Bridge System Research Articles

Modelling, Analysis and Validation of Hydraulic Self-Adaptive Bearings for Elevated Floating Bridges

Conventional floating bridge systems used during emergency repairs, such as during wartime or after natural disasters, typically rely on passive rubber bearings or semi-active control systems. These methods often limit traffic speed, stability, and safety under dynamic conditions, including varying vehicle loads and fluctuating water levels. To address these challenges, this study proposes a novel Hydraulic Self-Adaptive Bearing System (HABS). The system integrates real-time position closed-loop control and a flexible support compensation method to enhance stability and adaptability to environmental changes. A modified three-variable controller is introduced to optimise load response, while a multi-state observer control strategy effectively reduces vibrations and improves traffic smoothness. A 1:15 scale prototype was constructed, and a co-simulation model combining MATLAB/Simulink and MSC Adams was developed to simulate various operational conditions. Results from both experiments and simulations demonstrate the HABS’s ability to adapt to varying loads and environmental disturbances, achieving a 72% reduction in displacement and a 54% reduction in acceleration. These improvements enhance traffic speed, stability, and safety, making the system a promising solution for emergency and floating bridges, providing superior performance under challenging and dynamic conditions.

Comparative Analysis of Common Structural Systems for Pedestrian Bridges in Kuwait

Introduction Pedestrian bridges are crucial urban infrastructure, providing safe passage over roads, railways, and waterways. Different structural systems like trusses, steel girders, and reinforced concrete beams are used, but more research is needed to determine the best design for specific regional contexts. Methods This research paper presents a comparison of various structural systems for pedestrian bridges, with a focus on a practical case study in Kuwait. The study evaluates five common pedestrian bridge designs: steel, concrete, and three truss arrangements. The designs were assessed based on multiple criteria, such as cost, construction time, structural weight, carbon emissions, and vibration performance. Using a decision-making matrix (DMM) and engineering judgment, Truss 3 (X-bracings without verticals) was identified as the optimal design. It features a unique bracing system that enhances its properties. Truss 3 was found to be the lightest design at 561.6 kN, with moderate CO2 emissions of 64.2 tons and a cost of 4288.5 KD per span. Detailed design and safety checks were conducted using ETABS software. The final design was detailed and presented using Autodesk Revit. Results The findings highlight the importance of using integrated frameworks and multi-criteria decision analysis (MCDA) to select suitable structural systems that meet technical and regional sustainability goals. Conclusion This research aims to provide a robust solution tailored to the unique conditions of Kuwait, ensuring safety, efficiency, and sustainability for pedestrian bridge infrastructure.

USE OF FLOATING (PONTOON) BRIDGES FOR THE ENGINEERING COVER OF TRANSPORT FACILITIES

Purpose. The purpose of this work is to investigate the topic of floating (pontoon) bridge systems as an option for overcoming water obstacles, a means of technical cover for national transport infrastructure facilities, and to analyze the current state of application of existing floating system property in order to determine the directions of further research in this area. Methodology. Research of existing floating (pontoon) bridge systems, their classification and technical characteristics, in the context of means of technical cover of important transport facilities and overcoming water obstacles in the conditions of modern warfare. Findings. Provision of temporary pontoon bridges is carried out during the creation of duplicate bridge crossings (ferry crossings) and the restoration of traffic in areas with destroyed transport facilities. Pontoons from sets of floating bridges can be used as platforms for installing special construction equipment during the construction (restoration) of transport facilities. A systemic analysis of floating (pontoon) bridges as an option for overcoming water obstacles for the technical cover of transport infrastructure facilities was conducted. All available floating (pontoon) means that can be used for their intended purpose were considered, and the need for modeling floating (pontoon) systems to expand their application possibilities was determined. Originality. The scientific interest lies in the fact that after conducting an analysis of the classification and technical characteristics of the available means of floating (pontoon) bridge systems, the main directions for further research and their simulations have been established, which will create conditions for their optimized application, taking into account the challenges of today in overcoming wide water obstacles, technical cover objects of the national transport infrastructure by laying duplicate temporary floating bridges (ferry crossings). Practical value. Pontoon systems for bridges are essential for providing technical cover for national transport infrastructure objects. Given the limited number of identical systems available for pontoon bridge systems, it is relevant to research the adaptation of different pontoon systems in one crossing, thereby expanding their application possibilities and providing all the necessary conditions for overcoming the widest water obstacles in Ukraine.

