Community Noise Prediction of Digital High Speed Train Using LBM

Abstract

CFD/CAA simulations on a non-confidential geometry of a high speed train are performed and used to estimate the flow-induced noise contribution radiated to the far-field. The approach consists of a Lattice Boltzmann Method (LBM) for the calculation of the flowfield around a virtual high speed train providing transient inputs to an acoustic analogy solver based on the Ffowcs Williams and Hawkings (FW-H) equation. The far-field noise is then calculated, providing information which represents a first step toward digital certification. The numerical method is applied to the main flow-induced sources of noise, i.e. the pantograph, all bogies and the inter-coach gaps, to derive acoustic power levels as well as by-pass noise at specific far-field locations. The near-field flow is analyzed and the far-field noise spectra are provided for each source. The dependency of the results with the resolution, and the effect of a symmetry plane used to reduce the calculation size and time by a factor of two, are also investigated. Noise levels obtained directly from the CFD/CAA simulations are also compared to the FW-H predictions at a location within the simulation domain.