A framework to predict the airborne noise inside railway vehicles with application to rolling noise

2021 ◽  
Vol 179 ◽  
pp. 108064
Author(s):  
Hui Li ◽  
David Thompson ◽  
Giacomo Squicciarini ◽  
Xiaowan Liu ◽  
Martin Rissmann ◽  
...  
Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3957
Author(s):  
Krzysztof Polak ◽  
Jarosław Korzeb

In this work, the problematic identification of the main sources of noise occurring from the exploitation of railway vehicles moving at a speed of 200 km/h were analyzed. Within the conducted experimental research, the testing fields were appointed, measurement apparatus selected, and a methodology for conducting measurements was defined, including the assessment of noise on a curve and straight track for electric multiple units of the so-called Pendolino, an Alstom type ETR610 series ED25 train. The measurements were made using a microphone camera Bionic S-112 at a distance of 22 m from the track axis. As a result of the conducted experimental research, it was indicated that the noise resulting from vibrations arising at the wheel-rail contact (rolling noise) was the dominant source of sound.


2007 ◽  
Vol 35 (3) ◽  
pp. 165-182 ◽  
Author(s):  
Maik Brinkmeier ◽  
Udo Nackenhorst ◽  
Heiner Volk

Abstract The sound radiating from rolling tires is the most important source of traffic noise in urban regions. In this contribution a detailed finite element approach for the dynamics of tire/road systems is presented with emphasis on rolling noise prediction. The analysis is split into sequential steps, namely, the nonlinear analysis of the stationary rolling problem within an arbitrary Lagrangian Eulerian framework, and a subsequent analysis of the transient dynamic response due to the excitation caused by road surface roughness. Here, a modal superposition approach is employed using complex eigenvalue analysis. Finally, the sound radiation analysis of the rolling tire/road system is performed.


Author(s):  
Shuiwen Shen ◽  
T X Mei ◽  
R. M. Goodall ◽  
J. Pearson ◽  
G. Himmelstein

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