Box Girder Bridge Research Articles

Improved Deflection Prediction Model for PSC Box Girder with Stay Cable System during Tensioning Phase

To improve the accuracy of deflection prediction for prestressed concrete (PSC) box-girder bridges with a stay cable system (SCS) during tensioning, this study employs the Latin hypercube sampling (LHS) technique to sample random variables affecting long-term deflection of the main girder. A long-term deflection randomness analysis model is established, and the shear stiffness degradation factor is included to quantify the contribution of diagonal web cracking to the main girder deflection. Uncertainty and sensitivity analysis are conducted for the Dongming Huanghe River Highway Bridge. An objective function is applied to select the optimal combination of random variables, and a modified model is established and verified for accuracy. Results show that diagonal web-cracking accounts for 8.8% of total deflection and cannot be ignored, and the prestressed tension control stress, creep uncertainty coefficient, and concrete density significantly impact long-term deflection. The modified model predicts deflection with greater accuracy than the mean value model.

Post-fire assessment of composite steel-concrete box-girder bridges: Lessons from a recent incident

The structural fire analysis of bridges is crucial for ensuring transportation infrastructure safety since bridges, due to their unique characteristics and exposure to environmental hazards, are particularly susceptible to fire-induced damage. Despite this vulnerability, there is a lack of both experimental research and design guidelines for ensuring fire safety in bridges. This underscores the importance of studying actual bridge fire incidents.This article presents a comprehensive examination of the numerical and experimental investigations carried out to evaluate the structural condition of a composite box-girder bridge located in Valencia, Spain, following a significant fire incident. In addition, the paper details the repair works carried out to fully restore the operational capacity of the bridge, along with the key lessons learnt from the incident. Therefore, the article highlights the vital synergy between advanced numerical models and experimental investigations to strengthen rehabilitation action plans and gain valuable insights for making informed decisions regarding post-fire structural integrity. By doing so, the study enhances understanding of bridge safety under fire and provides actionable recommendations for researchers, practitioners, and transportation authorities.

Simulation Based Study Of Ground Mobile Robots For Inspection And Control Of The Bridge Assembly Process

Nowadays, the inspection of bridges poses a significant challenge for safeguarding critical infrastructures. Recent advancements have seen the integration of robots to replace human personnel in hazardous tasks. These robots, whether operating autonomously or through tele-operation, play a crucial role in monitoring structures and infrastructure, ensuring secure access to areas such as manholes on decks and box girder bridges. Specifically designed for environments deemed dangerous, difficult, or inaccessible to humans, ground mobile robots equipped with appropriate sensors are increasingly deployed for inspection purposes. This paper addresses simulation tests conducted by a hybrid mobile robot. Its compact design and maneuverability enable it to navigate through obstacles, making it suitable for inspecting railway or highway bridge decks as well as confined spaces within box girder bridges. The study includes a survey of existing bridges highlighting key issues to be addressed and presents simulation results for the hybrid rover, which has been developed and equipped with sensors tailored to fulfill inspection tasks within a selected case study.

Damage Identification in Large‐Scale Bridge Girders Using Output‐Only Modal Flexibility–Based Deflections and Span‐Similar Virtual Beam Models

Damage identification (DI) methods using changes in static and modal flexibility (MF)–based deflections are effective tools to assess the damage in beam‐like structures due to the explicit relationships between deflection change and stiffness reduction caused by damage. However, current methods developed for statically determinate beams require the calculation of mathematical scalar functions which do not exist in statically indeterminate beams and limit their application mainly to single‐span bridges and cantilever structures. This paper presents an enhanced deflection‐based damage identification (DBDI) method that can be applied to both statically determinate and indeterminate beams, including multispan girder bridges. The proposed method utilises the deflections obtained either from static tests or proportional defections extracted from output‐only vibration tests. Specifically, general mathematical relationships between deflection change and relative deflection change with respect to the damage characteristics are established. From these, additional damage‐locating criteria are proposed to help distinguish undamaged spans from the damaged ones and to identify the damage location within the damaged span. Notably, a span‐similar virtual beam (SSVB) model concept is introduced to quantify the damage and make this task straightforward without the need to calculate complicated mathematical formulae. This model only requires information of the beam span length, which can be conveniently and accurately obtained from a real structure. The robustness of the method is tested through a series of case studies from a numerical two‐span beam to a benchmark real slab‐on‐girder bridge as well as a complex large‐scale box girder bridge (BGB). The results of these studies, including the minimal verification errors within five percent observed in the real bridge scenario, demonstrate that the proposed method is robust and can serve as a practical tool for structural health monitoring (SHM) of important highway bridges.

