Slab Bridge Research Articles

Performance of hinge joints in hollow-core slab bridges reinforced with iron-based shape memory alloy U-bars

The mechanical behavior of hinge joints has an important influence on the hollow-core slab bridges. However, hinge joints are prone to cracking. This study proposed a new hinge joint reinforced by locally prestressed iron-based shape memory alloy (Fe-SMA) U-bars for the new hollow-core slab bridge. To verify the effectiveness of this hinge joint, six test specimens were prepared, encompassing two spans (10 m and 20 m), and three working conditions (nonactivation, activation before cracking, and repair and activation after cracking). The load transfer mechanism under flexural-shear load was investigated, and the validity was verified using a proposed simplified analytical model. The results indicated that the failure mode of the new hinge joint under flexural-shear load can be divided into three stages. The new hinge joint can effectively apply local prestressing by heating activation of the Fe-SMA U-bars, thus increasing the crack penetration load. In addition, the damaged new hinge joints can be repaired and further reinforced by pressure injection of adhesive and heating activation of the Fe-SMA U-bars. Load transfer is affected by the development of cracks, and the ultimate load of the new hinge joint is controlled by the splitting tensile strength of the concrete in the hinge joint.

Quantitative Evaluation of Reinforced Concrete Slab Bridges Using a Novel Health Index and LSTM-Based Deterioration Models

The Health Index (HI) serves as an essential tool for assessing the structural and functional condition of bridges, calculated based on the condition of structural components and the serviceability of the bridge. Its primary purpose is to identify the most deteriorated structures in an asset inventory and prioritize those in most urgent need of repair. However, a frequently cited issue is the lack of accurate and objective data, with the determination of the HI often being heavily reliant on expert opinions and engineering judgment. Furthermore, the HI systems used in most countries are dependent on the current state of bridge components, making it challenging to use as a proactive indicator for factors such as the rate of bridge aging. To address this issue, this study introduces a novel HI as a quantitative evaluation metric for reinforced concrete slab bridges and details the process of deriving the HI based on deterioration models. The deterioration models are derived by preprocessing the deterioration data of reinforced concrete (RC) slab bridges, wherein the relationship between time and deterioration is directly employed for training a long short-term memory model. The HI was validated through a case study involving six RC slab bridges, wherein accuracies of >93% were achieved, confirming that the proposed quantitative evaluation methodology can significantly contribute to maintenance decisions for bridges.

In Situ Testing and Finite Element Analysis of a Discontinuous Mortise and Tenon Stone Bridge Under Natural Excitation

To study the dynamic response of multi-span mortise and tenon stone bridges under natural excitation, a bluestone multi-span stone bridge with a main span of 2.56 m in southern China was taken as the research object. Based on the collected pulsating signals of bridge piers and slabs, the natural frequencies and damping ratios of the main span bridge slab and pier were analyzed using the half-power broadband method (HPBM) and random decrement technique (RDT). Modal analysis was conducted using ANSYS, and the results were compared with those obtained from on-site experiments for further performance analysis. The research results of this article indicate that the natural frequency range of the 2.56-m bridge slab identified by measured signals is 48–49 Hz, and the damping ratio range is 33.33–36.61%. The natural frequency of the central pier is 75–76 Hz, and the damping ratio range is 26.39–27.83%. Through finite element modal analysis, the natural frequency of the bridge slab is 54.401 Hz, with an error of 10.5%. The natural frequency of the overall stone bridge is about 82.2 Hz, with an error of about 8.2%. The validated finite element model was subjected to normal water flow impact and erosion simulation. The results indicate that under erosion with fewer particles and lower flow rates, the upstream pier bottom at the center receives the highest relative erosion mass and displacement per unit area. The bridge deck near the main span also experienced relative displacement. Therefore, in the subsequent protection work, special attention should be paid to these components.

