Simply-supported Bridge Research Articles

Automatic crack detection method for high-speed railway box girder based on deep learning techniques and inspection robot

Box girders serve as crucial upper-level load-bearing components in high-speed railway simply-supported bridges, requiring sufficient structural rigidity during operation. The occurrence of cracks compromises the overall stiffness of the structure, posing significant safety risks and potentially leading to substantial loss of life and property. Therefore, it is essential to rapidly and accurately detect cracks within the girder structure, particularly in the interior of box girders where access for maintenance by personnel is inconvenient. To address this issue, this paper proposes a robot-based framework for crack detection in high-speed railway box girder, and accurately evaluate the damage status of structures. This comprehensive framework includes an image generation network for generating high-quality crack images, a lightweight object detection algorithm for rapidly identifying crack targets, and a high-precision semantic segmentation algorithm for accurately extracting crack pixels. Comparative analysis with mainstream algorithms validates the superiority of the proposed methods. Moreover, preliminary validation through simulated tests highlights the feasibility of the proposed framework, offering novel method and theoretical support for the intelligent operation and maintenance of high-speed railway bridge structures.

Stochastic optimization of levitation control system for maglev vehicles subjected to random guideway irregularity

The dynamic performance of maglev vehicle-bridge coupled systems subjected to random guideway irregularity, especially the levitation stability of the running vehicle subsystem, is a critical issue affecting the safe operation and the comfort riding of maglev railways. This study is devoted to stochastic optimization of the levitation control system considering the coupled vibration of maglev vehicle and bridge under the random guideway irregularity. To alleviate the computational burden in the stochastic optimization process, the explicit expressions of the critical responses of the maglev vehicle-bridge coupled systems and the sensitivities of critical responses with respect to the feedback gains of the proportional-integral-derivative (PID) levitation controller are respectively constructed in terms of the guideway irregularity by virtue of the dimension-reduced formulation capability of the explicit time-domain method (ETDM), enabling stochastic dynamic analysis and stochastic sensitivity analysis to be executed at high efficiency. The stochastic optimization problem is formulated as the minimization of the standard deviation of the air gap variation with the constraint on the standard deviation of the current variation, and the optimal values of the PID gains are searched by the gradient-based method of moving asymptotes (MMA), in which the statistical moments and moment sensitivities of the critical responses required in the optimization process are obtained by ETDM. A numerical example with a 2-degree-of-freedom maglev vehicle moving on a multi-span simply-supported bridge is used to demonstrate the efficacy of ETDM for the stochastic analysis of maglev vehicle-bridge coupled systems under guideway irregularity. An engineering example involving a 3-car maglev train traversing a multi-span simply-supported bridge is further presented to show the effectiveness of the ETDM-based approach for the stochastic optimization of large-scale engineering problems. The levitation stability of the maglev train under the action of random guideway irregularity is considerably improved with the use of optimal feedback gains.

Reliability assessment of ballasted railway bridges considering soil-structure interaction using ensemble of surrogate models

ABSTRACT The increasing speeds of modern trains lead to excessive vibrations on the bridges, which have the potential to destabilize the ballast particles. The occurrence of this phenomenon not only increases the track maintenance cost, but can also disrupt the load path from the rail level to the bridge deck, posing a risk to the train running safety. The design regulations indirectly control this limit-state by restricting the vertical acceleration of the bridge deck. The assessments pertaining to this purpose often neglect the soil-structure interaction (SSI) effects considering that as a conservative assumption. Such effects can positively contribute by increasing the system damping, but they can also increase the bridge flexibility making it more susceptible to vibrations due to reduction on critical speed. Therefore, this study investigates the influence of considering/disregarding SSI effects on the ballast destabilization phenomenon using a probabilistic methodology. The results are classified based on the maximum permissible train speeds and the bridge span length. Due to the high computational costs of the reliability analyses, the associated limit-state is approximated by an ensemble of classification-based surrogate models using the stack-generalization concept. Subsequently, the upper/lower bounds of the failure probability in the presence of SSI effects are compared with those obtained for simply-supported bridges. It is pointed out that neglecting SSI effects for shorter span bridges may lead to an underestimation of system safety. For longer span bridges, however, this may lead to an overestimation of safety, which means that a non-conservative system can be designed.