A BIM-based approach for risk assessment and management in roadway bridges: preliminary results from the application to a post- tensioned concrete box girder bridge

The Guidelines for Risk Classification and Management, Safety Assessment, and Monitoring of Existing Bridges, released in 2020 by the Italian Ministry of Infrastructures and Transport, promote the use of Building Information Modeling (BIM) environment as one of the main tools to achieve informed risk mitigation of infrastructures. To date, BIM environments are often only used as repositories of information from different entities involved in bridge design, management, and retrofitting. However, to achieve informed risk mitigation of bridges, the current BIM paradigms should be expanded by integrating new typologies of data, such as those from Structural Health Monitoring (SHM) systems, and functionalities, such as the ability to process stored data directly within the BIM environments. In this light, this paper presents a BIM-based approach conceived to achieve comprehensive assessment and management of the risk conditions and structural performance of bridges. To this end, specific algorithms have been implemented into the selected BIM environment to perform tasks such as assessing the preliminary risk level of a bridge according to the methodology proposed by the Italian Guidelines, evaluating the outcomes from visual inspections to estimate its defect level, storing and processing data from SHM systems installed on the structure, and more. The paper also presents the first application of the proposed BIM-based approach to a post-tensioned box girder bridge belonging to the Italian road network.

Self-Sensing Strands and Their Application in Prestressed Concrete Box Girders

Strands are widely used in prestressed concrete structures such as buildings, bridges, and dams. Traditional strands can only meet the structural stress requirements, but the long-term and effective monitoring of their stress state, leading to soaring maintenance costs, imposes a significant economic burden on operating units. In response, this paper studies the application of self-sensing strands in prestressed concrete bridges. Firstly, a new type of self-sensing strand properties is proposed, including its design and encapsulation process. Secondly, the designed self-sensing strand is applied to a prestressed concrete box girder bridge on a certain highway for verification analysis. Lastly, the prestress loss during the construction and maintenance stages of this box girder bridge is monitored. The results show that the prestress loss is minimal within the first 24 hours of box girder prefabrication and during the grouting stage of anchorage, with an average prestress loss of 0.43 KN, consistent with structural characteristics. The tension of the four strands inside the concrete box girder during the maintenance period ranged from 186 to 194 KN, all exceeding 95% of the locking force, meeting the design requirements. This proves that prestressed self-sensing strands can effectively monitor prestress loss while ensuring structural stability and safety, significantly reducing maintenance costs. It also provides reliable support for the intelligent operation and long-term health monitoring of bridge structures.

Engineering Mechanics Methods in Stability Studies of Bridge Structures and Innovations in Future Bridge Designs

Abstract With the development of science and technology and transportation, high pier and large-span bridges are rapidly rising. Due to the increase in span diameter and pier height, nonlinear and stability problems of bridges become more and more important. In this paper, the stability of large-span steel box-girder suspension bridges is investigated using engineering mechanics methods. Based on the finite element analysis method to solve the bridge structure of the first type of stability problems and the second type of stability problems, the use of the response spectrum method for bridge seismic response. Taking “Xiling Yangtze River Bridge” as the engineering background, the seismic response is analyzed by establishing a finite element model. The axial force of the bridge tower generated by the downstream earthquake is larger than that generated by the transverse earthquake. In the transverse direction, the bending moment MZ is larger than the bending moment MY in the transverse direction, and the bending moment of the pile foundation is larger than the bending moment of the pile foundation in the longitudinal direction. The Xiling Yangtze River Bridge plays a dominant role in transverse seismicity, and its downstream seismic excitation plays a dominant role in longitudinal seismicity. However, the energy-demand ratio corresponding to the transverse moment MY is only 1.83, and the strength of the pile section needs to be further improved. For the future innovation of bridge design, a high-performance bridge structure based on UHPC is an important direction for future development.

Investigating the Performance of a Degraded Prestressed Concrete Box Girder Half-joint Bridge in the Spirit of the Italian Guidelines

The paper investigates a paired pre-stressed box-girder concrete bridge, according to the framework suggested by the new Italian Guidelines for the risk assessment of existing bridges. The bridges, selected as case study within the research agreement signed by the FABRE Consortium and ANAS S.p.A. for first applications of the Italian Guidelines, present significant age-related degradation phenomena known to the Administrator, who decided for the bridges demolition and reconstruction. Visual inspections confirmed defects in the pre-stressing system, a permanent deflection of the deck, and cracks at half-joints, possibly due to pre-stressing loss and creep effects triggered by the poor quality of concrete. Also, preliminary safety verifications revealed not to meet code requirements in most cross-sections. Consequently, the most degraded bridge was closed. From March 2022, experimental campaigns have been performed by the FABRE Consortium and ANAS for improving their experience on the behaviour of old pre-stressed concrete bridges, as well as to control possible performance loss of the open bridge, sustaining the overall route traffic. The paper summarises these activities and presents some possible future investigations to be carried out before bridge demolition.

