Simplified Architectural Models and Affected Acoustic Parameters: Creation of a method to simplify architectural models and the effects of the simplified models on various room acoustic parameters

Abstract

For acousticians to create accurate acoustic models in CATT the models must be of a simplified form, with minor details excluded from the implementation. The models used in CATT are either made from scratch or by taking the existing architectural model and simplifying it by hand. By creating a program in Grasshopper, models in Rhino can be automatically simplified to a desired number of faces, saving on time and manpower. Further, the program can be extended to include the application of acoustic materials to each face and the export of the files from Grasshopper straight to CATT without other intermediary steps. The program was successfully created, and now can take an existing model and reduce it down to even just a small number of faces. But at what point does this simplification take a toll on the acoustic results? This was explored further with emphasis on the following acoustic parameters: Clarity (C80), Strength (G), Sound Pressure Level (SPL), Speech Transmission Index (STI), and Reverberation Time (T30). The extent to which these parameters are affected by the reduction of a mesh is explored in both the source to receiver calculations and the audience maps for three differently shaped venues. Three different levels of simplification were tested: 50%, 80%, and 95%. These were compared to the original model and also an unsimplified, 0%, model that was altered (but not reduced) by the Mesh Reduce component. All the five parameters for the 50% reduction deviated only slightly from the unsimplified models. As the simplification increased to 80% most of the parameters were still within a reasonable range with little deviation, except for the reverberation time. From the results it was found that the upper limit of reduction would be about 80%, and falling somewhere between that and 50% would be a useful range for simplification. The results also showed a great amount of time saved for these simplified models, particularly in the audience map results. Ultimately, the program can be used effectively to reduce meshes for acoustic modelling with little detriment to the final results.