(444f) Using a Novel Approach to Model Drop Size Distribution: The Adaptive Multi-Size Group Method
The simpler models can increase the accuracy in dispersed flow but are not sufficient to capture all the details, especially if the size distributions do not follow log normal type of distributions. The quadrature based models generally give higher accuracy but at a disproportionately higher compute cost. This is due to them computing size bins which may be empty and/or cannot adapt to the changing distribution shape. In this paper we present the results from a recent model termed as AMuSiG or adaptive multi-size group model. This model is expected to give higher accuracy comparable to quadrature based models but at a much lower compute cost. A basic description of the model with validation examples will be provided.
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