Journal of Bridge Engineering

Corrosion and traffic-induced fatigue are two major threats to RC bridges in high-traffic and corrosive environments. Coupled interaction of these two mechanisms, referred to as corrosion–fatigue, causes gradual material degradation of bridge girders and leads to an enhanced seismic vulnerability of bridges as deterioration proceeds. In this context, the paper develops a numerical framework to estimate seismic resilience of two RC bridges, having two and three spans, subjected to combined corrosion–fatigue degradation over their lifecycles. Modeling of corrosion–fatigue involves the simulation of fatigue loads on bridge girders using stochastic samples of gross vehicle weights obtained from weigh-in-motion measurements and estimation of fatigue stresses at fatigue-critical locations of bridge girders. Observed time-variant deterioration of bridge girders due to corrosion–fatigue is utilized to develop finite-element models of these bridges, in which piers are also assumed to have corrosion. Analyses result in an estimation of seismic vulnerability and resilience of these bridges in the life-cycle context. Among the two bridges, a three-span bridge is observed to experience higher reduction in resilience with time due to its higher flexibility than does a two-span bridge. Overall, research outcome demonstrated the confronting role of corrosion–fatigue degradation and emphasized its adverse impact on life-cycle seismic resilience of RC bridges.

This paper proposes a novel bridge damage identification methodology using simulated rotation measurements. To illustrate the concept, a numerical 1D beam model subject to a one-axle moving vehicle model is presented. Different bridge segmentation strategies, damage scenarios, and measurement points are considered to demonstrate the detection, localization, and severity quantification capability of the proposed approach. To extend the application to a bridge subject to a fleet of unweighed multiaxle vehicles, the proposed method is combined with an iterative Bridge Weigh-in-Motion algorithm to obtain vehicle weights, bridge damage presence, and location. The results indicate that even if the vehicle weights and damage location are unknown, the proposed method can successfully detect and localize damage. The severity of the damage can also be predicted with reasonable accuracy. Finally, the proposed damage identification system is applied to measurements simulated with a fully calibrated (using in situ measurements) 3D finite-element model of a simply supported multi-T-girder bridge. Results confirm that the proposed system can accurately and automatically detect, localize, and quantify the severity of the defect for a range of cases.

Accurately identifying tension force on cables is of great significance for construction control and the operational status assessment of a bridge during its lifetime. Unlike the conventional vibration methods that encounter problems in the inaccurate identification of short cables and difficulties when identifying multiparameters simultaneously, when solving the vibration differential equation inversely, a novel strategy was proposed that was based on an intelligent algorithm for cable parameter monitoring onsite. The Extreme Gradient Boosting (XGBoost) model was employed to establish the mapping relationship between the natural frequencies of the cable and its tension, bending stiffness, and boundary conditions through data mining. The results revealed that when the measured natural frequencies of a cable were fed into the XGBoost model, the previously mentioned multiparameters could be identified simultaneously with a relative error of <5%. Meanwhile, the proposed intelligent method with the XGBoost algorithm produced a more accurate identification of the cable parameters than the extreme learning machine (ELM) and conventional vibration methods. The current intelligent strategy might provide efficient tools for the simultaneous identification of multiple parameters in cables and, therefore, might facilitate policy decisions for the structural maintenance of cable-supported bridges.

The ability to estimate, with reasonable accuracy, the likelihood and extent of damage to bridges following an earthquake is crucial to postearthquake response activities. While the development of seismic demand models has seen considerable progress, there is a significant gap in our current ability to correlate demands with capacity limit states, particularly for older bridges with nonductile detailing. A simulation model was developed for typical nonductile bridge columns considering potential failure modes and incorporating critical response effects at the material and sectional levels. A primary drawback in using ductility-based measures to characterize capacity limit states under random earthquake-induced loading led us to develop a damage index–based approach to classifying limit states. The proposed damage-based approach was validated against experimental data and then applied to single-column bridge bents. Fragility functions were developed by which the exceedance probabilities of damage states could be examined and median estimates used to develop damage-index ranges for each limit state. The findings from this study will not only assist in postearthquake emergency response efforts, but also in prioritizing the strengthening of older, nonductile bridges.

The main cable of a self-anchored suspension bridge (SSB) is directly anchored to the two ends of a stiffening girder, and the stiffening girder is therefore subjected to enormous axial force and bending moment. This paper proposes a new method to determine the reasonable completed bridge state of the SSB in preliminary design. This method can accurately find the main cable shape that satisfies the minimum bending strain energy of the stiffening girder without being trapped in a local optimum. The method is suitable for the SSB with three-dimensional cables. Based on the segmental catenary theory, the relational expression of the component of the main cable tension in the longitudinal direction and the hanger tension is derived. Also, the partial differential equations for the condition at which the stiffening girder has minimum bending strain energy are also presented, which innovatively incorporates the effect of the vertical curve of the stiffening girder. The problem of solving simultaneous equations is converted into an optimization problem, which is then solved using the generalized reduced gradient method to obtain the hanger tensions and the main cable shape in the completed bridge state. The solving process is clear and has explicit physical meaning. Besides, there is no need to build a finite-element model. A calculation example is used to verify the applicability and accuracy of the proposed method. The mechanical behaviors of the cable-only system are further analyzed. On this basis, the approximate expressions of the component of the main cable tension in the longitudinal direction and the partial derivative of this tension component with respect to each vertical component of the hanger tension are provided.

