No abstract
The computational method of interior aerodynamic noise of the high-speed train was proposed based on the large eddy simulation (LES) and statistical energy analysis (SEA). Based on the SEA theory, the computation model of the interior aerodynamic noise was established, which included 422 car-body structural subsystems and 170 interior acoustic cavity subsystems. The fluctuating pressure spectrums on the car-body structural subsystems were obtained by the LES, and then the interior aerodynamic noise of the high-speed train was computed and analyzed. Computational results show that the sound pressure level of the drive's cab cavity and passenger compartment cavity has low frequency characteristics for the linerweighted sound pressure level and has broadband characteristics for the A-weighted sound pressure level. For the A-weighted sound pressure level, the sound energy of the drive's cab cavity is mainly distributed between 100~2000Hz, the sound energy of the passenger compartment cavity is mainly distributed between 50~2000Hz. The sound pressure level of the interior aerodynamic noise can be reduced for every frequency by improving interior sound absorption performance and increasing the damping of the car-body plate.
The adjoint optimization method has been well developed and applied in the field of aviation. In this paper, the adjoint method is used to optimize the head shape of a simplified high-speed train, and the feasibility of this method in aerodynamic shape optimization of high speed-trains is discussed. The optimization results show that the aerodynamic drag coefficient of the optimized train is 0.9% lower than that of the original one, while the main feature of the head shape is not changed significantly. The adjoint method has important engineering application value in the aerodynamic optimization of high-speed trains.
The one-dimensional flow model is an effective method to study the train tunnel pressure wave problem. Critical aerodynamic coefficients (pressure loss coefficient of the streamlined head, friction coefficient of the train body, pressure loss coefficient of the streamlined tail) are the main factors that affect the computational accuracy of the one-dimensional flow model. In the present paper, the computational formulas of the pressure loss coefficient of the streamlined head, friction coefficient of the train body, pressure loss coefficient of the streamlined tail are derived, which show the relationship among critical aerodynamic coefficients and typical pressure increments. Typical pressure increments are computed by the three-dimensional flow model. Computational results show that, for the high-speed train studied in the present paper, the pressure loss coefficient of the streamlined head is 0.0149, the friction coefficient of the train body is 0.0040, and the pressure loss coefficient of the streamlined tail is 0.0151. The computational difference between the onedimensional flow model and three-dimensional flow model is no more than 5%, which verifies the accuracy of critical aerodynamic coefficients.
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