Bridge Maintenance Research Articles

Review of Bridge Structure Damping Model and Identification Method

Damping is a fundamental characteristic of bridge structures, reflecting their ability to dissipate energy during vibration. In the design and maintenance of bridges, the damping ratio has a direct impact on the safety and service life of the structure, thus affecting its sustainability. Currently, there is no suitable theoretical method for estimating structural damping at the design stage. Therefore, the modal damping ratio of a completed or under-construction bridge can only be obtained through field dynamic tests to ensure compliance with design specifications. To summarize the latest research findings on bridge structure damping models and identification methods, and to advance the development of damping identification techniques, this paper provides an in-depth review from several perspectives: Firstly, it offers a comprehensive analysis of the theoretical framework for structural damping. Secondly, it summarizes the damping models proposed by researchers from various countries. Thirdly, it reviews the research progress on identifying the modal damping ratio of bridge structures using time domain, frequency domain, and time-frequency domain methods based on environmental excitation. It also summarizes the methods and current status of identifying the modal damping ratio using artificial excitation. Finally, the future prospects and conclusions are discussed from three aspects: damping theory, test and identification method and data processing. This research and summary provide a solid theoretical foundation for advancing bridge structural damping theory and identification methods and offer valuable references for bridge operation and maintenance, as well as damage identification. From the perspective of modal parameter identification, it provides a theoretical basis for the sustainable development of bridges.

Evaluation of Load-Bearing Capacity in Japanese Arch Steel Aqueduct Bridge through Structural Redundancy Assessment

Structural redundancy assessment of steel aqueduct bridges is made by the analysis of a case study using the Musota Aqueduct bridge structure: a simply supported steel arch bridge erected in 1973 and a seven- span continuous steel aqueduct bridge. In this paper, as a case study, after the validation of the model, the structural redundancy of the Musota aqueduct bridge in Wakayama City with respect to its load-carrying capacity after the failure of hanging components due to corrosion was investigated. The conventional procedure for the assessment of redundancy makes use of static nonlinear structural analysis. A three-dimensional finite-element model of this bridge was developed to simulate its behavior. The results from the linear analysis are compared with those from the nonlinear analysis to investigate the appropriateness of the former in the evaluation of redundancy. A detailed nonlinear static finite element study is carried out into the hangers' components of the arch bridge in order to clarify the implications involved in the failure of redundancy. Finally, recommendations for prudent bridge maintenance methods are presented based on findings from the investigation.

Flow field analysis of self-sustained flutter of a wide-slotted bridge deck

This study delves into the flutter mechanism of a 5,000 m bridge with a wide-slotted deck, finding that the motion is self-sustained and not violently destructive. The system damping ratio is not fixed, and only one stable orbit exists. High-resolution PIV experiments at an experimental wind speed of 10.5 m/s measured the static and dynamic flow fields on the windward and leeward decks. The static results showed leading-edge separation on the windward deck within the reference range, while separation on the leeward deck was difficult to observe. Dynamic testing identified instantaneous vortices around the windward/leeward deck at each phase, with no signs of vortices in the wind speed vectors at all phases after phase-averaging, indicating that the vortex drift hypothesis is not valid. The analysis of the streamline pattern revealed periodic variations in leading-edge separation size and reattachment length on the windward deck during the vibration process, while the leeward deck showed consistently inconspicuous changes. Further examination uncovered a peculiar behavior in the horizontal wind speed profile on the leeward deck during the vibration process, attributed to dynamic changes in the height difference between the windward and leeward decks during flutter. The study suggests that the unusual wind speed profile on the leeward deck is caused by the dynamic changes in height difference between the windward and leeward decks during the flutter process, resulting in additional wind loading. These findings shed light on the complex dynamics of bridge flutter and have implications for the design and maintenance of long-span bridges.

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.

