• Steel and Composite Structures
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• v.37 no.3
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• pp.291-306
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• 2020

The noise from the elevated lines of rail transit has become a growing problem. This paper presents a new method for the rapid prediction of the structure-borne noise from steel or composite bridges, based on the receptance and Statistical Energy Analysis (SEA), which is essential to the study of the generation mechanism and the design of a low-noise bridge. First, the vertical track-bridge coupled vibration equations in the frequency domain are constructed by simplifying the rail and the bridge as an infinite Timoshenko beam and a finite Euler-Bernoulli beam respectively. Second, all wheel/rail forces acting upon the track are computed by taking a moving wheel-rail roughness spectrum as the excitation to the train-track-bridge system. The displacements of rail and bridge are obtained by substituting wheel/rail forces into the track-bridge coupled vibration equations, and all spring forces on the bridge are calculated by multiplying the stiffness by the deformation of each spring. Then, the input power to the bridge in the SEA model is derived from spring forces and the bridge receptance. The vibration response of the bridge is derived from the solution to the power balance equations of the bridge, and then the structure-borne noise from the bridge is obtained. Finally, a tri-span continuous steel-concrete composite bridge is taken as a numerical example, and the theoretical calculations in terms of the vibration and noise induced by a passing train agree well with the field measurements, verifying the method. The influence of various factors on wheel/rail and spring forces is investigated to simplify the train-track-bridge interaction calculation for predicting the vibration and noise from steel or composite bridges.

• Journal of the Korean Society for Railway
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• v.10 no.1 s.38
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• pp.22-28
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• 2007

During the passage of the train, the railway bridge undergoes vibration and noise. The noise of railway bridge can be occurred from various sources. The wheel-rail contact, noise from machinery parts, structural-borne noise, pantagraph noise and aerodynamic noise of the train work in combination. Running train is one of the most important factors 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. 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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.772-777
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• 2006

An acoustic finite element model of a bridge is developed to evaluate the noise generated by the traffic-induced vibration of the bridge. The dynamic response of a multi-girder bridge, modeled by a 3-dimensional frame element model, is analyzed with a 3-axle(8DOF) truck model and a 5-axle(l3DOF) semi-trailer. The flat plate element is used to analyze the acoustic pressure due to the fluid-structure interactions between the vibrating surface and contiguous acoustic fluid medium. The radiation fields of noise with a specified distribution of vibrating velocity and pressure on the structural surface are also computed using the Kirchhoff-Helmholtz integral. In an attempt to illustrate the influence of the structural vibration noise of a bridge to total noise level around the bridge, the random function is used to generate the vehicle noise source including the engine noise and the rolling noise interacting between the road and tire. Among the diverse parameters affecting the dynamic response of bridge, the vehicle velocity, the vehicle weight, the spatial distribution of the road surface roughness, the stiffness degradation of the bridge and the variation of the air temperature changing the air density are found to be the main factors that increase the level of vibration noise. Consequently, The amplification rate of noise increases with the traveling speed and the vehicle weight.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.45-51
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• 2002

An acoustic finite element model of a bridge is developed to evaluate the noise generated by the traffic-induced vibration of the bridge. The dynamic response of a multi-girder bridge, modeled by a 3-dimensional frame element model, is analyzed with a 3-axle 8 DOFs truck model and a 5-axle 13 DOFs semi-trailer. The flat plate element is used to analyze the acoustic pressure due to the fluid-structure interactions between the vibrating surface and contiguous acoustic fluid medium. The radiation fields of noise with a specified distribution of vibrating velocity and pressure on the structural surface are also computed using the Kirchhoff-Helmholtz integral. Although the noise produced by the bridge vibration is not serious in itself, which is below the audible frequency range, it should be considered as an interaction problem between vehicle noise and bridge vibration noise in order to evaluate the traffic noise around the bridge.

