Abstract
This paper presents a ray tracing algorithm developed as a research and teaching tool. The motivations to pursue this task and some novel features of the algorithm are presented. Amongst them, it is possible to cite: (i) the receivers may grow in size, which saves some computational cost; (ii) sound intensity calculations are performed in a separate step than geometrical ray tracing; and (iii) those features allow Monte Carlo simulations for uncertainty prediction related to absorption data. The results obtained with the proposed algorithm are compared with the measured data (and other software packages) of Round Robins II (Elmia Hall) and III (PTB recording studio) and proved to be in good agreement with measured data. The ratio of the mean error by the JND of each parameter are compatible with the results presented by the other round robin participants. The product of this research is also scalable to an hybrid algorithm and alternatives to do so are provided through the discussion in the paper.
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