The pseudospectral time-domain method (PSTD) provides an efficient way to solve the linear acoustics equations. With regards to acoustic modeling and auralization, source directivity as well as head-related directivity have a clear influence on the perceived sound field and have to be included in computations. In this paper directive sources are implemented in the time-domain method PSTD. First, a given frequency dependent source directivity is decomposed onto spherical harmonic functions. The directive source is then implemented through spatial distributions in PSTD that relate to the spherical harmonic functions, and time-dependent functions are assigned to the spatial distributions in order to obtain the frequency content of the directivity. Since any directivity function can be expressed as a summation of series of spherical harmonics, the approach can be used to model any type of directive source. For the evaluation of the method, a directivity function was designed analytically and then modeled in PSTD. Octave band analysis was performed and results show a good agreement between the analytical and simulated directivity. A distance related error was observed. However, for distances above 17.5 grid cells from the source center the average error was small (<0.9 dB) at all octave-bands.

No abstract

Car noise is the main environmental noise source in the urban environment. In this paper, a method for auralization of a car pass-by in a street from using a wave-based acoustic prediction method is explored. For the transfer paths between sound source locations and a listener, binaural impulse responses are computed with the pseudospectral time-domain method for various source locations. A dry synthesized car signal is convolved with the binaural impulse responses of the different locations in the street and cross-fade windows are used in order to make the transition between the source positions smooth and continuous. The auralizations are performed for the simplified scenarios where buildings are absent, and for an environment where a long building block is located behind the car. A subjective evaluation was carried out in order to detect the maximum spacing between the discrete source positions that still can produce a perceived continuous car pass-by auralization.

To reduce noise exposure along railway lines various combinations of noise mitigation measures can be considered. However, predicting and assessing their effects is non-trivial and the potential need for multiple measures is difficult to communicate to stakeholders. Auralisation is a promising tool that can help to support communication and decision-making, and enable psychoacoustic evaluations. This paper presents developments of a physics-based auralisation model for train pass-bys that allows various mitigation measures to be included. The work is conducted within the European research project SILVARSTAR. The proposed model includes contribution from rolling noise, impact noise, traction, auxiliary systems, and aerodynamic noise. It is physically based and allows a direct assessment of pass-by parameters such as speed, roughness, wheel flats and track design. Based on the TWINS model, five structural transfer paths for rolling noise are considered to integrate mitigation measures such as wheel and rail dampers. Shielding by noise barriers is simulated with analytical models. Reflection at different ground types is considered and can account for track embankments. The results can be coupled to an immersive Virtual Reality environment, by first panning the synthesised sounds to a small virtual speaker array and subsequently dynamic binaural rendering for headphones.

No abstract