Truss Bridge Research Articles

Aerodynamic Characteristics of Express Freight Train on Bridges Based on Wind Tunnel Tests

The express freight trains are being developed rapidly in China, and they have the characteristics of smaller axle weight and higher velocity compared with the normal freight trains. The running safety of the trains on the bridge is significantly affected by the strong crosswind, which may cause overturning accidents in severe cases. The wind tunnel tests of the express freight train–bridge scale models are conducted in this study to investigate the aerodynamic characteristics of the vehicles when they run on the box girder bridge and the double-deck steel truss bridge. The uniform flow and the atmospheric boundary layer (ABL) flow are constructed respectively to compare the differences of the aerodynamic characteristics under different flow fields. The test results show that the distribution of pressure coefficients on the car body is related to the type of test flow field and bridge, and it is also greatly affected by the running position on the bridge as well as the location of the vehicle in the train. The magnitude of the side force coefficients and the rolling moment coefficients of the vehicle on the steel truss bridge are less than those on the box girder bridge. The influence of the flow field type on the side force coefficients of the middle vehicle is slightly larger than that of the tail vehicle, but it has a low correlation with the type of bridge. When the vehicle is on the windward track of the bridge, the values of power spectral density (PSD) of the side force are larger than those on the leeward track. The results provide data support for the running safety research of the express freight trains and reference for the railway vehicle wind tunnel test method.

Seismic performance of a truss bridge with different substructure configurations

Seismic performance of a truss bridge with different substructure configurations

Comparison of Wind Load on Standard Steel Truss Bridge Based on Indonesian Bridge Loading Codes

The truss bridge is a type of bridge that is widely used in Indonesia because of its practicality and can be constructed in short period of time. The relatively light weight of the truss bridge structure also facilitates the transportation of superstructure materials to bridge locations located in remote areas. The dimensions of the large truss bridge and the relatively light weight cause the figure bridge to be vulnerable to wind loads. Meanwhile, the bridge loading regulations including wind load is continuing to change. Previous design code BMS 1992 and SNI T 02 2005 has been superseded with SNI 1725 2016. One of the main changes to the loading regulations is related to the magnitude and how wind loads are calculated and applied to the bridge structure. This study will compare the magnitude of the wind load in the previous loading regulations in Indonesia with the latest regulations and also with wind loading according to AASHTO on steel truss bridges. A 60-class standard steel truss bridge from the Ministry of Public Works which is used for Case Study. The results showed that there was a significant increase in wind loading by applying SNI 1725 2016 loading regulations

A novel structural damage identification method based on the acceleration responses under ambient vibration and an optimized deep residual algorithm

Recently, structural health monitoring (SHM) methods for civil structures have been investigated widely, especially Deep Learning (DL)-based methods. However, it is usually difficult to fully train a deep neural network, and thus, typical DL-based SHM methods are limited in terms of performance. While addressing these issues, in this paper, a novel methodology is proposed for smart damage identification of frame structures. The newly proposed SHM method is based on raw time-domain structural response signals and deep residual network (DRN). The introduced DRN algorithm has been designed and tested in an effective way for extracting and learning the optimum features of the 1D raw ambient vibration acceleration signals, without any need for engineered features. Also, the network’s performance has been optimized using Bayesian optimization, which clearly enhances the network’s accuracy and information flow across it. Next, the outputs of DRNs are further utilized through new methods for damage size estimation and damage localization. The proposed methodology has been evaluated using the datasets of numerical and experimental frames of the SHM benchmark problem and the dataset of a real-world full-scale truss bridge. The results show that the proposed method is capable of detecting, localizing, and quantifying structural damage accurately for all of the simulated cases of the two examples. Furthermore, conducted comparison studies have approved that the new approach is more efficient than other machine learning-based methods, and it can overcome the major limitations of Artificial intelligence-based SHM models.