Dynamic Modeling and Analysis of Multi-Span Timoshenko Beams Under Moving Loads

Dynamic response analysis of multi-span beams is one of the important topics in the field of highway and railway engineering, which provides valuable guidance for the design, operation and maintenance of multi-span bridges. It is worth considering how to calculate the dynamic characteristics of multi-span beams quickly and conveniently. In this study, an effective analytical method is developed for the dynamic modeling and investigations of multi-span Timoshenko beams under moving loads by employing the assumed mode method (AMM). Based on Hamilton’s principle, the equation of motion of the Timoshenko multi-span beam subjected to moving loads is formulated and the natural frequencies are calculated. A comprehensive investigation is conducted on the dynamic responses of the multi-span Timoshenko beam considering different factors, including the length-to-thickness ratio, disorder degree, arrangement order, number of spans and related parameters of moving loads. In addition, the influence of the interval and velocity of the moving load series on the dynamic responses, including displacement, velocity and acceleration of the multi-span beam, are analyzed in detail. The theoretical calculation results of multi-span Timoshenko beams under moving loads are compared with numerical results obtained from ANSYS software, and the results are in good agreement. This demonstrates that the developed method, which utilizes the AMM to analyze the dynamic characteristics of multi-span beams subjected to moving loads, significantly simplifies the calculations and is well-suited for practical engineering applications.

Comprehensive durability assessment of in-service concrete bridges based on combination weighting and extenics cloud model

In recent years, with the continuous development of urban transportation, the durability of concrete bridge structures has become increasingly prominent. Many in-service concrete bridges exhibit issues such as cracks, excessive deflection, and a significant reduction in load-bearing capacity during their service life. To meet the requirements of sustainable development, it is urgent to assess the durability of bridges accurately. Therefore, this paper establishes a scientific and reliable evaluation index system for the durability of in-service concrete bridges. Based on a review of the literature and relevant standards and specifications, this paper establishes an evaluation index system for the durability of in-service concrete bridges and calculates the weights using a combination weighting method. The durability of the bridges is assessed using the extension cloud model theory, and MATLAB is utilized for efficient and accurate computation and analysis, ultimately determining the durability grades of the bridges. The method was applied to the durability assessment of five in-service concrete bridges, and the results were in high agreement with the measured data, proving its effectiveness and accuracy. The research results provide a scientific basis for the management and maintenance of concrete bridges, which can help extend their service life. Future studies will expand the sample to cover more bridge types to comprehensively assess and enhance the durability of bridges.

Automatic bridge inspection database construction through hybrid information extraction and large language models

Regular bridge inspections generate extensive reports that, while critical for maintenance, often remain underutilized due to their unstructured format. Traditional information extraction methods depend on intricate labeling systems that commonly require time-consuming and labor-intensive labeling. This paper presents a novel bridge inspection database construction method leveraging LLM-assisted information extraction. First, we introduce the pseudo-labelling method using a closed-source LLM to generate high-quality data. Then we propose the hybrid extraction pipeline to extract relevant information segments and process them by a generation-based IE model, fine-tuned on pseudo-labeled data. Finally, the extracted data is used to construct the bridge inspection database. The proposed method, validated with real-world data, not only demonstrates higher extraction precision than the closed-source LLM used for pseudo-labeling but also outperforms traditional methods in both data preparation time and extraction accuracy. This approach provides a scalable solution for more proactive and data-driven bridge maintenance strategies.

Comparative Analysis of Image Stitching Algorithms for Bridge Inspection Imaging Systems

This paper discusses an innovative vehicle-mounted device designed for efficient inspection of bridge undersides, aiming to address the challenges of manual inspections, such as being labor-intensive and inefficient. The device uses high-precision cameras to capture detailed images of bridge bottoms, facilitating a thorough condition assessment. It evaluates three feature point extraction algorithms for image stitching—Scale-Invariant Feature Transform (SIFT), Harris corner detection, and Speeded Up Robust Features (SURF)—to create complete visual representations of bridge undersides. Field tests on a prefabricated I girder bridge demonstrated the device's effectiveness in gathering and stitching images, with the SIFT algorithm performing best for girder bottoms, Harris corner algorithm for web and flange surfaces, and SURF for rapid image processing. This research provides a foundation for the rapid identification of visible defects on bridge superstructures, significantly benefiting bridge maintenance and safety evaluations.

