridge structure, and the response feature matrix is extracted and used to classify sequences or images in the LSTM network and the Resnet50 network. The results show that the signal processing techniques can effectively extract the structural response features and reduce the overfitting phenomenon of neural networks, and the combination of signal processing techniques and deep learning techniques can recognize the seismic response of bridge structures with high accuracy and efficiency.

Wireless Accelerometer Architecture for Bridge SHM: From Sensor Design to System Deployment

This paper introduces a framework to perform operational modal analysis (OMA) for structural health monitoring (SHM) by presenting the development and validation of a low-power, solar-powered wireless sensor network (WSN) tailored for bridge structures. The system integrates accelerometers and temperature sensors for dynamic structural assessment, all interconnected through the energy-efficient message queuing telemetry transport (MQTT) messaging protocol. Moreover, it delves into the details of sensor selection, calibration, and the design considerations necessary to address the unique challenges associated with bridge structures. Special attention is given to the solar-powered aspect, allowing for extended deployment periods without the need for frequent maintenance or battery replacements. To validate the proposed system, a comprehensive field deployment was conducted on an actual bridge structure. The collected data were transmitted through MQTT messages and analyzed by means of OMA. Comparative studies with traditional wired systems underscore the advantages of the solar-powered wireless solution in terms of sustainability, scalability, and ease of deployment. Results from the validation phase demonstrate the system’s capability to provide accurate and real-time data needed to assess the health state of the monitored asset. This paper concludes with insights into the practical implications of adopting such a solar-powered WSN, emphasizing its potential to revolutionize bridge health monitoring by offering a cost-effective and energy-efficient solution for long-term infrastructure resilience.

Biotechnology for Global Sustainability: Innovations, Applications, and Challenges

Biotechnology, from a global perspective, involves applying biological systems, organisms, or derivatives to develop innovative products and processes that address global challenges and enhance the quality of life. As an interdisciplinary field bridging biology, technology, and engineering, biotechnology significantly impacts critical sectors, including healthcare, agriculture, environmental management, and industrial processes. In healthcare, biotechnology drives advancements in vaccines, gene therapy, personalized medicine, and diagnostic tools, improving disease prevention and treatment. Agricultural biotechnology focuses on developing genetically modified (GM) crops with higher yields, resistance to pests, and adaptability to climate change, ensuring food security. Additionally, it enhances livestock breeding and productivity. Environmental applications of biotechnology include bioremediation to combat pollution, development of biofuels to reduce reliance on fossil fuels, and creation of biodegradable materials to mitigate waste. In industrial processes, biotechnology optimizes manufacturing efficiency through the use of enzymes and microorganisms, contributing to sustainable production. Globally, biotechnology addresses pressing challenges like food insecurity, climate change, health inequality, and environmental degradation. Its role in sustainable development is critical, fostering eco-friendly solutions and improving the resilience of economies and societies. However, the field raises ethical and regulatory concerns, such as the risks of genetic engineering and the equitable distribution of benefits. International collaboration among governments, industries, and scientists is essential to ensure responsible innovation and maximize biotechnology’s potential to improve global well-being. As a transformative science, biotechnology continues to shape the future, balancing innovation with sustainability and equity.

Generalization of anomaly detection in bridge structures using a vibration‐based Siamese convolutional neural network

Generalization of anomaly detection in bridge structures using a vibration‐based Siamese convolutional neural network

Application of dynamic vibration dampers for vibration protection of bridge structures