A Method for Analyzing Transverse Stress in Link Slabs of Simply Supported Steel–Concrete Composite Bridges

The cracking of link slabs in jointless bridges presents significant challenges due to the complexity of their stress conditions. This study focused on analyzing the transverse stresses in link slabs of jointless steel–concrete composite bridges. Utilizing linear elasticity theory and partial differential equations of plates, the deflection and stress distribution functions for the link slabs were determined. The validity of these analytical solutions was confirmed through comparisons with finite element models and load tests. Results from both the load tests and the finite element model indicate that the upper face of the girder end link slabs experiences maximum tensile stresses in both transverse and longitudinal directions. The stress values obtained from the analytical method align well with these results, showing that the total stress, when considering transverse stresses, reaches 107% of the longitudinal stresses alone. Furthermore, a 40% reduction in longitudinal girder spacing or a 50% increase in girder end length can lead to link slab stresses of 128% and 145% of the longitudinal stresses, respectively. This finding suggests that even loads lower than those designed based solely on longitudinal stresses can result in cracking. Therefore, it is recommended that transverse stresses be considered in the design of link slabs for jointless bridges. Relying solely on conventional longitudinal stress analyses may underestimate actual stress conditions and contribute to the formation of cracks.

Influence of Transient Static and Transient Dynamic Analysis on Deflection of Bridge Slab Using Finite Element Method in ANSYS

The deflection behavior of bridge slabs is critical for ensuring structural safety and longevity. By using the Finite Element Method (FEM) in ANSYS, engineers can simulate and analyze the effects of both transient static and transient dynamic loads on bridge slabs. This paper explores how these two types of analyses affect the deflection behavior of a bridge slab. We present the mathematical formulations, practical applications, and a case study involving a bridge slab subjected to time-varying loads. The comparative results demonstrate the significant impact that the choice of analysis method has on predicting deflection and ultimately guiding structural design decisions.

A spectrum correlation matrix-based rapid damage identification method for joints in hinged slab bridges by sparse measurement

Hinged slab bridges are widely used in the medium and small-span bridges on highways and the joints are highly susceptible to damage under the action of the increasing traffic. However, current methods for damage identification of hinged joints, whether rely on static or dynamic testing, typically require substantial manpower, resources and time, which presents challenges for the rapid evaluation of numerous bridges. In view of this, a novel damage index named spectrum correlation matrix (SCM) is proposed and its feature extraction technology is established as well as the potential for sparse measurement is theoretically explained. Furthermore, a rapid, robust, and convenient damage identification methodology using SCM and Levenberg-Marquardt algorithm is proposed. An optimal strategy for the layout of sparse measuring points has been explored, the sensitivity and the effectiveness of the proposed method is validated through both numerical simulations and the in-situ test of a bridge in service. The results indicate that the SCM contains abundant vibration information and shows a high sensitivity to damage. The strategy for the layout of measuring points is highly efficient and the proposed methodology greatly reduces the number of measuring points compared to previous vibration-based methods, which eases rapid identification of damage for joints in hinged slab bridges.

Artificial Neural Network and Kriging Surrogate Model for Embodied Energy Optimization of Prestressed Slab Bridges

The main objective of this study is to assess and contrast the efficacy of distinct spatial prediction methods in a simulation aimed at optimizing the embodied energy during the construction of prestressed slab bridge decks. A literature review and cross-sectional analysis have identified crucial design parameters that directly affect the design and construction of bridge decks. This analysis determines the critical design variables to improve the deck’s energy efficiency, providing practical guidance for engineers and professionals in the field. The methods analyzed in this study are ordinary Kriging and a multilayer perceptron neural network. The methodology involves analyzing the predictive performance of both models through error analysis and assessing their ability to identify local optima on the response surface. The results show that both models generally overestimate the observed values. The Kriging model with second-order polynomials yields a 4% relative error at the local optimum, while the neural network achieves lower root mean square errors (RMSEs). Neither the Kriging model nor the neural network provides precise predictions but point to promising solution regions. Optimizing the response surface to find a local minimum is crucial. High slenderness ratios (around 1/28) and 40 MPa concrete grade are recommended to improve energy efficiency.

