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Item type:Publication, Access status: without files , An efficient multiscale bi-directional PBM-DEM coupling framework to simulate one-dimensional aggregation mechanismsThe mesoscale population balance modelling (PBM) technique is widely used in predicting aggregation processes. The accuracy and efficiency of PBM depend on the formulation of its kernels. A model of the volume- A nd time-dependent onedimensional aggregation kernel is developed for predicting the temporal evolution of the considered particulate system. To make the developed model physically relevant, the PBM model needs three unknown parameters as input: Volume-dependency in collisions, collision frequency per particle and aggregation probability. For this, the microscale discrete element model (DEM) is used. The system's collision frequency is extracted periodically using a novel collision detection algorithm that detects and ignores duplicate collisions. Finally, a multiscale bi-directional PBM-DEM coupling framework is presented to simulate the aggregation mechanism. PBM and DEM simulations take place periodically to update the particle size distribution (PSD) and extract the collision-frequency, respectively. The coupling framework successfully explains the dependence between the PSD and the collision frequency. Additionally, computational cost of the algorithm is optimized while maintaining the accuracy of the results. Lastly, the accuracy and efficiency of the developed framework are verified using two different test cases. In one of the examples, a simple aggregation is simulated directly inside the DEM for the first time.Publicationtype: Journal Article37 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A weighted finite volume scheme for multivariate aggregation population balance equation(2017); ; For solving multivariate aggregation population balance equation, two new discretizations based on number and mass distributions are presented. These proposed schemes are relatively simple to implement and computationally very efficient. Moreover, the mathematical structure of the schemes remains unchanged with the change in dimension. Hence, these methods are ideally suited for solving multidimensional aggregation problems on non-uniform grids. The accuracy of the new schemes is shown by comparing number density as well as different order moments with exact results as well as with the numerical results of Forestier and Mancini (2012). Besides preservation of the zeroth and first order moments, the new schemes also predict higher order moments and number density very accurately. In conclusion, the proposed schemes are more accurate and efficient than the scheme of Forestier and Mancini (2012).Publicationtype: Journal Article66