Dynamic behaviour of bridges under critical conventional and regular trains: Review of some regulations included in EN 1991-2

In the field of structural analysis dedicated to the study of vibrations of high-speed railway bridges, one reference load model is the well-known HSLM-A, which limits of validity are stated in Eurocode EN 1991-2, Annex E. In a recent paper published in the Journal of Rail and Rapid Transit, the authors investigated the degree of coverage provided by HSLM-A to critical articulated trains. Now in the present article, the authors have extended those analyses to critical conventional and regular trains as well. This is an important aspect because HSLM-A as such is an articulated-type model, so it is of interest to understand how it deals with covering the various resonance phenomena generated by other train types. Therefore, the main goal of this work is to establish whether the conventional and regular trains that stem from the validity rules given in Annex E/EN 1991-2, produce vibratory effects that are duly covered by HSLM-A. Following the aforementioned validity rules, one first aspect analysed is the importance of near-to-integer wheelbase ratios in the coupled vibrations produced by conventional trains. Subsequently, seven realistic, conventional and regular high-speed train models have been synthesised; these models have been made publicly available in Mendeley Data, and comprise almost 3800 different sequences of axle loads. Finally, the response of simply-supported bridges has been analysed with a view to compare the seven synthesised models versus HSLM-A. The exceedance and required speed increase have been computed for both displacements and accelerations, in a comprehensive ensemble of spans and speeds. The results provide a diagnosis of the degree of coverage of HSLM-A with respect to those conventional and regular trains compliant with Annex E/EN 1991-2.

Contact-point response reconstruction for indirect bridge monitoring via Bayesian expectation-maximization based augmented Kalman filter

The drive-by bridge dynamic measurement using an instrumented vehicle during its passage over the bridge can be an indirect bridge structural health monitoring system. The identification of the contact-point (CP) responses between vehicle wheels and bridge structure from vehicle responses offers an efficient and economical way for the modal identification and condition assessment of short- to mid-span road bridges. This paper proposes a novel method for the contact-point displacement response reconstruction of the vehicle-bridge interaction (VBI) system in a joint input-state estimation manner based on Bayesian Expectation-Maximization (BEM). An analytical model of VBI including the road approach in front of a simply-supported bridge is presented firstly. Then the augmented state-space model of the vehicle with the contact-point responses included as variables along with vehicle states is established. A new method by integrating the augmented Kalman filter (AKF) with a BEM strategy is proposed to solve the state estimation problem without knowing the vehicle axle responses. The vehicle states and CP displacement responses are identified simultaneously. The effects of the measurement noise, road surface roughness and vehicle speed on the identified results are investigated using numerical simulations. The experimental tests are used to further verify the feasibility and accuracy of the proposed method. The results show that the proposed method has potential for drive-by bridge condition assessment using on-board vehicle response measurements for a large population of short- to mid-span bridges.

Performance parameter design of seismic isolation bearings for high-speed railway simply-supported bridges using neural network

In the simply-supported bridge system for the high-speed railway with unequal pier heights, the intrinsic relationship between the seismic isolation bearing parameters and the seismic performance objectives of the bridge is very complex. It is not easy to establish a precise mathematical model, and the design process of the bearings relies heavily on the experience of the designers. This paper uses an artificial neural network (ANN) to design the seismic performance of seismic isolation bearing. Considering that the triple friction pendulum bearing (TFPB) can adaptively change the stiffness under different seismic levels, the ANN model fits the mapping relationship between the parameters of the TFPB and the seismic performance objectives. Four evaluation indexes are used to verify that the ANN model has good generalization ability. A case study shows that the designed bearing meets the expected seismic performance requirements, which verifies the applicability of the ANN model.

