Modelling the interior sound field of a railway vehicle using statistical energy analysis

Abstract

The sound field in train compartments, treated as a series of connected air cavities, is modelled using statistical energy analysis, SEA. For the case under study, with five cavities in series and the source in the second cavity, a closed--form solution is obtained. An adjusted SEA model is used to predict the rate of spatial decay within a cavity. The SEA model is validated using results from a ray tracing method and from scale model measurements. For the octave bands 500-4000 Hz, good agreement is shown between the results from measurements, the ray tracing and the SEA model, for the two saloons closest to the source cavity (a vestibule). The SEA model was shown to slightly underestimate the rate of spatial decay within a cavity. It is concluded that a reasonable cause is the additional diffusion due to the seating.

Prediction of noise inside an acoustic cavity of elongated shape using statistical energy analyses with spatial decay consideration

“…In the work of Forssén et al [12], a decay relation is introduced to the SEA subsystem to get the spatial variation information. The relation, derived by Redmore [13], is expressed as…”

“…The L p is also predicted, respectively, by the current model using Eq. (12) and the Forssén model using Eq. (13), and is depicted in the figures.…”

“…It is found, in room acoustics, that the acoustic pressure in a room that has one dimension dominant over other dimensions exhibits a certain decay pattern, starting from the point where the source is placed [11]. Forssén et al [12] made use of this information and introduced a constant decay relation, derived by Redmore [13] for a corridor, to the standard SEA model to predict the acoustic pressure level in a railway train. Validation on a scale model showed that the modified SEA model could be able to visualize the acoustic variation across the train compartments.…”

Acoustic Metamaterials: A Potential for Cabin Noise Control in Automobiles and Armored Vehicles

“…Marzbanrad and Beyg [2012] attempted likewise on another commercial car albeit they lacked validation of their numerical results. SEA is also applied for similar intention on ship [Pang et al, 2014] and trains [Forssen et al, 2012;Zhao et al, 2013]. Interest in improving the methodology of SEA is still ongoing; evident from recent literature [Putra et al, 2015].…”

Automatic subsystem identification in statistical energy analysis

“…However, SEA may also be a powerful tool for dealing with vibroacoustic problems with complex shapes and non-conventional configurations. Examples of this kind of problems might be found, for instance, in the automotive [4][5][6], railway [7,8] or aerospace [9] industries, or even in some new architectonic designs and buildings [10]. In these cases the domain subdivision is not so clear and often the decomposition is done following material or geometrical criteria, see Chen et al [11] or Forssén et al [7].…”