A framework to predict the airborne noise inside railway vehicles with application to rolling noise

A framework is described for predicting the airborne noise inside railway vehicles which applied to rolling sources. Statistical energy analysis (SEA) used predict interior by subdividing train cabin into several subsystems. The dissipation loss factors are obtained from measured reverberation time in cabin. power input SEA model external sources multiplying incident sound on surfaces with transmission coefficients of floor and sidewalls. calculated using an equivalent source wheels track together region below floor. sides a waveguide boundary element (2.5D BE) method. procedure Spanish metro vehicle running open field main source. verified measurements pressure beneath carriage, sidewalls vehicle. sensitivity results changes absorption also studied, including effect passengers.