Simplified linear analysis model of longitudinal constraint effect of high-speed railway simply-supported bridge under frequent earthquake

Simplified linear analysis model of longitudinal constraint effect of high-speed railway simply-supported bridge under frequent earthquake

Seismic assessment and parametric analysis on a multi-level aseismic simply-supported bridge with cable-restraining composite rubber bearings and dissipative controlled rocking piers

Recent earthquakes uncovered the potential risk of widely-used simply-supported bridges (SSBs) to suffer severe bearing and pier damage, which may not be mitigated efficiently by only enhancing one of these components. Hence, this study proposes a novel multi-level aseismic bridge system (MLABS) comprising cable-restraining composite rubber bearings (CRCRBs) and dissipative controlled rocking (DCR) piers to make improvements at the system level. Deterministic and fragility analyses are conducted to compare the seismic performance of the novel system with that of the other three reference ones. Then, an economy analysis is carried out to evaluate economic efficiency. Finally, the effects of four main influential factors are investigated. The results reveal that the novel MLABS is capable of controlling the response of each vulnerable component within an acceptable range so that it can possess a large seismic capacity and a low system fragility. The economy superiority is also proved by the lowest expected losses under the concerned events and the minimum life-cycle cost. The internal sliding area ratio of the bearings is positively related to the performance and the economy, while the optimal design free displacement of the cables is about 140 mm. The pier capacity can be weakened by increasing the initial prestressing force or the energy-dissipating bar area in this case, which reduces the effectiveness and economy in improving the structural performance.

Hybrid Modeling of a Simply-Supported Bridge Under Opposite Moving Loads via Multi-Layered Feed-Forward ANN

Keeping in view the design of short to medium-span bridges in critical locations such as road/river crossings under the action of oppositely moving high-speed loads, this paper presents a hybrid model for the prediction of dynamic displacement employing a theoretical non-dimensional framework aided by an artificial neural network (ANN). The introduction of such a hybrid model reduces parametric space and time. The feed-forward ANN is implemented to train the comprehensive data set obtained from the non-dimensional theoretical scheme. The dimensionless input to ANN comprises the bridge and load parameters, whereas maximum dynamic displacement is the output parameter. The robustness and efficiency of the proposed surrogate ANN framework in terms of computational efficiency are compared with the conventional mode-superposition method formulated in dimensionless form. The training of test and validated data sets results in best-fit models with optimistic statistical metrics and accuracy [Formula: see text] 6%. Moreover, the sensitivity of different parameters to the displacement response is highlighted using Pearson’s correlation and Quantile–Quantile plots. To incorporate the best-fit models into the design by bypassing the high-fidelity model, a user-friendly interface is developed, confirming the standards of the high-speed rating code (TZY2014-232 2014). Such interfaces have the potential for wide application in the preliminary design of short-to medium-span bridges under opposite moving loads in critical locations such as crossing valleys, rivers, and railroads.

Visualization of structural health monitoring information using Internet-of-Things integrated with building information modeling

Structural Health Monitoring (SHM) has become a paramount necessity in civil engineering for improving the operational performance of aging infrastructure. Recent monitoring techniques have utilized emerging technologies in Industry 4.0, such as the Internet of Things, Big Data analytics, cloud computing, and cybersecurity, to automate SHM methodologies. However, they have found challenges in linking these technologies and developing an autonomous, well-established digital framework for applications of SHM. Visualizing processed SHM data in a real-time digital interface generates multiple obstacles, such as witnessing delays in data transfer and resorting to offline tools for manual data processing. This paper, therefore, explores the integration of Building Information Modeling (BIM) and the Internet of Things (IoT) through an Arduino micro-processing unit for tracking and visualizing the data from the time and frequency domains. Strategies for enabling data monitoring and processing are developed while continuously acquiring structural responses. The query of data is established in a web-based database instead of storing the data in offline resources that await manual intervention. The proposed real-time SHM methodology is validated experimentally using two practical applications: a dynamically moving vehicle over a simply-supported bridge prototype and a randomly excited three-story model with real-time visualization of both time- and frequency-domain information under undamaged and damaged conditions. The proposed research develops an early-phase Digital Twin (DT) to present static and real-time dynamic data in a rich-fed BIM database.