Deep learning-based prediction model of temperature-induced deflection of a multi-span continuous box girder bridge: Case Study

The deflection of a bridge is a crucial factor in assessing its structural integrity and safety, serving as an indicator of the overall rigidity of the bridge. The deflections stemming from temperature variations may surpass those attributed to live loads. However, the monitoring data acquired from the sensors indicate a time-lag effect exists between temperature variations and resulting deflection. The time-lag effect poses challenges in precisely characterizing and modeling the temperature-induced deflection behavior. Therefore, this paper presents a deep learning-based prediction model to predict the temperature-induced deflection of multi-span continuous box girder bridges. The Long-Short Term Memory (LSTM) model was adapted in this paper leveraging deep learning techniques which capable to learn complex patterns and non-linear relations between temperature and temperature-induced deflection data to predict the deflection of both span-1 and span-6 of bridge under ambient temperature and girder temperature variations respectively. To enhance the precision of the LSTM model, this paper proposed the Empirical Mode Decomposition (EMD) method to extract the temperature-induced deflection from the raw deflection data which induced by other live loads. Lastly, residual analysis was conducted to analyze the prediction outputs from the LSTM model with the actual measurements obtained from sensors.

UAV photogrammetry and laser scanning of bridges: a new methodology and its application to a case study

The state of preservation of infrastructures, such as bridges and viaducts, plays a crucial role in the economic development of a country. To this aim, a multi-level knowledge-based approach providing guidance on several aspects included in the management of large bridge inventories is utterly needed. In particular, the knowledge of bridge geometry, construction details, and structural defectiveness is of pivotal importance. Accordingly, methodologies to achieve the systematic collection of this information should be investigated and tested in practical applications. This paper presents a new methodology for surveying reinforced concrete box girder bridges using UAV photogrammetry and laser scanning. The proposed methodology is based on the adoption of predefined trajectories to accelerate surveying procedures and achieve high-quality results. The use of UAV photogrammetry allows for capturing high-resolution images of the entire structure, structural flaws included, while laser scanning provides measurements of geometric details. By integrating the data acquired, an accurate 3D digital twin of the bridge can be obtained, and its structural defects can be assessed. A comparison between the employed technologies is also proposed. Although UAV photogrammetry is slightly less precise than laser scanning in detecting geometries and construction details, it offers a more cost-effective and faster alternative to traditional laser scanning, primarily due to its accessibility in the field, without compromising the quality and reliability of the collected data. The proposed methodology has been applied on a case study reinforced concrete box girder bridge located in central Italy. The obtained results highlight the effectiveness of the proposed approach for the systematic collection of essential data for the knowledge of the assets and suggest that UAV photogrammetry can almost replace traditional laser scanning of bridges within the structural risk assessment process.

Analysis the torsional vibration of PC Box Girder Bridge with Corrugated Steel Webs

In this study, in order to accurately calculate the torsional vibration frequency of a simply supported corrugated steel web composite box girder, the element stiffness matrix of the torsional vibration of the simply supported corrugated steel web composite box girder was derived using the principle of constant dynamic potential energy, taking into account the shear deformation of the corrugated steel web. Analyzed the influence of waveform steel web plate type and shear deformation on torsional vibration frequency. The results show that the torsional vibration frequencies of the four commonly used types of simply supported corrugated steel web composite box girders in engineering are relatively close, and the influence of corrugated steel web types on torsional vibration frequencies can be ignored in practical calculations; The influence of shear deformation on the torsional vibration frequency of simply supported corrugated steel web composite box girder is significant, and exceeds the influence on its bending vibration frequency. Therefore, the influence of shear deformation must be considered in practical engineering calculations

Dynamic characterization of a curved nine-spans pre-stressed concrete box girder bridge with half-joints