Introduction. The increase in traffic intensity and the prospects for the development of high-speed railway transport require solving the problem of the effectiveness of vibration protection of transport infrastructure facilities by developing innovative solutions. Currently, the issues of combating vibration in relation to the span structures of bridges and overpasses are insufficiently studied. The purpose of the work is to study the promising directions of vibration protection of bridge structures based on the use of dynamic vibration dampers.Research methodology. To achieve the goal of research and implementation of effective technical solutions in the field of vibration protection of bridge structuresimproved design of dynamic vibration damper is proposed in which inertial mass is fixed on two springs, upper of which is connected to structure protected from vibration, and lower spring to base or foundation of object. Oscillations are damped due to oscillations in antiphase due to free and forced oscillations of auxiliary inertial masses protected from vibrations. This technical solution makes it possible to balance forces of elastic interaction of damping device and object protected against vibration and moments from these forces.Results. As a result of experimental studies of the prototype of the improved dynamic vibration damper installed on the vibration stand, it was found that the vibration levels in all directions significantly decreased, including in the vertical direction by 5.7 times.Discussion and conclusion. The obtained positive results of experiments and the relative simplicity of the proposed design make it possible to propose this method of vibration protection of superstructures for both newly designed and already in operation facilities. It is especially important to minimize the possibility of resonant phenomena and pitching. The results of the study will make it possible in the future to ensure the effectiveness of vibration protection of oscillating machines, mechanisms and infrastructure facilities.

Recommendations for Active-Learning Kriging Reliability Analysis of Bridge Structures

Recommendations for Active-Learning Kriging Reliability Analysis of Bridge Structures

Microstructure Regulation and Fabrication of Epoxy-based Conductive Films with Excellent Electrical and Thermal Conductivity, Adhesion, Toughness, and Flexibility

The electrically conductive adhesive films (ECAFs) are new materials used for large-format bonding in microelectronics packaging. However, improving its electrical and thermal conductivity, adhesion, and flexibility simultaneously has been a challenge. In this study, silver powder with different particle sizes and poly(3,4-ethylenedioxythiophene)/poly(styrene sulfonate) (PEDOT/PSS) were used to create a high-efficient multi-scale conductive bridge structure. This reduced the volume resistivity from 7.30×10-4 Ω·cm to 3.80×10-4 Ω·cm, with lower silver powder content. The thermal conductivity improved from 9.074 W/m·K to 9.124 W/m·K, and adhesion performance between the epoxy matrix and the metal increased from 6.85 MPa to 8.08 MPa. Furthermore, the addition of hydroxyl-functionalized polyurethane materials enhanced the toughness without significantly affecting its electrical, thermal, and adhesion properties. This study successfully prepared epoxy-based conductive adhesive films with a combination of electrical conductivity, thermal conductivity, adhesion, and flexibility, while significantly reducing costs due to the reduction in silver powder content.

Full-Locked Coil Ropes with HDPE Sheath: Studies of Mechanical Behavior of HDPE Under Accelerated Aging.

In accordance with German guideline ZTV-ING Part 4, full-locked coil ropes are provided with a three-layer corrosion protection coating based on epoxy resin and polyurethane, which must be renewed regularly. An alternative method is to use a coating of high-density polyethylene (HDPE), which is extruded onto the rope. In this article, the mechanical behavior of the thermoplastic material is studied, taking into account various accelerated aging processes, which are derived from the climatic boundary conditions of a real bridge structure and implemented in tests. In addition to the quasi-static material behavior, which is described using the uniaxial tensile test, the cyclic conditioning, relaxation, type of production and oxidation stability are also investigated. Finally, the results obtained are evaluated with regard to the applicability of the material as corrosion protection for full-locked coil ropes.

Seismic Drift Estimates of Corroded Piers: A Multihazard Approach Utilizing 3D‐IDA Analysis With Time Stamps Considering Climate Change Effects

ABSTRACTThe compounding effect of seismicity, exposure to corrosion, and climate change in regions such as North America pose significant challenges for bridge design engineers, as the multihazards impact on the seismic performance of bridge structural systems remains underexplored. While drift ratio is the most widely used parameter in probabilistic seismic demand assessment, existing models predominantly concentrate on seismic intensity levels, overlooking the increase in demand and the reduced deformation capacity, both being affected by corrosion‐induced damage and climate change. Therefore, developing an evaluation framework for the multihazard seismic vulnerability of deficient bridges is an emerging priority in the field. To address this need, a methodology is proposed here that uses data collected from field inspections to quantify the accumulation of historic corrosion damage and forecast future corrosion propagation. Climate change scenarios derived from future climate forecast models are used to project the temperature and relative humidity changes up to the year 2100; the rate of reinforcement corrosion is quantified based on these scenarios. Utilizing incremental dynamic analysis (IDA) across a projected timeline, expressions are derived for the time evolution of drift demand in existing reinforced concrete circular piers over the lifetime of the bridge. By using these results, drift demand expressions are derived for different climate change scenarios. The influence of design parameters (e.g., concrete cover, chloride diffusion coefficient, and aging factor) on the drift demands is evaluated using Monte Carlo simulation. The proposed expressions serve as a benchmark for bridge engineers to study the seismic performance of bridge structures in multihazard environments.