Study on the Effect of Temperature on the Alignment of a Long-Span Steel–Concrete Composite Beam Track Cable-Stayed Bridge

In order to study the effect of temperature on the alignment of a long-span special track bridge, this paper provides a theoretical basis and technical support for bridge design, construction and later operation. This research established the section model of the steel-hybrid beam by COMSOL, and the internal temperature field, transverse temperature, and vertical temperature gradient were analyzed. The Midas Civil bridge model analysis system was established to investigate the influence of temperature difference and temperature gradient on the vertical deformation of the whole bridge. Based on the temperature and displacement monitoring system of the Chongqing Nanjimen track bridge, the temperature and displacement data in 2023 were obtained for comparative analysis. The results show that the temperature field inside the composite beam presents a nonlinear distribution, the daily temperature difference can reach 26.0 °C, and there is a significant temperature gradient between the steel beam and the concrete. The highest temperature is 60.3 °C at 15:00 when the temperature difference between the upper and lower edges of the concrete slab is 11.1 °C, and the daily transverse temperature gradient is 3.2 °C, 5.3 °C and 7.4 °C, respectively. Under the temperature difference in the system, the maximum displacement of the main beam is 92.3 mm, and the mid-span displacement is 132.1 mm under the positive temperature difference. Based on the measured data for the whole year, it is found that the displacement of the main beam under the combined action of ambient temperature and solar radiation significantly exceeds the influence of a single temperature. The research shows that temperature change has an important impact on the stability and durability of the bridge, and temperature monitoring and management should be strengthened in the design and operation stage to ensure the bridge’s safety and smooth operation of the train.

3D Pixelwise damage mapping using a deep attention based modified Nerfacto

Recent advancements in structural health monitoring have highlighted the necessity for accurate three-dimensional (3D) damage mapping on digital twins, moving beyond traditional methods such as photogrammetry, which frequently struggle to capture intricate planar surfaces. To address this limitation, this paper proposes a new advanced 3D reconstruction method and its integration with 3D damage mapping techniques. As the 3D reconstruction method, an Attention-based Modified Nerfacto (ABM-Nerfacto) model is developed, and is integrated with an advanced damage segmentation method. Using a three-span continuous bridge with concrete piers as an example structure, and concrete cracks as the example damage, the state-of-the-art STRNet is utilized for crack segmentation. Through extensive parametric studies and comparative evaluations, the proposed ABM-Nerfacto model was demonstrated to produce high-quality 3D reconstructions and corresponding damage mappings for this bridge system. This integrated approach provides a promising solution for comprehensive 3D digital twin-based structural health monitoring.

Modal analysis of natural dynamic frequency for a double deck cable-stayed steel bridge by using finite element method

Double-deck cable-stayed bridges are appropriate when there is a high traffic volume and little space for the structure. They combine road and rail transit to maximize the utilization of bridge structures and tackle traffic issues. This study investigates the fluctuations in the modal properties caused by several factors that impact the modal characteristics of bridges. The aim is to ascertain the system’s inherent frequencies, associated natural periods, and mode shapes. The modal analysis inquiry was conducted utilizing a software model grounded in the finite element method. The bridge deck slab, cable, pier, and pylon are discretized utilizing SHELL 181, CABLE 280, and BEAM 188 elements in this finite element model. The model’s dependability was validated by mesh convergence analysis and comparison with findings from prior research investigations. The cumulative mass participation factor analysis reveals that the bridge induces vibrations in 90% of the mass associated with the first five modes in the research of cumulative modal vibration. The application of prestressing force has significantly increased the natural frequencies of the bridges, resulting in a large rise. An increase in the damping ratio leads to a reduction in the natural frequency. Several factors, such as the existence or absence of prestressing force and different damping ratios in the bridge system, will affect free vibration results. Additionally, it can provide the foundation for subsequent fatigue analysis related to different dynamic loads.