Displacement-based seismic performance assessment of multi-span steel truss bridges

Simplified mechanics-based approaches for the seismic performance analysis are used for the risk assessment of large bridge portfolios. This study evaluates the applicability and effectiveness of displacement-based assessment (DBA) and nonlinear static procedures for multi-span railway steel truss bridges. Although built in the first part of the last century, these historical bridges are currently in service within the European railway networks, and their seismic performance is poorly investigated in the literature. Direct DBA algorithms and pushover-based procedures aimed at seismic performance assessment and fragility analysis of bridges are presented and tested within a set of case studies parametrically generated by using an archetype steel truss bridge. The first part of this study focuses on the seismic analysis of steel braced towers which, in many situations, compose the substructure of steel truss multi-span bridges. A simplified pseudo-pushover and an accurate equivalent viscous damping formulation are proposed to be used for the approximate performance displacement assessment of these structural components. The second part discusses the accuracy of the investigated approaches for multi-span steel truss bridges through comparisons with nonlinear time history analysis. The results of the parametric analysis are used to propose recommendations for an appropriate DBA or pushover-based strategy for the deterministic performance assessment and fragility analysis with reference to the damage state of the supporting towers or bridge serviceability in terms of superstructure transverse deformation.

Formalising the R of Reduce in a Circular Economy Oriented Design Methodology for Pedestrian and Cycling Bridges

The construction industry consumes over 32% of the annually excavated natural resources worldwide. Additionally, it is responsible for 25% of the annually generated solid waste. To become a more sustainable industry, a circular economy is necessary: resources are kept in use as long as possible, aiming to reduce and recirculate natural resources. In this paper, the investigation focuses on pedestrian truss bridges of the types Warren and Howe. Many pedestrian bridges currently find themselves in their end-of-life phase and most commonly these bridges are demolished and rebuilt, thus needing a lot of new materials and energy. The aim is thus first and foremost to reduce the amount of necessary new materials. For this reason, a design tool will be created, using the software ‘Matlab’, in which truss bridges can be evaluated and compared in the conceptual design stage. The tool is based on the theory of morphological indicators: the volume indicator, displacement indicator, buckling indicator and first natural frequency indicator. These allow a designer to determine the most material efficient Warren or Howe truss bridge design with user-defined constraints concerning deflection, load frequency, buckling and overall dimension. Subsequently, the tool was tested and compared to calculations made in the finite element modelling software Diamonds. In total, 72 steel bridge structures were tested. From these it could be concluded that the manual calculations in Diamonds in general confirmed the results obtained with the automated design tool based on morphological indicators. As such, it allows a designer to converge more quickly towards the best performing structure, thus saving time, materials, and corresponding costs and energy.

Dynamic load testing of a modular truss bridge using military vehicles

Determination of appropriate load factors ensures bridge assessments completed using limit states design are applicable for all potential loading scenarios. Extremely limited research has been completed to determine accurate Dynamic Load Allowance (DLA) values for military vehicle loading of bridges, specifically independent values for tracked and wheeled vehicle types. An experimental testing program was used to assess the dynamic load effects caused by these vehicle categories by subjecting a bridge to loading from multiple different vehicle types at different speeds, while controlling deck surface condition. It was found that tracked vehicles generated approximately half the dynamic bridge response of wheeled vehicles. Using this knowledge, tracked vehicle DLA value recommendations relevant for this bridge are made for use in the North Atlantic Treaty Organization (NATO) Military Load Classification (MLC) system, and in the Canadian Highway Bridge Design Code (CHBDC) and American Association of State Highway and Transportation Officials (AASHTO) bridge code. Further research in this area could lead to strategic increases in tracked vehicle mobility.

Synchronized Assessment of Bridge Structural Damage and Moving Force via Truncated Load Shape Function

Moving load and structural damage assessment has always been a crucial topic in bridge health monitoring, as it helps analyze the daily operating status of bridges and provides fundamental information for bridge safety evaluation. However, most studies and research consider these issues as two separate problems. In practice, unknown moving loads and damage usually coexist and influence the bridge vibration synergically. This paper proposes an innovative synchronized assessment method that determines structural damages and moving forces simultaneously. The method firstly improves the virtual distortion method, which shifts the structural damage into external virtual forces and hence transforms the damage assessment as well as the moving force identification to a multi-force reconstruction problem. Secondly, a truncated load shape function (TLSF) technique is developed to solve the forces in the time domain. As the technique smoothens the pulse function via a limited number of TLSF, the singularity and dimension of the system matrix in the force reconstruction is largely reduced. A continuous beam and a three-dimensional truss bridge are simulated as examples. Case studies show that the method can effectively identify various speeds and numbers of moving loads, as well as different levels of structural damages. The calculation efficiency and robustness to white noise are also impressive.

