Computational aero-acoustics prediction method based on fast random particle mesh

Coupled with stochastic turbulent velocity generation model and linear Euler equation, a hybrid computational aero-acoustics prediction method, which can simulate the noise propagation in non-uniform flow, has been set up. The random particle mesh method was used in the stochastic turbulent velocity generation model to provide reliable sound sources for the acoustic propagation equation. The linear Euler equation was applied in modeling the sound propagation. Dispersion-Relation-Preserving (DRP) scheme in spatial discretion together with high-accuracy large-step explicit Runge-Kutta (HALE-RK) scheme in time advancement were implemented. The far-field uses the non-split Perfect-Match-Layer (PML) boundary. Firstly, Gaussian-pulse propagation model was chosen to verify space-time discrete scheme and far-field boundary of the linear Euler equation. Next, the spatial correlation of isotropic turbulence was used to verify the turbulent velocity generation model. Finally, slat noise of 30P30N airfoil was calculated with the proposed hybrid method. The results show that the power spectral density curve and the noise directivity at monitoring points were well consistent with the results in the reference literature. Numerical results demonstrate that the hybrid prediction method could effectively predict the aero-acoustics of 2D complex geometry.