TESTING OF MODELS OF BRIDGE DECKS WITH REINFORCED CONCRETE FIXED FORMWORK

In Ukraine, in the second half of the 20th century, the vast majority of highway bridges span structures were built from precast concrete. This was due to the requirement of construction industrialization in the USSR, which required the maximum use of prefab structures. Therefore, the bridge deck slabs had a significant number of longitudinal joints. The experience of maintenance of bridges prefabricated reinforced concrete span structures has shown that a significant number of defects occur in their slabs due to the presence of joints. Taking into account the above, the current state building regulations of Ukraine for bridge design indicate that in the case of using prefabricated reinforced concrete beams, their surface should be covered with a layer of cast-in-situ reinforced concrete with a thickness of at least 14 cm. Taking these requirements into account, reinforced concrete span structures of highway bridges are arranged mainly precast and cast-in-situ: installing of precast beams, concreting of the cast-in-situ slab above them. This design requires using of formwork for the slab installation. A promising direction in cast-in-situ bridge construction is using of various types of permanent formwork. However, their use has not been studied to date. Having studied the experience of using non-removable formwork, it is proposed to test series of samples to determine the suitability for further operation of one or another option, in addition to studying of the joint operation of non-removable formwork plates as part of the combined cross-section of the deck slab.

Study on Fracture Delay of High-Strength Bolts in Road Bridge Maintenance

In the maintenance work of highway and bridge engineering structures, the fracture delay of high-strength bolts is a content that needs to be focused on and researched. Based on this, the paper analyzes the fracture delay of high-strength bolts in highway bridge maintenance, including an overview of the fundamental research on fracture delay and related specific studies. It is hoped that this study can provide scientific reference for the reasonable maintenance of high-strength bolts, so as to ensure the overall maintenance effect of highway bridge projects.

Temperature gradient estimation of long-span concrete box girders using average conditional exceedance rate function

An accurate assessment of temperature gradients in box girders is crucial for design and maintenance of long-span bridges. Although the current bridge specifications have provided temperature gradient patterns, these existing specifications are insufficient to accurately describe temperature gradients of bridges in service period. In this article, a novel methodology for determining an efficient positive temperature gradient pattern considering condition dependent and whole design service life is proposed. Firstly, statistical analysis and curve fitting are performed by using the long-term temperature data collected through structural health monitoring system, which indicates that temperature gradient patterns can be described as exponential functions. Secondly, the representative values of temperature difference have been estimated using average conditional exceedance rate (ACER) functions, which can use short-term data and consider conditional dependencies to predict long-term extreme values. Finally, the temperature gradient patterns of box girder of bridges in the whole service life have been estimated. Compared with the gradient patterns in current Chinese specification, the proposed temperature gradient pattern demonstrates better applicability in a long-span continuous concrete box-girder bridge. This result is expected to provide a research reference for accurately assessment of temperature gradients in box girders, which is crucial for design and maintenance of long-span bridges.

Finite Element Modeling and Calibration of a Three-Span Continuous Suspension Bridge Based on Loop Adjustment and Temperature Correction.

Precise finite element modeling is critically important for the construction and maintenance of long-span suspension bridges. During the process of modeling, shape-finding and model calibration directly impact the accuracy and reliability. Scholars have provided numerous alternative proposals for the shape-finding of main cables in suspension bridges from both theoretical and finite element analysis perspectives. However, it is difficult to apply these solutions to suspension bridges with special components. Seeking a viable solution for such suspension bridges holds practical significance. The Nanjing Qixiashan Yangtze River Bridge is the first three-span suspension bridge in China. To maintain the configuration of the main cable, the suspension bridge is equipped with specialized suspenders near the anchors, referred to as displacement-limiting suspenders. It is the first suspension bridge in China to use displacement-limiting suspenders and their anchorage system. Taking the suspension bridge as a research background, this paper introduces a refined finite element modeling approach considering the effect of geometric nonlinearity. Firstly, based on the loop adjustment and temperature correction, the shape-finding and force assessment of the main cables are carried out. On this basis, a nonlinear finite element model of the bridge was established and calibrated, taking into account factors such as pylon settlement and cable saddle precession. Finally, the static and dynamic characteristics of the suspension bridge were thoroughly investigated. This study aims to provide a reference for the design, construction and operation of the three-span continuous suspension bridge.

