Cavity noise reduction of a high-speed train pantograph through jet parameter optimization

Abstract

The effect of aerodynamic noise from high-speed trains on residents living near railway lines is a critical issue. The pantograph cavity is considered to be a major source of aerodynamic noise. To address this problem, this study proposes the application of jetting at the leading edge of the cavity, directly targeting noise reduction at its source. The large eddy simulation approach is used for flow calculations, and the Ffowcs Williams and Hawkings aeroacoustic analogy is adopted for far-field acoustic predictions. Orthogonal designs and the backpropagation algorithm optimized by the genetic algorithm (BP-GA) is used to explore the effects of jetting factors on noise and identify the optimal parameters. Orthogonal design analysis shows that the most influential among the factors is jet orifice diameter, followed by jet velocity and jet angle. The use of the BP-GA algorithm for optimization reveals that the optimal jet parameters are jet velocity of 118.28 m/s, jet angle of 3.17°, and jet orifice diameter of 76.74 mm. The algorithm predicts a minimum noise level of 91.04 dB, which is close to the simulated noise level of 90.74 dB. The jetting process achieves a maximum noise reduction of 4 dB. Results demonstrate that the proposed method for cavity leading edge jetting effectively reduces turbulent kinetic energy and horseshoe-shaped vortices in the cavity, leading to noise reduction. This method also minimizes the effects of aerodynamic noise on distant areas, such as waiting areas and residential buildings. This work provides a theoretical basis for increasing high-speed train speeds.