Dynamic metabolic modeling of ATP allocation during viral infection.

Viral pathogens, like SARS-CoV-2, hijack the host's macromolecular production machinery, imposing an energetic burden that is distributed across cellular metabolism. To explore the dynamic metabolic tension between the host's survival and viral replication, we developed a computational framework that uses genome-scale models to perform dynamic Flux Balance Analysis of human cell metabolism during virus infections. Relative to previous models, our framework addresses the physiology of viral infections of non-proliferating host cells through two new features. First, by incorporating the lipid content of SARS-CoV-2 biomass, we discovered activation of previously overlooked pathways giving rise to new predictions of possible drug targets. Furthermore, we introduce a dynamic model that simulates the partitioning of resources between the virus and the host cell, capturing the extent to which the competition depletes the human cells from essential ATP. By incorporating viral dynamics into our COMETS framework for spatio-temporal modeling of metabolism, we provide a mechanistic, dynamic and generalizable starting point for bridging systems biology modeling with viral pathogenesis. This framework could be extended to broadly incorporate phage dynamics in microbial systems and ecosystems.

A deep kernel regression-based forecasting framework for temperature-induced strain in large-span bridges

The strain data from health monitoring systems of large-span bridges is influenced by various load effects, with the extraction and forecasting of temperature-induced strain being particularly significant for precise analysis and early warning of monitoring data. This paper presents a forecasting framework for temperature-induced strain in large-span bridges, employing a deep kernel regression (DKR) approach that integrates deep learning with Bayesian regression to enhance accuracy and certainty. Initially, this paper addresses the influence of additional response increment induced by vehicle strain effects and employs a robust data smoothing algorithm to extract temperature-induced effect components from measured strain data offline. Subsequently, a DKR model is proposed, integrating a long short-term memory (LSTM) layer with a fully connected layer. The output of the deep learning module serves as the kernel function parameter for the Gaussian process regression (GPR) module, and the GPR module with updated hyperparameters is used for time series forecasting. This method effectively extracts and utilizes time series features from historical data alongside key environmental factors, enabling real-time forecasting of strain effects and significantly improving the performance and utility of health monitoring systems in large-span bridges. Compared to commonly used time series forecasting algorithms, the algorithm proposed in this paper exhibits significantly improved accuracy, stability, and certainty. Through comparing the inference time, it was verified that the algorithm can meet the performance requirements of real-time inference, which underscores the model's potential as a robust tool in bridge structural health monitoring.

Optimization of a novel lateral energy dissipation system for cable-stayed bridge with short piers based on seismic vulnerability analysis

Cable-stayed bridges with short piers are susceptible to becoming the structural weak link in seismic resistance during strong earthquakes. Traditional lateral restraint systems, such as fixed and sliding bearing systems, may impose substantial lateral forces and displacement demands, affecting the entire bridge's seismic safety. A butterfly-shaped steel plate damper has been developed and integrated into a lateral energy dissipation system along with elastoplastic cables to address this. Given the significant computational challenges and the complexity of identifying the optimal parameters for the energy dissipation system, this paper combines the probabilistic seismic demand model (PSDM) with the response surface method (RSM) to propose the seismic vulnerability fitting optimization method (SVFOM). Based on SVFOM, utilizing a central composite design (CCD), 17 analysis scenarios that account for the parameter variations of the lateral energy dissipation system are established. By developing response surface functions for bearing damage (ys) and pier damage (yp) through the seismic response fitting of the structure across all scenarios, we determined the optimal parameters for the lateral energy dissipation system to minimize damage to both bearings and piers. The finite element model validation analysis, which demonstrated significant reductions in pier displacement and the probability of bearing damage, confirms the effectiveness of the SVFOM. Optimized parameters showed that the new lateral energy dissipation system can significantly enhance the lateral seismic performance of cable-stayed bridges with short piers. Compared to scenarios without energy dissipation and with lateral sliding bearings, they demonstrated that this optimized system reduces the relative displacement of the piers and girders by 56 % and the probability of complete bearing failure by 87 % while maintaining pier damage within acceptable limits. This optimized system offers a valuable reference for the seismic design of similar bridge structures.