Improved GAN-based deep learning approach for strain field prediction and failure analysis of precast bridge slab joints

Nonlinear finite element analysis (FEA) is crucial for understanding complex stress-strain behaviors and assessing potential structural failure risks. Building on the recent success of deep learning (DL) methods in physical field predictions, there has been growing interest in forecasting internal force fields of structures beyond the existing data scope. In this study, a data-driven strain field analysis model based on an improved Generative Adversarial Network (GAN) is proposed. To enrich the input data, this novel approach incorporates the Signed Distance Field (SDF) derived from the characteristics of the original Finite Element (FE) models. The generator, based on U-Net, is enhanced with channel attention mechanisms and loss penalty terms, forming the core of the improved GAN. The effectiveness of the proposed method is demonstrated using two parallel datasets comprising 3-Headed bar tension models across two planes. Subsequently, the generated strain field is subjected to feature extraction using the 2D-Principal Component Analysis (2D-PCA) method, followed by structural failure determination through the K-Nearest Neighbor (KNN) algorithm. The results indicate that the proposed improved approach achieves a significant reduction in Root Mean Square Error (RMSE) of 20.71 % and 13.21 % across the two datasets, with the structural failure determination method reaching an F1-score of 0.971. Thus, the intelligent strain field analysis method introduced here effectively predicts strain distributions and promptly identifies failure states, offering valuable insights for further numerical analysis and structural design.

Bayesian Inference and Condition Assessment Based on the Deflection of Aging Reinforced Concrete Hollow Slab Bridges

This paper presents a Bayesian inference framework for updating the structural rigidity ratio of aging hollow slab RC bridges using deflection measurements. The framework models the structural rigidity ratio as a stochastic field along the hollow RC slabs, using the Karhunen–Loeve (KL) transform to capture spatial correlation and variation. Bayesian inference is then applied using deflection data from static loading tests, supported by a finite element model (FEM) and a Kriging surrogate model to enhance computational efficiency. The posterior distribution of the structural rigidity ratio is derived using a Markov chain Monte Carlo (MCMC) sampler. The proposed method was tested on an RC bridge with hollow slabs, using deflection measurements taken before and after reinforcement. The Bayesian updates indicated increased structural rigidity ratios after reinforcement, validating the effectiveness of the reinforcement. The deflection predictions from the updated models closely matched the measurements, with the 95% confidence bounds encompassing most of the data. This demonstrates the method’s validity and robustness in capturing the structural improvements post-reinforcement.

An Investigation into the Impact of Time-Varying Non-Conservative Loads on the Seismic Stability of Concrete-Filled Steel-Tube Arch Bridges

When the arch rib of the mid-bearing through and lower-bearing through arch bridges undergoes out-of-plane deformation, it is usually subject to the resilience force provided by the flexible hanger, which is known as the “non-conservative force effect” of the suspender. In contrast to the static condition, in the dynamic scenario, the time-varying non-conservative force exerted by the flexible suspender becomes more complex due to dynamic changes in external load. Moreover, the difference in fundamental frequency and vibration period between the bridge system and arch rib may influence the stress distribution within the arch rib during ground motion. This paper investigates the impact of time-varying non-conservative forces on the dynamic stability of arch ribs in concrete-filled steel tube (CFST) bridges under seismic loads. Specifically, it examines the influence of different seismic waveforms, frequency disparities between bridge slabs and arch ribs, and suspender stiffness on the non-conservative effect. The results reveal significant disparities in the impact of non-conservative forces exerted by the suspender during seismic events with identical intensity but varying frequency characteristics. The influence of non-conservative forces on the dynamic stability of bridges escalates as deck stiffness increases, while it remains relatively unaffected by changes in suspender stiffness.

