Numerical method for micro-pressure wave noise prediction based on turbulence model evaluation and time window optimization
Wen-feng Luo , Hong-lin Wang , Hai-quan Bi , Wei-ping Ding
Journal of Central South University ›› : 1 -18.
The micro-pressure waves (MPWs) generated by a high-speed train entering a tunnel are a significant noise source affecting the acoustic environment near tunnel exits. Accurate prediction of MPW noise strongly depends on the selection of turbulence models and the treatment of transient impulsive sources. In this study, the generation of MPWs induced by a high-speed metro train was numerically simulated using delayed detached eddy simulation (DDES), based on the k-epsilon (k-ε), Shear stress transport k-omega (SST k-ω), Spalart-Allmaras (S-A) turbulence models, and large eddy simulation (LES). The comparison indicates that the DDES (SST k-ω) model achieves an appropriate balance between computational accuracy and efficiency, accurately reproducing the waveform and pressure gradient characteristics of MPWs. Furthermore, based on these results, the far-field radiation from MPW noise was computed using the acoustic finite element method (FEM). In the MPW noise, dipole noise dominated, with its energy concentrated below 20 Hz and a peak frequency of 4 Hz. An optimal time window method was also proposed, encompassing 95% of the total MPW energy. This criterion effectively minimizes acoustic energy loss caused by overly short windows. It avoids waveform smoothing caused by excessively long windows, thereby improving the accuracy of MPW noise prediction. Finally, the time window method was verified using on-site test data. The findings offer practical guidance for accurately predicting and effectively controlling MPW noise in the rail transit system.
tunnel portal / micro-pressure wave / turbulence models / micro-pressure wave noise / time window optimization
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Central South University
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