Final Thesis

Sound path algorithm with high er order reflection and diffraction components for the auralization of urban environments

Key Info

Basic Information

Professorship:
TA
Status:
abgeschlossen
Research Area:
Akustische Virtuelle Realitšt

Contact

Master Thesis of Erraji, Armin

Noise from trafik, industry and neighborhood is a prominent feature in urban environments. Surrounding buildings as well as streets and lawns are influencing the acoustic transmission of sound sources. In these environments, propagated sound mainly reaches sensit ive receiver points through reflections and diffractions. Numerical methods can be applied to simulate the propagation of sound waves. However, due to their high complexity, calculation times are usually exceeding the requirements for real-time auralization. Therefore, geometrical acoustics has become the de-facto standard to computationally predict the acoustic behavior in interior spaces. To determine the transmission between sour ce and receiver, sound particles are calculated that follow the wave front normal, instead of actual waves. As a consequence, the complexity is drastically reduced and transmission filters for auralization can be rapidly estimated using image source and ray tracing methods. In contrast to interior spaces, boundaries are missing in urban environments and urban sound cannot be treated in a confined area. Hence, the most significant paths often require multiple combinations of specular reflections at surface boundaries and diffractions around edges. Because stochastic approaches require non-diverging propagation paths, the reliable determination of these combined components is not trivial and requires new algorithms. In this thesis, asound path algorithm for the determination of high er order reflection and diffraction components is constructed and implemented. A deterministic brute-force method considers all combinations of possible paths to simulate reflections and diffractions. Due to the exponential complexity, a straight-forward implementation suffers from significant memory consumption and violates acceptable run-times even for simple scenarios. Therefore, smart optirnization approaches are proposed. They accelerate the determination of the propagation paths. A further approach is introduced that reduces the total number of propagation paths based on perceptual considerations. They accelerate simulation calculations and reduce demands for the DSP network required for auralization. The final algorithm is able to calculate sound paths with a sufficiently small run-time and is thus applicable for the auralization of common urban environments up to real-time.