Seismic applicability analysis of high-speed railway multi-span simply-supported bridges based on simplified model

Seismic applicability analysis of high-speed railway multi-span simply-supported bridges based on simplified model

Vulnerability analysis of HSR bridge under near-field blast based on response surface method

In this paper, the vulnerability analysis of a high-speed railway (HSR) bridge system attacked by the near-field blasts is conducted using the response surface method. An “explosive-air-ground” coupling analysis model is established by the ANSYS/LS-DYNA software. Through a comparison of the numerical simulated and the experimental results, the effectiveness of the Arbitrary Lagrangian Eulerian (ALE) algorithm and the accuracy of the analysis model are verified. Then, the dynamic responses of an HSR simply-supported bridge subjected to four types of car-bomb blasts are calculated. The damage levels of the bridge components are evaluated using the residual bearing capacities of the pier and beam, and the shear displacement of the bearings. By adopting the central composite design method, the response surface models for the evaluation indices of the bridge components are fitted. Furthermore, the failure probabilities of each component at various damage levels are calculated, and the vulnerability of the bridge system is analyzed based on the Boundary Estimation Method. The proposed method could predict the damage probability of the bridge system under various car-bomb blasts, and provide a reference for exploring a probability-based evaluation method for the post-blast safety of the HSR bridges.

Dynamic amplification of multi-span simply-supported prestressed concrete girder viaducts subjected to multi-body heavy vehicles

High productivity freight vehicles (HPFVs) are used in many countries to address increasing freight demand. However, it is then necessary to assess the safety of existing bridge structures subjected to HPFVs because of their increasing mass and dimension. A critical part of this work is to assess the dynamic amplification of such vehicles, without undue conservatism, often based on vehicle–bridge interaction (VBI) modelling. In the VBI problem, the vehicle model is usually derived using the Principle of Virtual Work or Euler–Lagrange methods. However, HPFVs are characterized by multiple bodies and articulation points and these techniques quickly become intractable. Alongside the vehicle model, the bridge is often assumed to be a single simply-supported span, or a few continuous spans, whereas many urban bridge viaducts, in particular, have multiple prestressed concrete (PSC) girder simply-supported spans. Furthermore, these bridges typically have an upwards hog as a result of the prestress and it is hypothesized that certain combinations of vehicle, hog, span length, and number of spans, could produce a large dynamic amplification of static load effects. In this work, Kane’s Method is applied to heavy vehicle with multi-trailers combinations which provides a relatively easy, systematic, and numerical manipulation means of determining the vehicle dynamic equations. The 9-axle B-Double vehicle, common in Australia, is used as an example to illustrate the procedure of deriving the vehicle dynamic equations. We apply the resulting vehicle models in a comprehensive VBI model to consider the dynamic amplification of PSC girder viaducts. The results indicate that the studied PSC girder viaducts experience higher amplification than the equivalent single-span simply-supported bridges. Recommendations for future studies and practice, such as the number of spans in the viaduct to obtain the ‘convergence’ of dynamic amplification, are given.

Reduction of the Longitudinal Seismic Response of High-Speed Railway Multi-Span Simply-Supported Bridges by the Track Constraint

ABSTRACT The longitudinal seismic response reduction in railway bridges is worthy of attention because it relates to the engineering cost. It is difficult to further explore the reduction effect because the complexity of traditional analysis model leads to the low efficiency in parametric analysis. In this paper, the track structure was simplified, and a simplified calculation model was established. The parametric analysis considering the span number and pier height on the simplified model seismic responses was carried out. The results showed that the reduction effect was extensive and there was a great internal force transferred to the subgrade-track structure.