• The Journal of the Acoustical Society of Korea
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• v.34 no.1
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• pp.52-59
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• 2015

In the conventional model for the prediction of the railway environmental noise, one used an empirical formula of the total noise level at specific distances. Only a function of the distance to the source was also used to calculate the noise level near the railway bridges. However, the noise varies depending on the position of the receiver as well as the distance from the source especially at concrete bridges. In this paper, a noise propagation model in the railway concrete bridge was derived by considering the diffraction at the bridge deck and the ground effect and applying the ISO 9613-2 noise propagation model. We compared the predicted and measured values of environmental noise at a high-speed railway bridge, and it was confirmed that this prediction model gives relatively small errors.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.483-483
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• 2007

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.862-867
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• 2000

The auxiliary engine exhaust noise in ships are directly transmitted to bridge wing with the only distance attenuation. It is not so practical that no special treatment can be applied between exhaust pipe and bridge wing in order to reduce the transmission of the exhaust noise. In general, a silencer is fitted to reduce the exhaust noise and also noise of bridge wing. The silencer should be properly designed under the consideration of the frequency component of the exhaust noise and the required insertion loss. In this paper, the frequency component of exhaust noise of various engines are compared and a design and a design and installation of silencer to reduce low frequency is introduced.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.731-736
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• 2004

The exhaust noise of auxiliary engine in ships is directly transmitted to bridge wing with only distance attenuation. It is not easy to find out practical treatment to be applied between exhaust pipe and bridge wing to reduce the transmission of the exhaust noise. In general, therefore, a silencer is fitted to reduce the exhaust noise and correspondingly noise of bridge wing. The silencer should be properly designed under the consideration of the frequency component of the exhaust noise and the required performance such as noise reduction or insertion loss. In general, the gas inside the exhaust pipe flows with high temperature and speed and thus onboard test condition is more adverse than the standard atmospheric condition. In this study, the test method to evaluate silencer performance using a probe microphone is introduced.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.1
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• pp.94-101
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• 2019

Most of the existing rail structures have undergone a lot of aging since a considerable period of time has passed from completion. In particular, among existing railway bridges, many of the plate girder bridges are older bridges that have lived 40 to 60 years or more. Since the treadmill is directly connected to the girder without the ballast, the running load of the vehicle is directly transmitted to the bridge. Therefore, the shock and noise applied to the bridge are larger than those of the ballast bridge, and the dynamic shock and vibration are also relatively large. Therefore, it is very urgent to develop appropriate maintenance, repair and reinforcement technology for existing steel plate bridge. In this study, the authors introduced the characteristics of embedded rail (ERS) developed for improving the performance of the existing plate girder bridge and the techniques solving the vibration and noise problems. In order to evaluate the vibration and noise reduction performance of ERS, a non-ballast plate girder bridge with 5m length of sleepers installed and a plate girder bridge with ERS were fabricated. And, then, the vibration response generated under the same excitation condition was measured and analyzed. Also, the radiated noise analysis was performed using the vibration response data obtained from the experiment as the input data of the acoustic analysis model. As a result of experiments and analyses, it was confirmed that the plate girder bridge's vibration using ERS was reduced by 15.0~18.8dB and the average noise was reduced by 7.7dB(A) more than the non-ballast bridge.

• Structural Engineering and Mechanics
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• v.57 no.1
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• pp.21-43
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• 2016

A conditional probability based approach known as Particle Filter Method (PFM) is a powerful tool for system parameter identification. In this paper, PFM has been applied to identify the vehicle parameters based on response statistics of the bridge. The flexibility of vehicle model has been considered in the formulation of bridge-vehicle interaction dynamics. The random unevenness of bridge has been idealized as non homogeneous random process in space. The simulated response has been contaminated with artificial noise to reflect the field condition. The performance of the identification system has been examined for various measurement location, vehicle velocity, bridge surface roughness factor, noise level and assumption of prior probability density. Identified vehicle parameters are found reasonably accurate and reconstructed interactive force time history with identified parameters closely matches with the simulated results. The study also reveals that crude assumption of prior probability density function does not end up with an incorrect estimate of parameters except requiring longer time for the iterative process to converge.