Step-by-Step Numerical Prediction of Aerodynamic Noise Generated by High Speed Trains

In this paper, the unsteady flow around a high-speed train is numerically simulated by detached eddy simulation method (DES), and the far-field noise is predicted using the Ffowcs Williams-Hawkings (FW-H) acoustic model. The reliability of the numerical calculation is verified by wind tunnel experiments. The superposition relationship between the far-field radiated noise of the local aerodynamic noise sources of the high-speed train and the whole noise source is analyzed. Since the aerodynamic noise of high-speed trains is derived from its different components, a stepwise calculation method is proposed to predict the aerodynamic noise of high-speed trains. The results show that the local noise sources of high-speed trains and the whole noise source conform to the principle of sound source energy superposition. Using the head, middle and tail cars of the high-speed train as noise sources, different numerical models are established to obtain the far-field radiated noise of each aerodynamic noise source. The far-field total noise of high-speed trains is predicted using sound source superposition. A step-by-step calculation of each local aerodynamic noise source is used to obtain the superimposed value of the far-field noise. This is consistent with the far-field noise of the whole train model's aerodynamic noise. The averaged sound pressure level of the far-field longitudinal noise measurement points differs by 1.92 dBA. The step-by-step numerical prediction method of aerodynamic noise of high-speed trains can provide a reference for the numerical prediction of aerodynamic noise generated by long marshalling high-speed trains.

Automated summary

In this paper, the unsteady flow and far-field noise of a high-speed train are simulated and analyzed using numerical methods and acoustic models. The study proposes a step-by-step calculation method to predict the noise of high-speed trains and verifies the reliability of numerical calculations through experiments. The research results contribute to a better understanding of the generation mechanism and control methods of high-speed train noise.