• Wind and Structures
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• v.23 no.3
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• pp.171-189
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• 2016

An adjustable, louver-type wind barrier was introduced in this study for improving the running safety and ride comfort of train on the bridge under the undesirable wind environment. The aerodynamic characteristics of both train and bridge due to this novel wind barrier was systematically investigated based on the wind tunnel tests. It is suggested that rotation angles of the adjustable blade of the louver-type wind barrier should be controlled within $90^{\circ}$ to achieve an effective solution in terms of the overall aerodynamic performance of the train. Compared to the traditional grid-type wind barrier, the louver-type wind barrier generally presents better aerodynamic performance. Specifically, the larger decrease of the lift force and overturn moment of the train and the smaller increase of the drag force and torsional moment of the bridge resulting from the louver-type wind barrier were highlighted. Finally, the computational fluid dynamics (CFD) technique was applied to explore the underlying mechanism of aerodynamic control using the proposed wind barrier.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.522-529
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• 2006

Running train is one of the most main factor for railway bridge vibration. The repeated forces with equidistant axles cause the magnification of dynamic responses which relates with maintenance of the track structure and structure-borne noises. The noise problem is one of the most important issues in services of light rail transit system which usually passes through towns. The noise of railway bridges can be divided into the noise from track-vehicle system and structure-borne noises. In the present study, The vibration and noise of the LRT bridge will be investigated with utilizing dynamics responses from moving train as input data for noise analysis.

• Smart Structures and Systems
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• v.20 no.5
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• pp.549-562
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• 2017

The US railroad network carries 40% of the nation's total freight. Railroad bridges are the most critical part of the network infrastructure and, therefore, must be properly maintained for the operational safety. Railroad managers inspect bridges by measuring displacements under train crossing events to assess their structural condition and prioritize bridge management and safety decisions accordingly. The displacement of a railroad bridge under train crossings is one parameter of interest to railroad bridge owners, as it quantifies a bridge's ability to perform safely and addresses its serviceability. Railroad bridges with poor track conditions will have amplified displacements under heavy loads due to impacts between the wheels and rail joints. Under these circumstances, vehicle-track-bridge interactions could cause excessive bridge displacements, and hence, unsafe train crossings. If displacements during train crossings could be measured objectively, owners could repair or replace less safe bridges first. However, data on bridge displacements is difficult to collect in the field as a fixed point of reference is required for measurement. Accelerations can be used to estimate dynamic displacements, but to date, the pseudo-static displacements cannot be measured using reference-free sensors. This study proposes a method to estimate total transverse displacements of a railroad bridge under live train loads using acceleration and tilt data at the top of the exterior pile bent of a standard timber trestle, where train derailment due to excessive lateral movement is the main concern. Researchers used real bridge transverse displacement data under train traffic from varying bridge serviceability levels. This study explores the design of a new bridge deck-pier experimental model that simulates the vibrations of railroad bridges under traffic using a shake table for the input of train crossing data collected from the field into a laboratory model of a standard timber railroad pile bent. Reference-free sensors measured both the inclination angle and accelerations of the pile cap. Various readings are used to estimate the total displacements of the bridge using data filtering. The estimated displacements are then compared to the true responses of the model measured with displacement sensors. An average peak error of 10% and a root mean square error average of 5% resulted, concluding that this method can cost-effectively measure the total displacement of railroad bridges without a fixed reference.

• Wind and Structures
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• v.29 no.6
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• pp.417-430
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• 2019

To study the wake influence of an upstream bridge on the wind-resistance performance of a downstream bridge, two adjacent long-span cable-stayed bridges are taken as examples. Based on wind tunnel tests, the static aerodynamic coefficients and the dynamic response of the downstream bridge are measured in the wake of the upstream one. Considering different horizontal and vertical distances, the flutter derivatives of the downstream bridge at different angles of attack are extracted by Computational Fluid Dynamics (CFD) simulations and discussed, and the change in critical flutter state is further studied. The results show that a train passing through the downstream bridge could significantly increase the lift coefficient of the bridge which has the same direction with the gravity of the train, leading to possible vertical deformation and vibration. In the wake of the upstream bridge, the change in lift coefficient of the downstream bridge is reduced, but the dynamic response seems to be strong. The effect of aerodynamic interference on flutter stability is related to the horizontal and vertical distances between the two adjacent bridges as well as the attack angle of incoming flow. At large angles of attack, the aerodynamic condition around the downstream girder which may drive the bridge to torsional flutter instability is weakened by the wake of the upstream bridge, and the critical flutter wind speed increases at this situation.

• Wind and Structures
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• v.36 no.6
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• pp.423-434
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• 2023

Aerodynamic force coefficients are generally obtained from traditional wind tunnel tests or computational fluid dynamics (CFD). Unfortunately, the techniques mentioned above can sometimes be cumbersome because of the cost involved, such as the computational cost and the use of heavy equipment, to name only two examples. This study proposed to build a deep neural network model to predict the aerodynamic force coefficients based on data collected from CFD simulations to overcome these drawbacks. Therefore, a series of CFD simulations were conducted using different geometric parameters to obtain the aerodynamic force coefficients, validated with wind tunnel tests. The results obtained from CFD simulations were used to create a dataset to train a multilayer perceptron artificial neural network (ANN) model. The models were obtained using three optimization algorithms: scaled conjugate gradient (SCG), Bayesian regularization (BR), and Levenberg-Marquardt algorithms (LM). Furthermore, the performance of each neural network was verified using two performance metrics, including the mean square error and the R-squared coefficient of determination. Finally, the ANN model proved to be highly accurate in predicting the force coefficients of similar bridge sections, thus circumventing the computational burden associated with CFD simulation and the cost of traditional wind tunnel tests.

