The complexity of aroom model affects to the computational resources required to model its acoustics by means of geometrical acoustics modeling methods. Thus, am ethod for reducing the geometry of the room models is presented for static room geometries. The topology of the model is simplified in aprocess where the model is first decomposed into avolumetric structure. The surface is reconstructed by utilizing this structure, and subsequently simplified by merging coplanar regions. The results of the method are verified by extracting room acoustical attributes from the original and reduced models with the ODEON room acoustics prediction software. It is shown that the most important acoustic properties have been preserved, even with relatively high reduction rates.
Most of today's room acoustics programs make use of scattering coefficients which are used in order to describe surface scattering (roughness of material) and scattering of reflected sound caused by limited surface size (diffraction). A method which combines scattering caused by diffraction due to typical surface dimensions, angle of incidence and incident path length with surface scattering is presented. Each of the two scattering effects is modeled as frequency dependent functions. The benefits are two-fold:• Separating the user specified surface scattering coefficient from the room geometry makes it easier for the user to make good gestimates of the coefficients that will be in better agreement with the ones that can be measured. In many cases a scattering coefficient of say 5% for all smooth surfaces may be sufficient.• Scattering due to diffraction is distance and angle dependent and as such it is not known before the source and receiver are defined, and the actual 'ray-tracing' or image source detection takes place. An example on this is that a desktop will provide a strong specular component to its user whereas it will provide scattered sound at remote distances.
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