Artificial neural network-based multiple-input multiple-output metamodel for prediction of design parameters for a high-speed rail viaduct

The prediction of the design parameters of short to medium-span supported bridges in critical locations (such as canal/road crossings) under the action of high-speed trains has been investigated in this article. An artificial neural network (ANN)-based MIMO (multiple-input multiple-output) metamodels is proposed in conjunction with the semi-analytical framework of simply-supported bridges. Three cases, namely single moving load, series of moving loads at equal spacing (HSLM-B), and as per conventional train configuration (HSLM-A) recommended in Eurocode1: EN 1991-2 (2003), are considered. The prime novelty of the article is to develop a dimensionless semi-analytical framework to train and validate a MIMO metamodel implementing ANN for predicting the multiple dynamic responses of bridges under high-speed loads. The dependency of the maximum dynamic responses, that is, displacement, shear force, and bending moment, on the governing parameters (structural and loading) have been elucidated using Pearson's correlation matrix for the three different train configurations. Further, the robustness and efficiency of the best-fitted metamodels have been compared, and a user interface has been developed for ease of implementation. This platform evaluates the responses such as displacement, shear force, bending moment, and structural safety confirming the standards of Eurocode EN 1990:2002 + A1:2005 (E).

An effective procedure for extracting mode shapes of simply-supported bridges using virtual contact-point responses of two-axle vehicles

This paper proposed an effective procedure using virtual contact-point responses to extract mode shapes of a simply-supported bridge. The theoretical closed-form solution of virtual contact-point response using two connected two-axle vehicles is derived based on the vehicle-bridge interaction theory. Variational mode decomposition and band-pass filter (VMD-BPF) method is adopted to decompose the virtual contact-point responses and extract the bridge mode shapes. And a mode shape splicing method is proposed to reduce the influence of vehicle length on the bridge mode shape identification. The accuracy of the identified mode shapes is verified by numerical simulations, indicating that the virtual contact-point responses of the front axle or rear axle in the two-axle vehicle can be used for mode shape extraction. Furthermore, parametric studies such as track irregularity, vehicle speed, and noise are conducted to analyze the parameters that affect the identification accuracy of the mode shapes. The results show that the first four order natural frequencies and corresponding mode shapes of bridges can be well identified by the virtual contact-point responses even when the track irregularity of grade 4 is used. It is also demonstrated that the proposed procedure has a good performance and robustness in extracting the mode frequencies and mode shapes of simply-supported bridges.

Statistical study on the derailment factor considering the weak correlation of lateral-vertical wheel-rail forces of a vehicle-bridge system

This paper proposes a stochastic method to solve the weak correlation of lateral-vertical forces when the train crosses a bridge. This method treats the Kalker creep equation with Taylor series and uses the moment statistical method to approximate the numerical characteristics of the nonlinear terms of the equation. The variance recursive method, mean recursive method, and lateral linear creep force modulation function are proposed. Based on these methods, the approximate numerical solutions for the standard deviation of the lateral linear creep force and the correlation coefficient of the lateral-vertical forces are obtained and verified by Monte Carlo method (MCM). Under certain preconditions, the derailment factor considering the correlation of the wheel-rail forces obeys the Approximate Cauchy Distribution, which is verified by the Kolmogorov–Smirnov test. The correctness of the proposed method is validated comparing the similarity of the derailment factor extreme value cumulative distribution function curve obtained by MCM. The case of a 6-car Pioneer EMU running through a 3-span 32 m simply-supported bridge is concerned by the proposed method and it is found that there is a significant difference with different traffic intense of the railway.