• Advances in Computational Design
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• v.4 no.1
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• pp.1-13
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• 2019

Recent generations of smartphones offer accelerometer sensors as a standard feature. While this has led to the development of a number of related applications (apps), there has been no study on their comparative or individual performance against a benchmark. This paper investigates the comparative performance of a number of smartphone accelerometer apps amongst themselves and to a calibrated benchmark accelerometer. A total of 12 apps were selected for testing out of 90 following an initial review. The selected apps were subjected to sinusoidal vibration testing of varying frequency and the response of each compared against the calibrated baseline accelerometer. The performance of apps was quantified using analysis of variance (ANOVA) and test of significance was carried out. The apps were then compared for a realistic dynamic scenario of measuring the acceleration response of a bridge due to the passage of a French Train $\grave{a}$ Grande Vitesse (TGV) in a laboratory environment.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.176-184
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• 2000

Recently, it becomes a very important issue to consider the mechanical systems such as high-speed vehicle and railway train moving on a flexible beam structure. Using general approach proposed in the first part of this paper, it tis possible to predict planar motion of constrained mechanical system and elastic structure with various kinds of foundation supporting condition. Combined differential-algebraic equations of motion derived from both multibody dynamics theory and Finite Element Method can be analyzed numerically using generalized coordinate partitioning algorithm. To verify the validity of this approach, results from simply supported elastic beam subjected to a moving load are compared with exact solution from a reference. Finally, parameter study is conducted for a moving vehicle model on a simply supported 3-span bridge.

• Structural Engineering and Mechanics
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• v.82 no.1
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• pp.31-40
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• 2022

In structural engineering, the material properties of the structures such as elastic modulus, shear modulus, density, and size may not be deterministic and may vary at different locations. The dynamic response analysis of such structures may need to consider these properties as stochastic. This paper introduces a stochastic finite element method (SFEM) approach to analyze moving loads problems. Firstly, Karhunen-Loéve expansion (KLE) is applied for expressing the stochastic field of material properties. Then the mathematical expression of the random field is substituted into the finite element model to formulate the corresponding random matrix. Finally, the statistical moment of the dynamic response is calculated by the point estimation method (PEM). The accuracy and efficiency of the dynamic response obtained from the KLE-PEM are demonstrated by the example of a moving load passing through a simply supported Euler-Bernoulli beam, in which the material properties (including elastic modulus and density) are considered as random fields. The results from the KLE-PEM are compared with those from the Monte Carlo simulation. The results demonstrate that the proposed method of KLE-PEM has high accuracy and efficiency. By using the proposed SFEM, the random vertical deflection of a high-speed railway (HSR) bridge is analyzed by considering the random fields of material properties under the moving load of a train.

• Advances in Computational Design
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• v.2 no.4
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• pp.257-271
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• 2017

There are many plain concrete arch bridges in Iran that have been used as railway bridges for more than seventy years. Owe to the fact that these bridges have not been designed seismically, and even may be loaded under high-speed trains, evaluation of fundamental frequencies of the bridges against earthquake and high-speed train vibrations is necessary for considering dynamics effects. To evaluate complex behavior of these bridges, results of field tests are useful. Since it is not possible to perform field tests for all arch bridges, these structures should be simulated correctly by computers for structural assessment. Several parameters are employed to describe the bridges, such as number of spans, length of spans, geometrical and material properties. In this study, results of field tests are used for modal analysis and adapted for 64 three dimensional finite element models with various physical parameters. Computer simulations show length of spans has important effect on fundamental frequencies of plain concrete arch bridge and modal deformations of bridges is in longitudinal and transverse directions. Also, these results demonstrate that fundamental frequencies of bridges decrease after increasing span length and number of spans. Plus, some relations based in the number of spans (n) and span length (l) are proposed for calculation of fundamental frequencies of plain concrete arch bridge.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.715-720
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• 2002

The dynamic load effects, generated by moving trains, are transferred to the railway bridges through tracks. The dynamic load effects may vary due to the dynamic characteristics of the applied vehicle loads and the railway bridges including the track system. However, the track models have been neglected or simplified by spring elements in the most studies since it is quite complicated to consider the track systems in the dynamic analysis models of railway bridges. In this study track system on railway bridges are modeled using a three-dimensional discrete-support model that can simulate the load carrying behavior of tracks. A 40m simply supported prestressed concrete box-girder system adopted for high-speed railway bridges are modeled for simulation works. The train models are composed of 20 cars for KTX. The dynamic response of railway bridges are found to be affected depending on whether the track model is considered for not. The influencing rate depends on the traveling speed and different wheel-axle distance. The dynamic bridge response decreases remarkably by the track systems around the resonant frequency. Therefore, the resonance effect can be reduced by modifying the track properties in the railway bridge, especially for KTX trains.