Journal of Bridge Engineering

Concrete cracking is one of the important factors affecting the safety and durability of composite bridge structures. While the existing crack width calculation methods cannot accurately predict the crack width of ultrahigh-performance concrete (UHPC), this paper aims to investigate flexural crack performance (e.g., failure mode, crack width, and crack spacing) of an innovative composite deck structure comprising an I-steel beam and glass fiber‒reinforced polymer (GFRP) strips‒UHPC composite deck. Three GFRP‒UHPC composite slabs and two steel‒GFRP strips‒UHPC composite beams are designed to explore the cracking behaviors in transverse and longitudinal directions, respectively. The effects of reinforcement ratio and the steel fiber content on flexural cracking behavior are analyzed. The results showed that increasing the reinforcement ratio restricts the formation and growth of cracks and reduces the crack width and average crack spacing in the UHPC plate. However, the impact of steel fiber content is small. The steel‒GFRP strips‒UHPC composite beams fail owing to the yield of the I-steel beam and longitudinal reinforcement bar in the UHPC plate, while the GFRP‒UHPC composite slabs collapse as a result of the yield of reinforcement bar in the UHPC plate. Based on the existing test results, the formulas are proposed to estimate the reinforcement stresses and the maximum crack width in the steel‒GFRP strips‒UHPC composite deck structure, and the findings have indicated good agreement with the measured ones.

When hollow reinforced concrete (RC) columns are retrofitted with concrete filling, the hollow interior cannot always be accessed to treat the internal surface. Without this treatment, an optimal bond between the newly introduced concrete and the existing column cannot be established; as a result, the two parts do not behave as a single unit. This study conducted cyclic loading tests on three types of large RC column specimens: a hollow RC column, a hollow RC column with a solid section at the column base, and a hollow RC column retrofitted with concrete filling (lacking inner surface treatment). The aim of this study was to investigate the effectiveness of a concrete-filling retrofitting method for hollow RC columns when the filled and existing portions behave separately, assuming a situation in which the bond between the filled and existing portions cannot be strengthened. The results indicated that concrete-filling retrofitting can suppress the inward buckling of the internal longitudinal bars, thereby enhancing the flexural deformation capacity of hollow RC columns to some extent. However, this did not prevent the significant axial settlement and reduction in the lateral load capacity that occurred when the inner longitudinal bars buckled. This is because the filled portion cannot resist axial forces when the filled and existing portions behave separately. Additionally, it was suggested that retrofitting with concrete filling does not substantially improve the shear resistance of a hollow RC column when the filled section behaves separately from the existing section.

Accurate deflection prediction of in-service bridges can be used to assess the overall structural stiffness and detect abnormal states in advance. The bridge structures, especially long-span bridges, experience varying environmental and operational conditions, including temperature, humidity, wind excitation, and traffic loads, as well as long-term material deterioration and stiffness degradation mechanisms, and therefore, their deformation behavior shows complex variation phenomena, which pose challenges to many current deflection prediction methods. To address this subject, a Bayesian dynamic difference model (BDDM) to predict bridge deflection behavior online is proposed in this paper, explicitly considering the effect of the nonstationarity of time series data under varying environmental and operational conditions. A novel dynamic difference model is first proposed to include the nonstationary residual term and provide a linear approximation of a complex nonlinear process. Then, the formulas for recursively updating the dynamic difference model based on Bayesian inference are proposed. The proposed method is first validated through a numerical application using simulated nonstationary time series data with a nonlinear trend, indicating that it can adaptively capture nonstationary variations, update noise variance estimations, and improve prediction accuracy. To further demonstrate its performance, the BDDM is employed to predict the daily maximum deflection of a real-world cable-stayed bridge using measured data, and its performance is compared with several existing methods. The findings reveal that the proposed method outperforms other methods in terms of prediction accuracy, and can be potentially implemented for an online monitoring and early warning system.

Changes in vehicular loading over time have caused some concrete slab span bridges to rate poorly when considering modern truck weights, which leads to load posting and restrictions that in turn lengthen trucking routes. A potential way to allow heavier vehicles to cross these bridges would be to increase the load rating by utilizing a more accurate live load distribution factor generated from field testing and computational modeling. The focus of this study was to determine the live load distribution factor for two slab span bridges using results from live load testing and plate model analysis. Field testing utilized a suite of instrumentation, and simple isotropic or orthotropic plate models of the slab span bridges were validated with field data to further investigate live load distribution. Field-test estimates of equivalent width computed using displacement data were more precise than those using strain data, but modeling indicated that strain data may better capture the distribution of stresses in the slab. Despite significant visible damage, the field bridge behaved more like an isotropic plate. AASHTO equivalent widths were conservative when compared with those computed from the field results and isotropic model for single-lane truck loading but were similar to each other for multilane loading. However, model results also indicated that the equivalent width depends on the load configuration, such that single-axle loading will be concentrated into a narrower strip compared with tandem loading. In addition, an orthotropic slab will further narrow the equivalent width compared with an isotropic slab, such that AASHTO equivalent widths may no longer be conservative for single-axle loading of a slab so degraded that it may be treated as effectively orthotropic.

