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Finally, there is a brief discussion regarding the existing models predicting particle sizes.
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A population balance-based model coupled with a thermodynamic model predicts particle size distribution vs. experimental time using a reconstruction model.
The statistical model predicts particle size (Y) with 90% confidence and the Y values are significantly affected by X1 and X2.
This paper presents initial work on developing models for predicting particle dampers (PDs) behaviour using the Discrete Element Method (DEM).
Combining the empirical model for predicting particle shape with the size distribution model, a flakiness prediction model is proposed.
A mathematical model for predicting particle separation efficiency and cut size particle diameter has been developed.
Prompted by the success of this model in predicting particle dispersion in one-dimensional and two-dimensional inhomogeneous turbulent flows, an assessment is made of the ability of the model to predict correctly mean particle concentrations in a three-dimensional inhomogeneous turbulent flow within a mechanically ventilated airspace.
Various lung models used in predicting particle deposition are reviewed and discussed.
Discussion of these results highlights the limited ability of existing models to aid in predicting particle retention of non-ideal materials for engineering purposes.
Also, a semi-empirical model was developed for predicting particle size.
It is observed that the 2D CPFD model is valuable for predicting particle flows in the feeding near region keeping it unaffected by fast fluidized bed upsets such as suspension chocking.
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