A novel data-driven bridge monitoring data prediction framework using improved intelligent optimization-assisted deep learning

Bridge monitoring data prediction plays a crucial role in maintaining the serviceability and safety of bridges. To assess the performance of bridge structures in advance, an accurate and robust prediction model for measurement data prediction is needed. In this context, this paper presents a novel hybrid prediction model called IGWO-VMD-IGWO-LSTM, which aims to improve the accuracy and generalization ability of bridge monitoring data prediction. First, the proposed model incorporates variational mode decomposition (VMD) and an improved gray wolf optimization (IGWO) algorithm to decompose the measured data into several intrinsic mode functions (IMFs) to capture the signal’s features comprehensively. Then, long short-term memory (LSTM) models are established individually for each IMF, with hyperparameters optimization using the IGWO algorithm. Finally, the integrated reconstructed subsequences yield the prediction results of the proposed IGWO-VMD-IGWO-LSTM model. Thus, the proposed framework avoids exploring the complex internal mechanism of bridge behavior evolution. The measurement data collected from a real bridge demonstrates the feasibility of the proposed prediction method, and different deep learning models are used for comparison. The results demonstrate a significant improvement in prediction performance comparison with the other concerned models, highlighting the strong generalization ability and robustness of the proposed IGWO-VMD-IGWO-LSTM model.

Numerical study of the asynchronous excitation effect of Boumerdes’ earthquake on a bridge behavior

This paper represents the numerical analysis of asynchronous excitation effects on a bridge response due to the Boumerdes earthquake, using the finite element method in modeling, and the Newmark method for dynamic response analysis. The influence of the time delay of excitation between the supports on the response of structure is investigated and study how these variations can affect structural behaviour during seismic events. The dynamic displacements, normal, and shear forces and bending moments are computed through detailed simulations. The obtained results show that due to the non-uniformity in the earthquake excitation, changes in qualitative and quantitative features of dynamic displacements of the bridges. This will consequently subject the bridges to increased displacements hence compromising their structural safety and integrity. In fact, the analysis also underlines that, due to non-uniform seismic forces, the distribution of normal and shear efforts, along with bending moments, gives important concentrations of stresses that were underestimated under uniform loading conditions. From these observations, one underlines the importance of non-uniform distribution of seismic loading during bridge design or evaluation. It provides useful data to the engineers and designers who will implement the improvement in the seismic resistance of bridge structures in earthquake areas.

Study on Sensitivity of Uncertainty Factors in Seismic Demand Analysis of Continuous Girder Bridges with Seismic Isolation Design

In order to clarify the influence of the uncertain parameters of a bridge numerical model for seismic isolation design on the calculation results of structural seismic demand and to improve the accuracy of bridge seismic isolation design, a refined numerical model of a seismic isolation continuous girder bridge was established. The uncertainty of the model parameters was sorted out at two classification levels of the seismic isolation device system and the non-isolated system, and the sensitivity of the structural parameters was systematically analyzed by using the tornado diagram and the first-order second-moment method. The uncertain factors that have a great influence on the seismic response of the bridge structure in the seismic isolation design are bulk density coefficient, bearing friction coefficient, clay ultimate resistance, damping ratio, elastic modulus, clay ultimate deformation, and isolation bearing fusing force. The impact of the seismic isolation bearing’s melting force is particularly significant during periods of low peak acceleration. It was observed that the selection results remained largely unchanged despite the consideration of the collision effect. This finding serves as a valuable reference for the design and calculation of seismic isolation measures in continuous beam bridges.