In recent years, the failure of many bridges has pressed governments all over the world to increase investments and to enact new monitoring regulations. In the Italian context, the Ministry of Infrastructure and Transport answered to that challenge by enacting the new Guidelines on Risk Classification and Management, Safety Assessment and Monitoring of Existing Bridges, in 2022. In this new regulation, Structural Health Monitoring (SHM) plays a fundamental role, complementing traditional periodic inspections by carrying out low intrusive non-destructive analyses. In this field, Operational Modal Analysis (OMA) is a vibration-based method consisting in the processing of the ambient accelerations recorded on the structure in order to extract and track its modal features. The final goal of continuous OMA is the timely identification of possible damage-induced persistent variations in the modal features of the monitored structure. This is why one of the most recent advances in OMA algorithms is related to the development of continuous Automated OMA embedded in high-potential software, to enable the infrastructure management authorities to realize large-scale monitoring of bridge networks. Many road bridges are however long multi-span bridges which require numerous sensors for their monitoring, thus making automated OMA especially challenging from the computational point of view. The aim of the work is to contribute to a more computationally affordable automated OMA for long bridges, by proposing to subdivide the OMA task considering suitable selections of subgroups of sensors. The proposed approach is illustrated in a case study consisting of a curved nine-spans pre-stressed concrete box girder bridge with 10 half-joints and equipped with more than 50 sensors.

Aerodynamic and aeroelastic response of wind barrier over trapezoidal box girder bridge under turbulence wind

Aerodynamic and aeroelastic response of wind barrier over trapezoidal box girder bridge under turbulence wind

SHM-based digital twin calibration of a post-tensioned reinforced concrete bridge with vertically prestressed internal joints

Post-tensioned concrete box-girder bridges exhibit complex time-varying behavior due to factors like creep, shrinkage, and steel relaxation. Predicting these phenomena accurately at the design phase is a difficult task, often leading to underestimation of their impact. Particularly in bridges constructed using a balanced cantilever scheme and cast-in-place concrete, the aging process and the timing of load application can influence the time-dependent behavior of the structure. The combination of these effects can result in significant vertical displacements and serviceability issues that necessitate careful consideration. The Italian Bridge Guidelines introduced specific evaluations for post-tensioned concrete bridges, which often require the support of FE models for accurate safety evaluation. The paper reports the investigations carried out on a very challenging post-tensioned concrete box-girder bridge with vertically prestressed internal joints. The main objective is to calibrate a predictive FE model of the bridge by integrating information from design reports and drawings, static and dynamic non-destructive experimental tests as well as onsite inspections and digital surveys to characterize the presence of defects. The data obtained from the test campaign are utilized to build an accurate model, which is further calibrated to become an actual digital twin of the real structure employing ambient vibration tests (AVT) to identify the dynamic behavior of the structure. The digital twin thus obtained will serve as a tool for performing reliability analyses and predicting future serviceability or collapse issues.

Dynamic characteristic identification of a bridge using BPF-WT combined filtering method

ABSTRACT The application of indirect identification of dynamic characteristics of bridge structures is largely hindered due to the complexity of bridge dynamic characteristics identification environment factors and signal processing. We propose a new combined filtering method by Bandpass filter with Wavelet Transform, which combines wavelet transform and bandpass filter to break through the problem of low accuracy of indirect recognition method due to the influence of vehicle frequency and other environmental noise. This new method not only gives full play to the advantages of bandpass filters but can easily reduce the peak caused by the known vehicle frequency. It realises the layer-by-layer decomposition and reconstruction of signals through wavelet transform advantage, to achieve the effect of automatic grouping filtering. The influencing factors of the new method are analysed by a customised trolley as an example to identify the dynamic characteristics of the structure. This paper also combines this method with virtual vehicles on ABAQUS and SIMPACK software to identify the dynamic characteristics of a simply supported box girder bridge. The effectiveness and reliability of this method in identifying bridge dynamic characteristics are further verified.

Reliability Assessment Approach for Fire Resistance Performance of Prestressed Steel–Concrete Box Girder Bridges

This paper employs probability methods to evaluate the fire safety performance of prestressed steel–concrete beam bridges based on simulation experimental research. Firstly, fire simulation experimental sample analysis was conducted on actual small box girder bridges to assess the structural response of prestressed steel–concrete structures to fire, as is in line with engineering practice. Next, we constructed a reliability analysis model to investigate the fire resistance performance of prestressed steel–concrete beam bridges. Combining reliability theory with the finite element method, we established a reliability analysis method for the fire resistance performance of prestressed steel–concrete beam bridges. Subsequently, we proposed a safety factor evaluation model for the fire resistance performance of prestressed steel–concrete beam bridges and then established a safety factor evaluation method for the fire resistance performance of prestressed steel–concrete beam bridges based on reliability back analysis. Finally, based on the analysis of the post-fire structural response in the specific case of a steel–concrete continuous beam bridge project moving from conditions of being simply supported to continuously prestressed, a structural resistance sample of the prestressed steel–concrete beam bridge was generated via the uniform design method, and statistical analysis was conducted. Subsequently, probability methods were used to evaluate the safety of the prestressed steel–concrete beam bridge after a fire. Through analysis, we concluded that the duration of the fire had a significant impact on the structural performance of prestressed steel–concrete beam bridges and that the randomness of parameters had a significant impact on the safety reserve of prestressed steel–concrete beam bridges following the fire. Going forward, it is necessary to pay attention to this factor in specific engineering practices and strengthen the monitoring and statistical analysis of structural random characteristics.