Effect of girder deformation on the dynamic performance of high-speed train-track-bridge coupling system

Aiming at the high-speed railway (HSR)-China Railway Track System III (CRTS III) slab ballastless track (SBT)-simply-supported bridge system, the mapping relationship between girder deformation and rail deformation had been deduced theoretically, and then, the additional irregularity of the rail was obtained. A dynamic model of the high-speed train-track-bridge (TTB) coupling system was established according to existing theory on the high-speed TTB dynamic interactions. Combined with the mapping relationship, taking the superposition of the additional irregularity and the random irregularity as excitation, the dynamic response of two train models (CRH2 and ICE3 trains) was analysed by using the high-speed TTB coupling system model. The recommended thresholds of girder deformation were given based on running safety and ride comfort indicators. The results show that the sensitivities of the two train models exposed to girder deformation were different, and the CRH2 train was more sensitive to the lateral girder deformation. The non-uniform dislocation deformation of multiple girders exerted a slightly more significant effect on the dynamic characteristics of two train models than the dislocation deformation of single girder. Under the same amplitude of girder deformation, the influences of vertical girder dislocation and vertical girder rotation on the running safety and ride comfort of trains were significantly greater than that of lateral girder dislocation and lateral girder rotation. Acceleration and wheel-rail force increase rapidly in the area of girder deformation. To guarantee running safety and ride comfort of trains, this paper proposes suggested values for girder deformation thresholds.

Improving running safety of railway bridges during earthquakes by equipping vehicle with lateral fuse stopper

Ensuring the safety of the railway vehicles over bridges shaken by earthquakes is a practical issue in the seismic design of railway bridges. To improve the vehicle’s running safety on railway bridges during earthquakes, the stopper (or bump-stop) between the bogie and the car-body of the vehicle was modified as a fuse-type element, i.e., it was designed to break under large impact due to earthquake occurrence. The efficacy of the fuse stopper was illustrated by a full-scale vehicle-track shake table test. The fuse stopper element was introduced to the vehicle-bridge interaction model, whose accuracy was also demonstrated by comparison with the test results. The fuse stopper was designed to remain intact under service level earthquakes (SLE) to avoid frequent replacement or repair, while it should fuse to improve vehicle safety on a group of bridges under design basis earthquakes (DBE). The bridge group includes 24 simply-supported bridges with pier heights ranging from 6m to 60m, covering the most simply-supported bridges in the China railway network. A total of 10 ground motion records were used in the analysis to account for the uncertainty of ground motions. Through vehicle-bridge incremental dynamic analysis (IDA) simulation, the optimal fusion strength of 188 kN and the extended gap of 0.04 m were proposed for the fuse stopper at DBE intensity, in which the bridge group can achieve derailment-free. The design procedure of the fuse stopper may provide a cost-effective way to improve the vehicle’s running safety on a group of bridges during earthquakes.

Target-free vision-based approach for modal identification of a simply-supported bridge

Accurate and efficient vibration response measurement is one of the key tasks in structural health monitoring (SHM) of civil engineering structures. Normally, dynamic responses such as displacement responses, are acquired by physical sensors and data acquisition systems installed on the structures. However, the installation of sensors may be time-consuming and costly. In recent decades, computer vision-based methods have been introduced into civil engineering to provide alternatives for traditional displacement measurements. However, the camera specifications, such as limitations on field of view (FOV) and relatively low resolution of economic lens, have prevented the vision-based method from being widely used for vibration displacement measurement on relatively large-scale structures. This paper proposes a target-free vision-based approach for dynamic displacement measurement and modal identification of simply-supported bridges using a single camera. In this study, a series of videos are captured in separate experimental tests using a consumer-class GoPro on a long-span beam subjected to a moving load. The radial distortion of videos caused by the wide-angle lens is offset by distortion adaption, and the scale factor is fitted using a static video shooting experiment. The tracking process consists of three basic steps, namely, region of interest (ROI) selection, natural feature extraction and features tracking. The results are compared with those measured by linear variable differential transducer (LVDT), demonstrating a high accuracy by the proposed approach. Vibration characteristics, including natural frequencies and mode shapes of the bridge, are identified from the measured displacement. The overall mode shapes are obtained by combining the mode shapes identified from different segmental videos of the bridge obtained by roving the single camera along the bridge for measurements. Comparisons of the natural frequencies and mode shapes between the results from the proposed approach and LVDTs demonstrate the effectiveness and accuracy of the proposed approach for displacement measurement and modal identification of long bridges under moving loads.