Analysis of numerical models of an integral bridge resting on an elastic half-space

Abstract The paper presents three methods of the numerical modeling of a 60 m long integral bridge structure resting on an elastic half-space. For the analysis, three bridge models were built using Abaqus FEA software. Models A and C represent complex three-dimensional numerical models consisting of the bridge structure and the soil layer beneath it. The soil layer on which the bridge is resting was modeled as a homogeneous, isotropic, continuous, and elastic semi-infinite body elastic half-space. Model B represents a simple three-dimensional numerical model consisting of just the bridge structure. The stiffness of the soil layer beneath the structure in model B was modeled with spring constants derived for shallow footing foundation based on the theory for an elastic half-space. This model represents an engineering approach to the design of an integral bridge. In all models, the bridge deck is monolithically connected with abutment walls and intermediate piers. The bridge is made of cast-in-situ reinforced concrete. All material constants used in the analysis are presented in the table. Self-weight, uniformly distributed load, and thermal longitudinal expansion of the bridge deck were applied to the bridge models. Due to the nonlinear boundary condition used in the supports of the bridge model A, such as contact and friction, the superposition principle cannot be used in the calculations of this model. For this reason, all the loads involved in all bridge models were combined into a single load case and the large displacement formulation was used in the static analysis. The self-weight of the soil layer beneath the structure was omitted in the analysis. The author is focused on the method of modeling an integral bridge structure resting on elastic soil. For the purpose of this paper, only two piers from each model were selected, from which the internal forces and displacements were compared. Based on the analysis, it was concluded that it is possible to design an integral bridge by building its simplified numerical model, once the conditions given in the conclusions are met.

Seismic Response Analysis of Continuous Girder Bridges Crossing Faults with Assembled Rocking-Self-Centering Piers

Under the action of cross-fault ground motion, bridge piers can experience significant residual displacements, which can irreversibly impact the integrity and reliability of the bridge structure. Traditional seismic mitigation measures struggle to effectively prevent multi-span chain collapses caused by the tilting of bridge piers. Therefore, it is of practical engineering significance to explore the effectiveness of rocking self-centering (RSC) piers as seismic mitigation measures for such bridges. In this paper, cross-fault ground motion with sliding effects is artificially synthesized based on the characteristics of the fault seismogenic mechanism. A finite element model of a cross-fault bridge is established using the OpenSees platform. The applicability of RSC piers to cross-fault bridges is explored. The results show that RSC piers can significantly reduce residual displacement during cross-fault ground motions, facilitating rapid recovery after an earthquake. RSC piers significantly reduce residual displacement in cross-fault bridges, with the most notable vibration reduction effects observed in piers adjacent to the fault. When an 80 cm fault displacement occurs, the vibration reduction rate reaches 48%. Additionally, when the fault’s permanent displacement increases the risk of pier toppling, the vibration reduction effect of the RSC pier is positively correlated with the degree of fault displacement. However, the amplification effect of RSC piers on the maximum relative displacement of bearings in cross-fault bridges cannot be ignored. In this study, for the first time, RSC piers were assembled on bridges spanning faults to investigate their seismic damping effect. When the degree of fault misalignment is greater than 60cm, the seismic damping effect of RSC abutments is positively correlated with the degree of fault misalignment, and its amplifying effect on the maximum relative displacement of the bearing becomes more and more obvious with the increase of permanent displacement. For example, when the fault misalignment degree is 60cm, the vibration reduction rate is 39%, and when the fault misalignment degree is 90cm, the vibration reduction rate is 54%. Designers should rationally configure RSC piers according to the specific bridge and site conditions to achieve optimal vibration reduction effects.