Explainable machine learning model for load-deformation correlation in long-span suspension bridges using XGBoost-SHAP

The deformation of long-span suspension bridges in multiple loads is an important indictor to reflect their operation state. However, the correlation between multiple loads and structural deformation is difficult to quantify. Therefore, this study proposes an explainable machine learning model for the load-deformation correlation in long-span suspension bridges using eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP). Firstly, the structural health monitoring system for a suspension bridge was used to construct the dataset for the training and testing of XGBoost model. Herein, temperature, wind and vehicle loads were used as the input variables, while midspan deflections and expansion joint displacements were treated as outputs. Subsequently, the hyperparameters of XGBoost model were optimized using grid search and 5-fold cross-validation to ensure its prediction performance. Then, the prediction results were compared with other four machine learning methods (i.e., linear regression, artificial neural networks, gradient boosted decision trees and CatBoost). Finally, the correlation between different loads and displacement responses were explained by the SHAP method to identify the contribution of the loads on deformation. The results show that the XGBoost model has the highest prediction accuracy. Compared to vehicle and wind loads, temperature significantly affects the deformation of long-span suspension bridges during daily operation. The effects of temperature and wind on bridge deformation are independent, and there is no significant interaction between these two factors.

Evolution of modal properties in the non-proportionally damped coupled vehicle–bridge system

The modal properties of bridges are crucial parameters in engineering applications, and their variation caused by moving vehicles has been increasingly recognized in recent years. However, existing closed-form analytical expressions for the varying modal properties during vehicle passage exist only for simple structural configurations. This paper proposes an innovative method for analyzing the instantaneous modal properties of the system, considering general boundary conditions and the damping effect. First, only general boundary conditions are considered, and the results show that the location of the maximum system frequency shift depends on the mode shape. Then the damping effect is considered, observing that the system is non-proportionally damped in most cases, making it difficult to obtain a closed-form solution using existing methods. To solve this, we transform the system of second-order ordinary differential equations into a set of fourth-order ordinary differential equations and derive the closed-form solution for system’s modal properties. Based on this solution, we introduce the concept of Critical Coupling Damping (CCD), which defines the transition between the coupled description and the moving mass case. This work deepens understanding of changing modal properties during the traverse of sprung masses, and so has numerous potential engineering applications.

Framework for Identification of Bridges in Need of Monitoring Based on Maintenance History

Recently, advanced Internet-of-Things (IoT) technology has been implemented in structural health monitoring to help increase safety of infrastructure and the reliability of maintenance decisions. In this context, preliminary studies are required to identify infrastructure in need of monitoring. This study establishes a basis for the identification of bridges that require monitoring and selects the bridges for measurement in order to build an efficient IoT-based monitoring system for small and medium bridges. The bridges selected based on various maintenance histories and risk factors are expected to be utilized in comprehensively assessing the characteristics of the overall bridge network.

Seismic response of rocking bridge systems under three-dimensional ground motions

Compared to theoretical models, finite element methods provide greater versatility for dynamic response analyses of rocking bridges, especially when considering the influences of various nonlinear boundary conditions. A finite element modeling method based on fiber section elements for three-dimensional seismic analyses of rocking bridges is developed in this paper. This method solves the problem of energy dissipation and stiffness determination of the rocking interface. Based on the proposed modeling method, considering nonlinear boundary conditions (such as abutment-soil interaction, impact effect, and pile-soil interaction), the seismic responses of rocking bridges, including free rocking, prestressed rocking and prestressed rocking with dampers, under the excitation of three-dimensional ground motions are analyzed. The results show that: after reasonable design, the prestressed rocking bridge with dampers exhibits similar seismic responses to the cast-in-place bridge, and maintains a good self-centering ability. The responses of all the rocking bridges under bi-directional loading are greater than those under unidirectional loading. In contrast, vertical ground motion's influence on the response of the rocking bridges is minimal. Ignoring the pile-soil interaction significantly underestimates the seismic demand of the evaluated bridges, especially the free rocking bridge and rocking bridge with prestressed tendons only.

