Browsing by Author "van Jaarsveld, Jacoline"

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    Predicting the effect of biofilm growth on the pressure drop over a biofilter
    (Stellenbosch : Stellenbosch University, 2017-12) van Jaarsveld, Jacoline; Fidder-Woudberg, Sonia; Stellenbosch University. Faculty of Science. Dept. of Mathematical Sciences. Division Applied Mathematics.
    ENGLISH ABSTRACT : Hydrogen sulphide is a poisonous gas produced by several industries. It is therefore crucial to investigate and mathematically model the environmentally friendly biofiltration process, which has the ability to remove poisonous gasses, such as hydrogen sulphide, from an air stream. In this study two approaches are used for modelling biofilm growth in three different biofilters, i.e. an empirical and analytical approach. In the empirical modelling approach, the pressure drop prediction of the Modified-Macdonald equation, the existing granular rectangular Representative Unit Cell (RUC) model and the model of Comiti and Renaud are used to determine the changes in biofilm affected porosity, specific surface area, tortuosity and biofilm thickness. The results are obtained by using Excel R Solver, which is based on an optimization method. Thereafter a sensitivity analysis is performed in order to analyze the effect of the sphericity. The analytical modelling approach involves only the RUC model. The first step is to predict the biofilm thickness. Thereafter, two methods are suggested for predicting the biofilm affected specific surface area. The first method is based on an approach suggested in the literature. In the second method, the RUC model is used to express the pressure drop in terms of the biofilm affected specific surface area, which yields the adapted RUC model. The biofilm affected specific surface area values are then obtained by making use of experimental pressure drop data and superficial velocity values. After incorporating both the analytically and empirically determined sphericity values into the adapted RUC model, the pressure drop results show the significant effect that the sphericity value has on the model predictions. Finally, a sensitivity analysis is performed on the input parameters to the model.