A Pressure-Bearing Microwave Transmission Line for Rapid Energy-Efficient Manufacturing Systems of High-End Composite Parts

Currently, a 2-port microwave transmission line with a glass window is usually used to transmit microwave energy to a pressure vessel while sealing the high-pressure gas. In this situation, the damage of the brittle glass window will inevitably result in disastrous accidents. In this paper, the idea of a “2+4”-port microwave transmission line is first proposed to solve this problem. A 4-port waveguide bridge structure is connected to the input port of a traditional 2-port structure, which can release the high-pressure gas safely when the glass window of the 2-port microwave transmitting structure fails. To test this idea, a “2+4”-port microwave transmission line at 2.45 GHz was designed and fabricated. The effectiveness of the whole system in microwave transmission was validated by both simulations and experiments. A high microwave transmittance of more than 97% in the simulation and 91% in the experiment was achieved. The long-time transmission of 15-kW microwave energy, 5 times higher than the previous work, was realized. Moreover, the effectiveness of the transmission line in releasing high-pressure gas (0.6 MPa) was validated by a series of fluid-structure interaction simulations. This research proposes a new transmission structure for transmitting microwave into a pressurized environment safely and efficiently, which can be promoted to a series of applications including vacuum electron devices, microwave ovens, and so on.

Bridge Displacements Monitoring Method Based on Pixel Sequence

In light of the challenges posed by intricate algorithms, subpar recognition accuracy, and prolonged recognition duration in current machine vision for bridge structure monitoring, this paper presents an innovative method for recognizing and extracting structural edges based on the Gaussian difference method. Initially, grayscale processing enhances the image’s information content. Subsequently, a Region of Interest (ROI) is identified to streamline further processing steps. Following this, Gaussian check images at different scales are processed, capitalizing on the observation that edges show reduced correspondence to the Gaussian kernel. Then, the structure image’s edges are derived using the difference algorithm. Lastly, employing the scale factor, the algorithm translates the detected edge displacement within the image into the precise physical displacement of the structure. This method enables continuous monitoring of the structure and facilitates the assessment of its safety status. The experimental results affirm that the proposed algorithm adeptly identifies and extracts the structural edge’s geometric characteristics with precision. Furthermore, the displacement information derived from the scale factor closely aligns with the actual displacement, validating the algorithm’s effectiveness.

High-Cycle Fatigue Behaviour and Structural Robustness of Glass Fibre-Reinforced Polymer Tiled Web-Core Sandwich Panel Unit Cells in Load-Bearing Structures

This paper explores the fatigue behaviour and robustness of tiled web-core sandwich panels used in glass fibre-reinforced polymer bridges, which are increasingly favoured for their lightweight and corrosion-resistant properties. Fatigue tests are conducted on unit cell specimens with manually induced crack initiation, simulating accidental damage scenarios in glass fibre-reinforced polymer bridge components. The objective is to assess the integrity of individual unit cells when subjected to a localized force at the top flange after damage initiation. The fatigue tests reveal three phases in the behaviour of a tiled unit cell. Initially, there is a substantial rapid stiffness degradation with crazing crack appearance within the cross-section. Subsequently, a plateau phase occurs, with limited stiffness degradation and stable crazing cracks, the duration of which depends on the applied fatigue load. Lastly, rapid stiffness degradation with substantial crack growth leads to ultimate failure within roughly a thousand cycles. Further analysis using digital image correlation reveals strain concentrations at the location of crazing cracks and crack propagation occurring interlaminarly but not through the plies of the top and bottom flanges, ensuring a robust design. This research enhances the understanding of the tiled sandwich panels, offering prospects for resilient load-bearing structures in glass fibre-reinforced polymer bridges and structural engineering applications.

Two‐step rapid inspection of underwater concrete bridge structures combining sonar, camera, and deep learning

AbstractUnderwater defects in piers pose potential hazards to the safety and durability of river‐crossing bridges. The concealment and difficulty in detecting underwater defects often result in their oversight. Acoustic methods face challenges in directly achieving accurate measurements of underwater defects, while optical methods are time‐consuming. This study proposes a two‐step rapid inspection method for underwater concrete bridge piers by combining acoustics and optics. The first step combines macroscopic sonar scanning with an enhanced YOLOv7 to detect and locate piers and defects. Second, the camera approaches the defects for image acquisition, and an enhanced DeepLabv3+ is used for defect identification. The results demonstrate an average mean average precision@0.5 of 95.10% for defect and pier detection, and an mean intersection over union of 0.914 for exposed reinforcement and spalling identification. The method was applied to a real river‐crossing bridge and reduced inspection time by 51.2% compared to traditional methods for assessing a row of 11 piers.