Dynamic Load Balancing and Service Prioritization Algorithm for Cloud Computing Environments

Bridge infrastructure plays a critical role in ensuring the safe and efficient transportation of goods and people. This research paper investigates the strength characteristics of bridges with a focus on understanding the factors influencing their structural integrity and resilience. The study employs a comprehensive methodology that includes field inspections, laboratory testing, and advanced computational modeling techniques to assess the performance of various bridge types under different loading conditions. Findings reveal the complex interplay between design parameters, material properties, and environmental factors in determining bridge strength and durability. Moreover, the research highlights the importance of proactive maintenance strategies and innovative engineering solutions to enhance the resilience of bridge infrastructure against aging, deterioration, and extreme events. The insights gained from this study have significant implications for bridge design, maintenance practices, and public safety, ultimately contributing to the sustainability and reliability of transportation networks.

Automated damage assessment of prestressed concrete bridge beam based on sagging

The appropriate bridge maintenance strategy cannot be determined unless the damage is identified, localized, and quantified correctly. Damage assessment can be performed based on model updating, where material properties of a numerical model are modified to represent the damaged state as accurately as possible. However, this approach may become tedious for complex structures such as bridges due to the high number of unknown variables. This study replaces the time-consuming Finite Element (FE) simulations with Artificial Neural Network (ANN) as a surrogate model to reduce the required computational time. The implementation of ANN enables automating the existing manual damage assessment of a prestressed concrete bridge beam. In this paper, the objective is to minimize the difference between the simulated and measured sagging, which is the irreversible downward movement of the bridge due to its weight. The minimization is performed with the Simulated Annealing (SA) algorithm, and the optimization process is repeated with 100 different starting points to ensure robustness. The results indicate that the automated approach performs similarly to the manual approach while being faster and enabling wider exploration in the search space without compromising accuracy. The proposed approach serves as a practical tool for real-world problems by offering an efficient damage assessment.

Nonlinear behavior of existing pre-tensioned concrete beams: Experimental study and finite element modeling with the constitutive Serial-Parallel rule of mixtures

The performance of existing prestressed concrete (PC) beams and their time-dependent behavior have been concerns for bridge maintenance services. In this paper, laboratory tests of three PC void slab beams taken away from an obsolete bridge were conducted and an alternative more efficient finite element (FE) method was developed. In preparing the three beam specimens, two retained their original reinforced concrete (RC) overlay and one chiseled off its RC overlay. Through the four-point loading tests, the load response plots of the beams from elastic to plastic failure were carefully documented, including the strains along the mid-span section, the strains of longitudinal rebars and strands, and the mid-span deflection. The test results showed that no interface slip was observed between the RC overlay and the top of void slab during the whole loading process, and the yield load of the test beams with the overlay was approximately 45 % higher than that without the overlay. Regarding the proposed nonlinear numerical formulation, the modelling process avoided the treatment of complex reinforcement and prestressing tendon layouts. The prestressed concrete was simulated as a composite material whose behavior is depicted by a constitutive serial-parallel rule of mixtures (SP-RoM). The generalized Maxwell model and generalized Kelvin model were applied to calculate the time-dependent losses of prestress. All the developments have been implemented within the open-source FE code Kratos-Multiphysics environment and are fully available. Compared with the test outcomes, it shows that the numerical results are in good agreement with the solutions in terms of stiffness, load-deflection curves, and damage evolution. The differences between the experimental and numerical values of ultimate load for the specimens with and without RC overlay were all within 10 %. Furthermore, the proposed nonlinear models can also predict the time-dependent prestress losses of existing PC beams.

