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Simulation of Sound Diffusion Patterns of Fractal-Based Surface Profiles (2017)

article⁄Simulation of Sound Diffusion Patterns of Fractal-Based Surface Profiles (2017)
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abstract⁄Acoustical design is one of the most challenging aspects of architecture. A complex system of competing influences e.g., space geometry, size, proportion, material properties, surface detail,etc. contribute to shaping the quality of the auditory experience. In particular, architectural surfaces affect the way that sound reflections propagate through space. By diffusing the reflectedsound energy, surface designs can promote a more homogeneous auditory atmosphere by mitigating sharp and focused reflections. One of the challenges with designing an effective diffuser isthe need to respond to a wide band of sound wavelengths, which requires the surface profile to precisely encode a range of detail sizes, depths and angles. Most of the available sound diffusersare designed to respond to a narrow band of frequencies. In this context, fractalbased surface designs can provide a unique opportunity for mitigating such limitations. A key principle of fractalgeometry is its multilevel hierarchical order, which enables the same pattern to occur at different scales. This characteristic makes it a potential candidate for diffusing a wider band of sound wavelengths. However, predicting the reflection patterns of complicated fractalbased surface designs can be challenging using available acoustical software. These tools are often costly, complicated and are not designed for predicting early sound propagation paths. This research argues that writing customized algorithms provides a valuable, free and efficient alternative for addressing targeted acoustical design problems. The paper presents a methodology for designing and testing a customized algorithm for predicting sound diffusion patterns of fractalbased surfaces. Both quantitative and qualitative approaches were used to develop the code and evaluate the results.
keywords⁄design methodsinformation processingsimulation-optimizationdata visualization2017
Year 2017
Authors Ajlouni, Rima.
Issue ACADIA 2017: DISCIPLINES & DISRUPTION
Pages 52-61
Library link N/A
Entry filename simulation-sound-diffusion-patterns-fractal-based