When predicting sound propagation in rooms such as industrial workrooms, a major factor that must be taken into consideration is the presence of 'fittings' — obstacles such as machines and stockpiles — in the room. Besides the fitting spatial distribution, there are two important parameters used in prediction models to describe the fittings — one is the fitting density — a measure of the number of fittings and the average fitting crosssection area — and the other is the fitting absorption

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... cient. While ranges of typical fitting densities are known, no method exists for measuring or estimating the fitting density in a given factory. Furthermore, theoretical expressions for calculating fitting density assume small fittings and high frequency. The aim of this research project is to develop and test a method for determining the fitting density in industrial workrooms. To achieve this objective a correction formula was derived for calculating the fitting density in the case of large fitting dimensions. The variation of fitting density with frequency was found from sound propagation measurements in large fitted regions; a formula to express the relationship is determined by statistical methods and this model was validated experimentally in a scale-model workroom and in a machine shop with the help of prediction models. A correction formula for calculating fitting absorption coefficient using empty and fitted room absorption coefficients was derived and validated using measurement in a machine shop. A n image-source model — based on improving an existing model used for infinite regions — was developed to predict sound propagation in fitted rooms and validated in several workrooms. This model provided a fast, workable and accurate alternative to existing fitted-room models.