The traditional multiscale model static updating method for long-span bridges requires load tests to obtain the correspondence between load and response, which leads to prolonged traffic interruption, with poor timeliness and low efficiency. Therefore, an efficient multiscale model dynamic calibrating framework based on stochastic vehicle-induced responses is proposed in this paper. The multiscale model is calibrated by monitoring data, and the dynamic calibrating efficiency is improved through the substructure–refined model combination modeling. First, the relationship between the structure and its corresponding response statistical characteristics is derived under stochastic traffic loads, and a statistical-based calibrating objective function of the multiscale model is established. Second, the framework for efficient multiscale model dynamic calibrating based on long-term monitoring data is presented, including efficient multiscale model establishment and dynamic calibrating based on stochastic vehicle-induced responses. Finally, the effectiveness of the proposed method is verified by its application to a long-span steel box girder suspension bridge. Comparison with the traditional load test method demonstrates that the proposed method effectively achieves multiscale model dynamic calibrating based on monitoring data during bridge operation, improving calibrating efficiency while ensuring multiscale modeling accuracy.

Single-column bridges are widely used for urban overpasses and highway bridges. Rising overturning incidents have exposed the vulnerability of this type of bridge, which is inherently susceptible to overturning collapse. A typical solution is to provide vertical restrainers at the beam ends. However, the current antioverturning calculation method was incapable of coordinating deformations between bridge components, which may have severe consequences in engineering practice. For example, the Huahu Viaduct, located in Hubei, China, experienced overturning failure even after applying vertical restrainers, which was not anticipated according to the current engineering experience. In this work, we proposed a modified calculation method regarding deformation coordination to predict the ultimate overturning capacity, verified through forensic investigation and numerical analysis, of the Huahu Viaduct. Compared with bridges without restrainers, overturning failures start with the failure of restrainers. Failure mechanisms are analyzed, including critical states and overturning features. Further comparison indicates that the practical method overestimates the ultimate overturning capacity by up to 38%, while the proposed method provides a more effective reference to this problem in engineering practice.

This paper presents a novel framework for assessing the impact of construction defects on bridge deck corrosion-induced deterioration. The model developed quantifies the impact of insufficient concrete cover, damage to the rebar epoxy coating, improper curing technique, and excessive water–cement ratio on the lifespan of concrete bridge decks. Regional variations, including freeze–thaw cycles, carbonation, and deicing salt usage, are also considered in the model. Two applications for estimating deterioration and decrease of condition rating are presented. Simulation results using the model developed reveal a substantial loss of life when these defects occur. This work highlights the importance of proper construction practices in ensuring long-term infrastructure integrity. Moreover, it provides a valuable tool for assessing the impact of these common construction defects on bridge deck deterioration. This tool enables bridge managers to make better-informed decisions regarding repair operations and ask contractors for fairer compensations when defective practices are observed during construction.

The blast resistance of a typical two-lane steel girder highway bridge structural system was modeled using a nonlinear finite-element approach that considered material damage, fracture, and separation. Critical blast scenarios were based on field observations of terrorist attacks on bridges in Iraq, while system failure was defined in terms of practical emergency serviceability criteria used on actual blast-damaged bridges. The blast resistance of various design parameters was assessed, including the number of girders, deck concrete strength, reinforcement ratio, slab thickness, girder and reinforcement yield strength, girder sectional dimensions, and pier column width. The presented approach uniquely quantifies structural system blast resistance in terms of the charge weight that can be applied at different locations until failure. A sensitivity analysis was conducted to determine the most influential design parameters. It was found that system blast capacity was primarily influenced by the number of girders and girder yield strength, while additional significant parameters were deck compressive strength, deck thickness, web stiffener width, and girder depth. Secondary parameters were deck reinforcement ratio, girder flange, and web thickness, while deck reinforcement yield stress was found to be insignificant. Based on the results, recommendations for improving blast resistance are provided.

With the increase in span, the flexibility and sensitivity to aerodynamic damage of bridges significantly increase. However, current research studies primarily focus on analyzing the single environment, leaving the safety and durability of bridges under extreme weather relatively understudied, such as snowdrift. This study selects four typical box girder bridges as test models to conduct wind tunnel tests. By analyzing similarity principles and particle properties, polyethylene particles are chosen as the test medium, and their simulation accuracy is validated using a step-type flat roof model. The study then explores wind-induced snow redistribution on the surfaces of the four box girder bridges under different horizontal wind speeds, initial particle heights, and wind attack angles. The results demonstrate that as the surface configurations of the test models become more complex, the particle redistribution becomes more chaotic. Among the three test conditions, the wind attack angle exerts the greatest influence, followed by horizontal wind speed and initial particle height. Notably, the dimensionless redistribution coefficients of particles on the surface of the large-span highway box girder bridge show the largest differences under these test conditions, with average differences and maximum differences reaching 50.3% and 63.5%, respectively, for different wind attack angles. These findings provide data support for the investigation of the safety and durability of real bridges under extreme weather conditions.