To study the flexural behavior of composite girders with concrete-filled steel tubular (CFST) truss chords under positive and negative bending moments, model tests, and theoretical analysis were carried out to investigate the evolution of their flexural behavior and the flexural bearing capacity. The results showed that the web members and joints of composite girders with CFST truss chords subjected to positive and negative bending moments had high strength and rigidity, which ensured that joint failures did not occur before the failure of the entire cross section. The longitudinal strains along the member axis changed linearly along the cross-sectional height, which confirmed the correctness of the plane-section assumption. The failure mode was due to the yield of the steel tube used in the chord and the rebars in the concrete slab under positive and negative bending moments, respectively. The contributions of the web members to the flexural bearing capacity under positive and negative bending moments were 12.5% and 8.6%, respectively. Calculation methods considering the contributions of the web members to the flexural bearing capacity under positive and negative bending moments were proposed. The deviation between the results of the proposed calculation methods and the test and the results of the finite-element parametric studies was less than 8.1%.

This paper presents a novel method for calibrating a physics-based corrosion prediction model using a deterioration curve derived from field-based bridge condition assessments. The corrosion model used in this study considers inputs such as corrosion rate to predict outputs such as concrete crack width. Deterioration curves that present bridge element condition versus time are converted into crack width versus time using inspection guidance from transportation agencies. Input parameters of the corrosion model are calibrated by matching the crack widths predicted by the corrosion model with those predicted by the deterioration curves. The calibration method is demonstrated for a reinforced concrete bridge column in this article. The corrosion rate before cracking, the pitting factor, and the ratio of corrosion rates at critical crack width and before cracking significantly influenced the model results and were calibrated. Postcalibration input parameter ranges were narrower than but within the ranges reported in the literature. A physics-based corrosion model thus calibrated using field inspection data can potentially improve the predictions of future structural health and aid in asset management.

Existing studies optimized the tuned mass damper (TMD) for vortex-induced vibration (VIV) control of bridges based on an empirical linear model or Scanlan’s nonlinear model, which cannot accurately simulate the effect of the vortex-induced force and hence results in a TMD design that lacks effectiveness or robustness. Four vortex-induced force models are considered to systematically analyze the influence of force models on TMD design for VIV control. The design results based on various vortex-induced force models, as well as three design formulas, are compared in terms of effectiveness and robustness. Numerical results suggest that the empirical linear model and Scanlan’s nonlinear model significantly underestimate the TMD mass ratio required to suppress the VIV amplitude to be lower than a threshold. The empirical linear model may overestimate the robustness of the TMD to changing the frequency ratio, while Scanlan’s nonlinear model may overestimate or underestimate the robustness depending on the threshold VIV amplitude. The TMD design based on the polynomial model is considered more accurate since it can accurately predict VIV responses at various effective damping levels. The aerodynamic envelope model can be used as a convenient model for TMD optimization. The results generated using the free vibration formula are the closest to that of the polynomial model. An appropriate safety factor should be considered to convert the TMD design based on sectional model experiments to real bridges.

The bridge weigh-in-motion (BWIM) technique uses the instrumented bridge on a large scale to identify the axle weight of a passing vehicle. Vehicle configurations, e.g., axle number and wheelbase, are crucial for the BWIM system, which require additional axle detectors. Free of axle (FAD) sensors are often used to obtain vehicle information, but they are only suitable for specific bridge types, such as slab-girder bridges. The concept of a virtual-axle-based algorithm, without requiring axle detectors, has been developed, and the validity of this algorithm has been verified numerically and experimentally. However, this algorithm assumes the vehicle speed as a known input, indicating that additional speed sensors/devices are still required in the BWIM system. Using this virtual-axle-based algorithm in a field test, it is found that the identification accuracy of the BWIM system is sensitive to the vehicle speed, and it shows poor recognition of vehicle configuration. To improve the recognition accuracy and remove vehicle speed detectors from the BWIM system, an extended BWIM system is proposed using the regularization technique and iterative approach. Both vehicular virtual axles and speeds are assumed in this approach. An error function based on the measured responses and theoretical ones is built to evaluate these assumed vehicle configurations and speeds. The effectiveness of the proposed approach is verified by the field tests. The results show that the proposed approach can obtain high recognition accuracy, which is close to Moses’s algorithm using FAD sensors. Compared with the previous virtual-axle-based algorithm, the recognition accuracy and robustness of the proposed approach are greatly improved. The proposed approach is still challenged by real-world traffic because this paper only considers the case when a single vehicle passes over the bridge. Nevertheless, the proposed extended BWIM system shows potential practical applications as it can further reduce costs and be applicable to more bridge types.