Development of a Damage Assessment Method for the Efficient Maintenance of Aging Small- to Medium-Sized Reinforced Concrete Slab Bridge Decks

Development of a Damage Assessment Method for the Efficient Maintenance of Aging Small- to Medium-Sized Reinforced Concrete Slab Bridge Decks

Analytical Study of R C C Deck Slab Bridge with Variable Parameters

Bridges ware always proved to be the key elements for the infrastructural development of country .While designing the bridges ,three major aspects were always to be considered. These three factors were strength , stability and cost effectiveness .It was observed that cost economy was based on width to span ratio of bridge. Another important aspect of economics of bridge was the thickness of deck slab. The length/span of bridge was kept constant and magnitude of width was selected as variable parameter. Four different width to span ratio were taken as 0.75,1, 1.5 and 2.0 respectively. Keeping the same width to span ratios , design calculations were carried out for 0.6 m and 0.7 m deck slab thickness Design was carried out for Mix M-30 and steel as Fe -415. Total eight cases were studied to observe an economy of deck slab bridge Four cases were considered for different parameters of design of deck slab . For all the four width to span ratios ,mentioned above for 0.6 m deck slab thickness and four cases for 0.7 m deck slab thickness were attempted. It was concluded that for width to span ratio=1.0 , was suitable for minimum cost . The results thus obtained were shown in tabular form .The results thus shown were useful for optimizing the design of deck slab bridges . This analysis is extremely useful to civil engineers, practicing engineers, contractors, research scholars and budding engineers.

Cyclic inelastic performance evaluation of locking bolt demountable shear connectors in steel-concrete composite structures

This study extends the research on the Locking Bolt Demountable Shear Connector (LBDSC), previously introduced and extensively analysed under monotonic loading through both experimental and numerical methods. The focus here shifts towards the inelastic cyclic performance of the LBDSC, a critical aspect for applications in seismic regions. The LBDSC, designed for use in composite floors or decks, such as in-situ solid slabs, profiled deck slabs, or precast slabs in buildings and bridges, features a grout-filled steel tube bolted to the top flange of steel sections. The design incorporates a unique 'locking bolt' technique to counteract the influence of construction tolerances on undesirable initial slip behaviour, significantly facilitating the deconstruction and reuse of steel sections without the need for recycling. Following the Eurocode 4 guidelines, a series of standard push out tests were conducted to explore the LBDSC's inelastic cyclic characteristics. The experimental results confirm the LBDSC's capability for high strength, high initial stiffness, and adequate slip capacity under cyclic loading, with ductile shear failure modes observed at the bolt shank and local concrete crushing above the steel flange. The cyclic loading tests reveal a larger zone of damaged concrete compared to monotonic loading conditions, yet the monotonic and cyclic force-slip curves closely align. Based on these findings, and supported by validated finite element analyses, this paper proposes theoretical monotonic and cyclic models for LBDSC under push out loading, aimed at accurately predicting the load-slip response. These models are intended to facilitate the efficient analyses, design and numerical modelling of composite structures incorporating LBDSCs, and to support the broader adoption of LBDSCs in earthquake-prone areas, promoting sustainable steel-concrete composite construction practices.

Strength capacity of RC beams without shear reinforcement: Numerical analysis and comparisons with code provisions

The investigation of the behavior of reinforced concrete (RC) elements without shear reinforcement is a current focal point, driven by the incomplete consolidation of predictive formulas for shear strength in RC elements. Currently, the literature provides, indeed, a limited number of experimental and numerical studies on this subject. This paper seeks to advance the comprehension of the behavior and collapse mechanisms of RC beams not provided of shear reinforcement, as commonly employed in RC slabs of bridges. The paper commences with a critical review of several predictive formulas for the shear strength of RC elements lacking transverse reinforcement, as stipulated by various international codes. The objective is to identify the principal parameters involved in the formulations and discuss their roles also by means of sensitivity analysis. Following this, the results of nonlinear numerical analyses, based on a three-dimensional finite element (FE) model, are presented. The FE model was initially calibrated using experimental results from a benchmark beam lacking shear reinforcement, retrieved from the literature, which exhibited a brittle shear failure. Subsequently, several specimens were prepared for the numerical investigation, assuming multiple combinations of geometrical and mechanical parameters. For specimens experiencing shear failure, the strength was compared with that provided by code formulas, as well as using the strut-and-tie approach for the cases characterized by a reduced shear span-to-depth ratio. In general, these analytical tools significantly underestimated the numerical strength, underscoring the necessity for further insights based on experimental tests. The numerical outcomes have been, indeed, prodromal to design an experimental campaign.