A novel solution for dynamic behaviors of multi-span bridge plates

The present paper draws a comprehensive analysis of the free vibration characteristics and discusses modal localization phenomena of multi-span bridge plate structures through an analytical method, numerical simulations, and experimental measurements. A novel analytical solution using the generalized superposition segment method (GSSM) is first proposed to investigate the transverse vibration of a multi-span bridge, which offers complete flexibility in describing arbitrarily classical boundary conditions. Furthermore, a new experimental setup achieves precisely simply supported boundary conditions, and scaled physical models of two- and three-span bridge plates are employed to validate the analytical solution. The effect of span length mismatch is studied by analyzing the resonant frequencies and mode shapes of a multi-span bridge plate with varying span lengths. The good consistency of results by theoretical analysis, numerical simulation, and experimental measurements indicate that the proposed analytical solution can solve the vibration problem of the multi-span bridge plate efficiently and reflect the real-world boundary condition. Finally, the two modal localization behaviors are observed in theoretical analysis and experimental measurement. Through analytical solutions, numerical simulations, and experimental measurements, this study enhances the understanding of the dynamic behavior of multi-span bridges. It provides a new theoretical benchmark for predicting vibrations of multi-span bridge systems and useful insights into the transient behavior of multi-span bridge plates, suggesting several fruitful avenues for future research, including exploring passive and active control systems and vibration suppression techniques.

Total Synthesis Analysis of Pseuboyenes D

In this work, we propose a total synthesis route for the antifungal agent Pseuboyenes D, a compound derived from Pseudallescheria boydii CS-793. Pseuboyenes D exhibits antifungal activity comparable to Amphotericin B while offering the advantage of a simpler structure, making it a promising candidate for clinical applications. The system became the focus of this analysis due to its regioselectivity, and after exploration, a [2+2] photocycloaddition and ring expansion strategy was adopted to construct the key bridged ring system. The route employs readily available substrates and mild reaction conditions, making it scalable and suitable for large-scale production. Computational analysis of the regioselectivity of the photocycloaddition revealed that the bridged adduct was thermodynamically favored over the fused system. The synthetic route was further diversified by incorporating functional group modifications using TMS derivatives, enhancing the potential for pharmacological applications. Overall, this work establishes an efficient and scalable synthetic pathway for Pseuboyenes D, paving the way for future applications in antifungal drug development.

Stability Analysis of Construction Factors for Partially Cable-Stayed Bridges with Multiple Towers and High Piers

Partially cable-stayed bridges have the characteristics of continuous rigid-frame bridges and cable-stayed bridges, making them a novel composite bridge system. This study focuses on the construction project of a multi-tower high-pier curved partially cable-stayed bridge to investigate the bridge’s stability during construction. The Midas/Civil software was used to establish a model for key construction stages of the bridge, considering structural linear elasticity and geometric nonlinearity. The study examines the impact of static wind loads, asymmetric construction of the main girder, closure sequence, and the load and detachment of the hanging basket on the bridge’s stability during construction. The results indicate that static wind loads have a significant impact on structural geometric nonlinearity, with a maximum reduction of 4.99%. Asymmetric construction at both ends of the main girder can cause structural instability and should be avoided. The geometric nonlinearity stability coefficient for the hanging basket load decreased by 10.83% during the maximum no-cable stage and by 7.84% during the cable stage, significantly affecting the stability during construction. A bridge closure sequence of side-span, secondary midspan, and midspan provides the most stable condition during the construction phase. The results of this study can inform the construction of similar partially cable-stayed bridges.

Dynamic Analysis of a Vehicle–Bridge System Under Excitation of Random Road Irregularities

This paper presents a comprehensive study of the dynamic response analysis of vehicle–bridge coupled systems, with detailed simulation methods for the vehicles, bridges, and wheel–road coupling relationships. The simulation of the entire vehicle–bridge coupling system is carried out using the open-source finite element analysis platform OpenSees. A novel three-dimensional wheel–road coupling element is introduced to model the interactions between the wheel and road nodes. This element facilitates precise computation of the dynamic responses within the vehicle–bridge coupled system, including both vehicle and bridge behaviors, along with the interaction forces between the wheels and the bridge surface. The coupling element consists of a wheel node and all potential road nodes on the bridge surface that the wheel may traverse. This configuration preserves the finite element model of the entire vehicle–bridge coupled system throughout the vehicle’s movement, thereby improving the efficiency of numerical simulations of vehicle–road interactions. The study accounts for the impact of random road irregularities on the dynamic responses of both the vehicle and the bridge. These irregularities are treated as input parameters for the wheel–road coupling element rather than being accounted for through the wheel–road interaction constraint equations, thereby improving the convenience of simulating random road irregularities.