Experimental study on bridge vibration test

Taking Chaihe bridge in Tieling City and Songhuajiang railway bridge on Binbei line as examples, the vibration test is carried out by using the environmental excitation method. By testing and comparing the first three typical vibration modes of the two bridges, and the experimental research shows that: A. compared with Concrete-Filled Steel Tubular Bridge, truss bridge has higher stiffness. B. The span and height of truss bridge can be higher and farther than that of Concrete-Filled Steel Tubular Bridge; C. Truss bridge is more convenient in testing, maintenance and health monitoring, and has good performance and stability.

Simple calculation method of remaining capacity for compressive members with uniform section loss in steel truss bridge

Simple calculation method of remaining capacity for compressive members with uniform section loss in steel truss bridge

Nonlinear Stress Analysis of Key Joints of Steel Truss Bridge

Steel truss bridges are widely used in bridge engineering for the advantages of good ability of spanning capacity, construction and light self-weight. Main trusses are the main stressed component of steel truss bridge. And the main truss are made of truss members connected by integral joints. So, the safety of integral joints are very important for normal operation of steel truss bridge. The superstructure of the continuous steel truss bridge with double decks was selected as the engineering example. The software, MIDAS/CIVIL is used to establish the full finite element model of the continuous steel truss bridge. Based on the results of the full bridge model, the 3D finite element model integral joint considering material nonlinearity was established by software Abaqus. The stress distribution of the integral joint under the unfavorable external force were analyzed and compared. The results showed that the most parts of the integral joint are in elastic stage, and the stress distribution is inhomogeneous. The stresses of integral joint are greater than that of truss members. Except for individual stress concentration areas, the stresses in the center area of the integral joint are greater than the stress at the edge. All in all, the safety of integral joints for the engineering example can be guaranteed.

Analytical fault tree and diagnostic aids for the preservation of historical steel truss bridges

Historical steel bridges represent an important construction typology integrating the constructive heritage of the past century that needs to be preserved. Exposure to fatigue phenomenon, aging, improper design or execution, extreme events, and other aggressive environmental agents can seriously compromise the conservation and performance of these structures as some recent catastrophic collapses have shown (Mississippi River bridge, Minneapolis, Minnesota 2007; Kinzua Bridge State Park, Pennsylvania 2003).In this context, the diagnostic of historical steel bridges becomes of basic importance to identify and implement maintenance, monitoring and conservation strategies. Fault Trees are useful tools for practitioners that provide a complete overview of possible failures. In the related literature, this instrument is mainly applied with approaches that are based on previous experience or failures detected in similar structures, and so the Fault Tree can only provide qualitative support.This paper proposes a new method to achieve an “Analytical” Bridge Fault Tree linking the technician’s experience and the numerical simulations of different fault scenarios. The latter are achieved by a numerical model able to consider fatigue failure and different concurring causes in the analysis (e.g., and aggressive phenomena, corrosion, defects, lack of maintenance). The proposed approach was applied to a historical railway steel truss bridge located in the East of Spain (Valencia Region) in order to show its applicability and potential.

Tracking of Stiffness Variation in Structural Members Using Input Error Function Observers

This study evaluates input error function observers for tracking of stiffness variation in real-time. The input error function is an Analytical Redundancy (AR)-based diagnosis method and necessitates a mathematical model of the system and system identification techniques. In practice, mathematical models used during numerical simulations differ from the actual status of the structure, and thus, accurate mathematical models are rarely available for reference. Noise is an unwanted signal in the input–output measurements but unavoidable in real-world applications (as in long span bridge trusses) and hard to imitate during numerical simulations. Simulation data from the truss system clearly indicates the effectiveness of the proposed structural damage detection method for estimating the severity of the damage. Optimization of the input error function can further automate the stiffness estimation in structural members and address critical aspects such as system uncertainties and the presence of noise in input–output measurements. Stiffness tracking in one of the planar truss members indicates the potential of optimization of the input error function for online structural health monitoring and implementing condition-based maintenance.