Static and dynamic load test on concrete hollow-core slab bridge

In this paper, dynamic and static load test were carried out on a multi-span reinforced concrete simply supported hollow core slab bridge in Shenyang, Liaoning Province. Through the static load test, the quality and reliability of the project are evaluated, and the results show that under the action of 0.88 times of highway-classⅠload, the deflection and strain check coefficients of the control section of the tested condition are less than 1, which meets the specification requirements, and the measured relative residual deformation and relative residual strain are less than 20%, and the bridge structure is basically in the elastic working state. And combined with the finite element analysis model, the comparison between measured data and calculated data is carried out. Through the dynamic load test, the self-oscillation frequency and damping ratio of the superstructure were tested, and the results showed that the measured damping ratio was 0.690%, the first-order measured vibration pattern conformed to the variation rule of the vibration pattern of the simply supported girder bridge, and the measured self-oscillation frequency was 13.594 Hz, and the measured self-oscillation frequency (fundamental frequency) was greater than the calculated frequency, and the structural actual stiffness was greater than the theoretical stiffness, and the working condition was good. This study is of great significance for the assessment of bearing capacity and quality control of concrete hollow core slab bridge, and provides a useful reference for bridge design and operation.

Finite element data-driven deep learning-based tensile failure analysis of precast bridge slab joint

The joint is a critical component that facilitates force transmission across precast bridge slabs while maintaining structural integrity. Finite Element Analysis (FEA) is commonly used to examine the mechanical properties and load-bearing capacity of joints with different configurations. However, the repetitive process of “modeling-meshing-computing” consumes substantial manpower, time, and expertise. This study proposes an approach consisting of three key steps: (1) predicting strain distributions, (2) determining failure modes, and (3) analyzing interpretability of predicted results. Specifically, DeepLabv3+ is used to map the Finite Element (FE) model to strain distributions. A binary classification model based on VGG-16 predicts the failure state of the specimen. Interpretability analysis, using Gradient-weighted Class Activation Mapping (Grad-CAM), provides insights into the neural network’s decision-making process. The optimized models achieve a Mean Intersection over Union (MIoU) of 0.5691 for strain distribution prediction on the cross-sectional surface and 0.6424 on the front surface. The failure detection model achieves an F1 score of 0.992 in determining failure states. The interpretability results align well with fracture mechanics theory, enhancing confidence in the model’s predictions. This method serves as a surrogate to reduce the workload of finite element analyses, facilitating strain analysis and failure detection.

Simplified Analytical Approach for Calculating the Transverse Load Distribution of Precast Slab Bridges with and without Concrete Overlays

Simplified Analytical Approach for Calculating the Transverse Load Distribution of Precast Slab Bridges with and without Concrete Overlays

Assisting Load Rating Testing of Precast Reinforced Concrete Bridge Slab through Digital Twins and Field Monitoring Data

Assisting Load Rating Testing of Precast Reinforced Concrete Bridge Slab through Digital Twins and Field Monitoring Data

The effectiveness of metaheuristic algorithms modified with Fitness Distance Balance (FDB) method on RC slab bridge superstructure optimization

The effectiveness of metaheuristic algorithms modified with Fitness Distance Balance (FDB) method on RC slab bridge superstructure optimization

Acoustic emission technology-based waveguide localization method for damaged internal tendons of in-service post-tensioned hollow slab bridges

Prestressing tendons are crucial load-bearing elements in post-tensioned hollow slab bridges. Damage to these tendons significantly reduces the safety, functionality, and longevity of the bridge. Regular monitoring of prestressing tendons is essential for bridge operation. Acoustic emission technology, known for its high accuracy and sensitivity to minor vibrations, is a key technique for monitoring bridge cables. This study proposes a novel dual-sensor acoustic emission localization method for detecting tendon damage in post-tensioned hollow slab bridges, utilizing waveguide technology. The effectiveness of this method is confirmed through hammering tests that simulate acoustic emission damage on operational hollow slab bridges. The proposed method, requiring only two sensors, offers a cost-effective alternative for monitoring the entire span of post-tensioned hollow slab bridges, so that effectively reduces the cost of bridge health monitoring and is easy to be promoted in actual engineering projects.