Seismic Performance of Steel-SMA Reinforced Columns: Numerical Investigation

The residual displacement of a bridge column governs its functionality after a severe earthquake. A box girder bridge was selected as a case study. Pushover analysis, quasi-static cyclic analysis, incremental dynamic analysis and fragility analysis were conducted to compare the seismic performance of the reinforced concrete column, the unbonded prestressed reinforced concrete column (UBPRC column) and the unbonded prestressed reinforced concrete column using superelastic shape memory alloy (UBPRC-SMA column). The threshold loading plateau axial load ratio was recommended in designing a UBPRC-SMA column, thereby ensuring the self-centering performance of a bridge column with fewer superelastic SMA bars. The self-centering performance was considered in the fragility analysis, and the results show that the UBPRC-SMA column suffers the least damage for the collapse damage state.

PROCEEDINGS IN UAS-ASSISTED BRIDGE INSPECTIONS: RTK-BASED PHOTOGRAMMETRIC RECONSTRUCTION AND SPATIAL FILTERING

Abstract. Traditional bridge inspections present considerable challenges in terms of efficiency and accuracy. However, recent advancements in Unmanned Aerial Systems (UASs) and deep learning for object detection have opened up new avenues for automatic bridge damage detection. We present a comprehensive framework leveraging these technologies for automated damage detection in UAS imagery, followed by accurate mapping of the damage predictions on photogrammetric models. In this work, we propose a photogrammetric procedure to retrieve geolocated bridge models solely based on Real-Time Kinematics (RTK) information. Within the damage detection step, we conduct extensive testing and optimization of model hyperparameters using YOLOv8 and Slicing Aided Hyper Interference (SAHI). Next, we map the predictions onto the 3D model using ray casting, allowing to group and filter the predictions by their area and position. Finally, a Graphical User Interface (GUI) allows bridge inspectors to identify false positive predictions, generate new training data, and directly measure damage dimensions in the images. Validation on a concrete box girder bridge resulted in a photogrammetric model with a mean error of 1.3 cm, negating the need for ground control points. Our model training process revealed substantial performance variations between training and test datasets, underscoring the importance of evaluating optimal hyperparameters on UAS inspection images rather than relying on the validation metrics. Lastly, we successfully map the detected damage and create new training data from the UAS inspection images. This framework significantly enhances bridge inspection accuracy and efficiency, providing a strong foundation for future developments in automated bridge inspections.

Effective width of steel-concrete composite box girder bridges: a review and method comparison

Steel-concrete composite girders have non-uniform stress distribution on the slab, presenting maximum stresses next to the webs of the girder. This phenomenon is known as shear lag effect. To understand this effect, there is the effective width concept, in which only a portion of the slab width is considered effective in contributing to the composite element’s resistant capacity. However, in the technical standards, there is no recommendation for calculating the effective width in steel-concrete composite box girder bridges. In view of this situation, the purpose of this paper is to carry out a systematic review on effective width and/or the shear lag effect in steel-concrete composite bridges, in order to raise the main existing recommendations and compare them. Through a bibliometric scan with carefully chosen keywords, it was found that of all research on shear lag or effective width in steel-concrete composite structures, only 31.19 are on bridges and 14.97% are on bridges with box girders. Among the papers, those that have a method for calculating the effective width of steel-concrete composite girder bridges have been compared quantitatively and qualitatively with the procedures of AASHTO and EN 1994-2-2. In these procedures were also identified that the, for the boundary conditions of the present paper, the parameters that most influencing the effective width are, in that order, the span length, the distance between girders, the concrete slab height, the longitudinal position and the type of load.

Torsional Strength of Horizontally Curved Continuous Reinforced Concrete Box Girder Bridges

Torsional Strength of Horizontally Curved Continuous Reinforced Concrete Box Girder Bridges