Deep learning-based automated identification on vortex-induced vibration of long suspenders for the suspension bridge

Large amplitude vortex-induced vibration (VIV) of long suspenders, caused by vortex-shedding and wake flow, will decrease the service life of high-strength wires and its anchorage systems, hence listed as an essential monitoring indicator of the structural health monitoring system in the suspension bridges. Traditionally, a static vibration amplitude limitation is usually predefined and used to identify VIV from continuously monitored acceleration data of bridge suspenders. Due to the complexity of the starting vibration of the suspenders, it may not be able to flexibly adapt to the suspenders VIV under different conditions. In addition, transient but significant vibration events may not be captured since it relies only on static vibration amplitude limits without considering the temporal information of vibration. To address the above-mentioned issues, a novel framework to autonomously identify the suspenders VIV is proposed using the multimodal fusion techniques with deep neural networks. The main contributions of the methodology are: i) by calculating the wind field and vibration characteristic, two vibration response parameters are identified as indexes for the identification of suspenders VIV based on the significant difference method of big data analysis; ii) Two different modal information of time history images and power spectral density (PSD) sequences are used as inputs to the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) to extract the suspenders vibration response features from the time and frequency domain perspectives, respectively; and iii) The multimodal information is concentrated and enhanced by the multi-head attention (MHA) mechanism to achieve automated identification of the suspenders VIV. The proposed framework is validated with data collected from a full-scale long-span suspension bridge in comparison with the base model. The results show that the proposed framework can efficiently identify the full-cycle development process of the suspenders VIV. This study provides a convenient strategy for suspenders VIV identification, which can be used for bridge management and vibration mitigation device design.

Enhanced Multi‐Objective Optimization Model for Bridge Performance Assessment and Prediction, Based on Improved PCA, K‐Means Clustering, and Kaplan–Meier Survival Algorithm

ABSTRACTThe research proposes a hybrid algorithm model that combines model‐driven and data‐driven approaches for the direct application of bridge health monitoring technology in bridge management. This comprehensive study encompasses a series of analytical techniques and methodologies to build a multi‐objective optimization model for bridge performance assessment and prediction. It focuses on the processing of multi‐source heterogeneous data, selection of key sub‐parameters using Principal Component Analysis (PCA), enhanced K‐means clustering analysis, determination of structural component target thresholds, time‐dependent survival probability analysis, regression fitting, and timing prediction of the bridge system for both the components of double‐layer truss arch bridge and the bridge system. The initial phase of the study concentrates on the diversification and decentralization of monitored data from various sources, integrating and cleaning data obtained from different sources to ensure data quality and consistency. PCA technique is applied to identify key sub‐parameters that have significant impacts on the performance of structural components. Enhanced K‐means clustering analysis is carried out to effectively group and classify the identified key sub‐parameters. Numerical simulations, including structural nonlinear analysis, are conducted to determine the target thresholds of bridge structure, providing important benchmarks for performance evaluation. Finally, a multi‐parameter regression model is used to evaluate and update the performance of the bridge structure, taking into account survival probability (using the Kaplan–Meier method), maintenance history, and material deterioration to estimate the most critical time for the bridge system. A case study is conducted to validate the suggested comprehensive algorithms for a double‐layer truss arch combination bridge, which contributes to enhancing performance evaluation and predicting the most critical time for structural components and bridge system in the bridge management and maintenance practices. It should not be ignored that, the accuracy and reasonability of bridge structure system performance evaluation and prediction depend largely on the selection of target thresholds.

Link Slab Behavior in Continuous Bridge Systems: A Comparative Study of Finite Element and Analytical Approach

Link Slab Behavior in Continuous Bridge Systems: A Comparative Study of Finite Element and Analytical Approach