Bridge performance degradation model based on the multi-variate bayesian dynamic linear method

The degradation of bridge structural performance arises from the combined influence of various factors. Performance assessment and reliable prediction of bridge performance degradation through effective utilizing of detection information updates is a challenging problem. In this paper, the concept of performance indicators is redefined, employing to delineate bridge performance degradation. A bridge performance degradation model (the error ≤8%) is formulated, considering the multiple-variable Bayesian dynamic linear method (MBDLM) and revealing the coupling mechanisms among factors influencing bridge performance degradation. On this basis, the prediction performance of the model is quantitatively evaluated by three metrics: mean squared error, predictive mean squared error and mean absolute percentage error. A methodology is presented for the assessment, prediction, and maintenance reinforcement of in-service bridge structural performance degradation. This approach holds promise for future applications in safety assessments and the decision-making process for preventive maintenance of operational bridges.

Durability evolution of RC bridges under the coupled action of fatigue effect and chloride attack

The main factors affecting the durability of a reinforced concrete bridge are the fatigue effect brought on by continuous traffic loads and chloride ion erosion, but studies on how these two factors interact have been scarce. As a result, concrete structure durability analyses need to be more thorough and accurate. The fatigue model from continuum damage mechanics is used to determine the equivalent stress range of traffic loads, and poroelasticity is used to establish the link between volumetric strain and porosity. Following a change in the porosity's function, the chlorine ion diffusion coefficient is covered. Finally, a proposed coupling analysis method that takes many physics into account is presented. This method takes into account fatigue stress, body strain, porosity, chlorine ion diffusion coefficient, and corrosion rate. The multiphysics finite element program and the associated theoretical equations can be used to simulate the chloride ion diffusion, erosion states, corrosion rate, and bearing capacity of the main sections in various stages. As a result, the reinforced concrete bridge's evolutionary durability can be fully attained. Fatigue loading can accelerate corrosion of reinforcement and chloride ion diffusion, which accelerates the loss of a bridge's flexural strength. The method described in this paper can calculate the flexural load capacity, erosion state, time-varying rust rate, and chloride ion diffusion effect of the main bridge sections at various times, which can show the detailed evolution of reinforced concrete bridge durability and offer useful theoretical and technical support for decisions about bridge durability assessment and maintenance

Health monitoring and maintenance of highway and bridge

In recent years, due to the rapid growth of traffic volume, the use frequency and load of Bridges have been significantly increased, and the service state of the bridge structure has deteriorated sharply. At present, there is no corresponding standard specification for the health monitoring and maintenance of Bridges in China, so the safety, durability and normal performance of Bridges are still the focus of people's attention. This paper summarizes the research results of health monitoring and maintenance at home and abroad, summarizes and analyzes the highway bridge health monitoring and maintenance, and introduces the bridge health monitoring system in China.

An integrated soft computing-based criteria interdependencies and intuitionistic fuzzy information to evaluate the urban concrete bridge maintenance models

An integrated soft computing-based criteria interdependencies and intuitionistic fuzzy information to evaluate the urban concrete bridge maintenance models

Inspection data‐based prediction on fatigue crack of orthotropic steel deck using interpretable machine learning method

AbstractThe prediction of fatigue cracks on orthotropic steel decks is of great significance to the maintenance of bridges. However, fatigue cracks are affected by various uncertainties in reality, which encourages a data‐driven study for the sake of reliability and accuracy of predictions. Based on the crack inspection data from orthotropic steel decks on actual bridges in China, the feature engineering is conducted considering fatigue crack behaviors, and the machine learning models are trained and tested for predicting cracks, including XGBoost, random forest, and multiple decision trees. According to the receiver operating characteristic curves of the three models, the XGBoost model has the best performance, whereas the average AUC is about 0.75, limited by the insufficient data volume of positive samples. With the SHAP values of all features, the interpretation of the machine learning model is presented, indicating that the global effects, that is, the longitudinal position, the loading condition, and the bridge age, are always influential factors for fatigue cracks. The local features concerning the interactions between cracks have an effect on crack behaviors to a certain extent, but less important. Accordingly, the interpretable machine learning model can provide conservative predictions in a rather transparent way on this issue, which can benefit decision‐making in bridge designs, maintenance, and management.