Damage detection of warren truss bridge using frequency change correlation

The detection of structural damage in any structure becomes the primary concern in failure analysis. Early detection of structural failure is crucial for preventing hazards and losses caused by structural failure. There are various approaches for detecting structural damage, and these approaches must be developed in large numbers for structural safety.The purpose of this study is to provide a simple and effective method for estimating the damage to a warren truss bridge utilizing frequency change correlation and the results of the modal analysis performed using SAP 2000 FEA software. The numerical results of the first five-mode shapes and frequencies of the Louisville bridge model were validated for modal analysis accuracy in SAP 2000. The primary variable in the modal analysis was the presence of six different sections of hollow mild steel pipe with an outer diameter of 10, 12, 14, 16, 18, and 20 mm and a 2 mm plate thickness. Three different locations for damage have been considered in the warren truss bridge. The first six modes' natural frequencies and modal participation factors were compared for undamaged and damaged warren truss bridges. The results indicate that as the diameter of warren truss bridge sections increases, the natural frequency and modal participation factors of the first six modes remain constant in the undamaged case but increase in the three-damage scenario. Additionally, there was a slight change in natural frequency and modal participation factor for three damage scenarios. As a result of increasing the natural frequency and modal participation factor for damage scenarios, the health of the warren truss bridge may be monitored, and appropriate measures adopted before it fails.

Safety evaluation of truss bridges using continuous Bayesian networks

Truss structures have been widely used in railway and highway bridges. However, it is difficult to evaluate the safety states of truss bridges due to a large number of members, high system redundancy, and insufficient monitoring data caused by limited sensors. Due to this, a new method based on continuous Bayesian Networks (BNs) is proposed to perform the safety evaluation on truss bridges, where the external loads and member stresses are assigned with two types of nodes in the BN. First, the BN topologies are established by combining the mechanical relationship of truss members to avoid the negative influence of redundant and missing edges in large-scale topology learning. Then, since the monitoring data in real-world civil structures are usually insufficient, a completed numerical sample set is adopted for parameter learning to obtain the conditional probability distributions. Subsequently, multiple BN models corresponding to different external load levels are established. A monitoring data-based matching approach is presented for model screening to find the optimal BN model. After that, the data from a few truss members are used to simulate the insufficient data in actual situations, and they are input into the optimal BN model to infer the external loads and the stresses of the remaining members. The inference ability using insufficient information well accords with the demand in engineering practice. Furthermore, two safety indices representing system states and failure probabilities are defined to evaluate the safety states of truss bridges. Finally, the feasibility of the proposed method has been successfully verified against both numerical and experimental truss bridge models.

Structural dominant failure modes searching method based on deep reinforcement learning

The dominant failure modes (DFMs) of a structural system are significant for structural analysis and failure probability estimation. However, existing failure modes (FMs) searching methods often face problems of combinatorial explosion. To address this issue, a deep reinforcement learning (DRL)-based method is proposed for DFMs searching, which transforms the probability-based failure component selection process into a sequential decision process. First, the failure stages and the selected failure components of a structural system are transformed to be the states and actions in the DRL. Second, a deep neural network (DNN) is established to observe the failure stages and select failure components. Finally, a new reward function is designed to guide the network to learn the failure component selection policy. The proposed method was tested through a roof truss structure and a truss bridge structure. It was demonstrated that the trained DNN could learn to observe the failure stages and select the most critical components in a completely unknown testing set. High accuracy of the identified DFMs can be achieved. In comparison with the calculation results of Monte Carlo Simulation (MCS) and β-unzipping method, this proposed method shows significant computational efficiency advantages with high accuracy in dealing with combinatorial explosion.

Interfacial failure of circular or tubular hybrid bonded joints: A theoretical description

In different industries, the bonding technique has gained several advances in recent years. However, due to the specificity of each industry, the bonded joints may present different configurations. For instance, in the case of metallic truss bridges, the use of Carbon Fibre Reinforced Polymers (CFRP) bonded on the steel surface members may require circular or even tubular transitions between these materials. Although the bonded transitions between a metal and a composite material have been deeply studied with flat surfaces the information on circular or tubular hybrid bonded joints is still scarce. Therefore, the present study aims to mitigate some of this lack of knowledge by proposing an analytical solution able to describe the interfacial debonding process between a circular or tubular bonded transition between two materials. The proposed model also aims to simulate the interfacial debonding of double butt (or stepped) lap joints. Under these circumstances, a bilinear local adhesive model is adopted which required the quantification of the elastic and the softened stiffnesses as well as the pure Mode II fracture energy. The Finite Element Method (FEM) is used for the validation of the proposed model. The behaviour of the adhesive joint between materials is numerically modelled through the Cohesive Zone Modelling (CZM) in which the same bilinear shape used in the analytical solutions is adopted. Different situations were analyzed thoroughly and the numerical simulations tracked very closely the analytical results obtained from the proposed closed-form solutions.

Investigating the redundancy of steel truss bridges composed of modular joints

The objective of this paper is to present a numerical investigation of the redundancy of steel truss bridges composed of novel modular joints when subjected to the sudden loss of diagonal members. The modular joint - a prefabricated steel nodal connector composed of flat web plate welded to flat and curved cold bent flange plates - represents a new approach to the construction of steel truss bridges in which the connector is a module that joins member that are standard rolled wide flange sections. A unique feature of this approach is that a moment-resisting connection is achieved in a truss topology by joining webs and flanges independently through bolted splice connections. This, in combination with orienting members in strong axis bending, provides the potential for the system to tolerate the loss of a diagonal member through load redistribution in flexure. The response of a 119-m (390-ft) simply supported vehicular bridge following the abrupt loss of a diagonal is numerically investigated considering three behaviors: (1) instantaneous dynamic behavior, focusing on the effect of the high-velocity stress wave, with its associated high strain rates and impact on fracture toughness particularly in the cold bent and welded portion of the modular joint, (2) short-term dynamic behavior of the structure, and (3) static behavior of the faulted structure. Results show that the modular joint is able to redistribute load after sudden member loss, demonstrating the redundancy of this new approach to modular construction.

Shielding and internode effects of truss bridge on the aerodynamic characteristics of high-speed train under crosswinds

Accurately simulating the aerodynamic characteristics is important to the safety and stability of high-speed train, especially when it operates under strong crosswinds. In recent, long span highway-railway bridge has been developed rapidly to enable the high-speed rail to cross wide rivers and valleys, where the truss bridges are usually served as the main girder type. This study aims to investigate the unique interference effects on the aerodynamic characteristics of the high-speed train caused by the truss bridge, i.e., the so-called shielding effect and internode effect. The shielding effect of the truss bridge on the mean aerodynamic coefficients is firstly quantified based on a moving train model test in wind tunnel. Combined with a 3-D computational fluid dynamic (CFD) model validated by the wind tunnel test, a series of numerical simulations are conducted to study the mechanism of internode effect, where the airflow field and pressure distributions around the train body and on the bridge surface are interpreted. The results reveal that the truss bridge has an obvious whole and local shielding effects, with the first effect introducing a remarkable decrease on the aerodynamic forces of trains at the entrance and the second effect leading to an intermittent excitation.

Damage Identification in Warren Truss Bridges by Two Different Time–Frequency Algorithms

Recently, a number of authors have been focusing on drive-by monitoring methods, exploiting sensors mounted on the vehicle rather than on the bridge to be monitored, with clear advantages in terms of cost and flexibility. This work aims at further exploring the feasibility and effectiveness of novel tools for indirect health monitoring of railway structures, by introducing a higher level of accuracy in damage modelling, achieve more close-to-reality results. A numerical study is carried out by means of a FE 3D model of a short span Warren truss bridge, simulating the dynamic interaction of the bridge/track/train structure. Two kinds of defects are simulated, the first one affecting the connection between the lower chord and the side diagonal member, the second one involving the joint between the cross-girder and the lower chord. Accelerations gathered from the train bogie in different working conditions and for different intensities of the damage level are analyzed through two time-frequency algorithms, namely Continuous Wavelet and Huang-Hilbert transforms, to evaluate their robustness to disturbing factors. Compared to previous studies, a complete 3D model of the rail vehicle, together with a 3D structural scheme of the bridge in place of the 2D equivalent scheme widely adopted in the literature, allow a more detailed and realistic representation of the effects of the bridge damage on the vehicle dynamics. Good numerical results are obtained from both the two algorithms in the case of the time-invariant track profile, whereas the Continuous Wavelet Transform is found to be more robust when a deterioration of track irregularity is simulated.