Modelling and Simulation of Multidimensional Fractionation in Fine Particle Systems and their Application

For fine particle systems, a separation gap is observed for particle sizes in the range of 100nm to 10µm. In this transition region, facilities suffer from a lowered selectivity and separation efficiency. In order to be able to improve existing plants and processes, new fundamental knowledge on particle dynamics will be gained through numerical simulations in this project. It is based on a previous project in which a model for the prediction of sedimentation of arbitrarily shaped particles and distributed particle collectives was developed. In this project, the focus is on process engineering applications. For this purpose, the model is extended, such that simulations of realistic particle collectives can be carried out in real application geometries. The main goal is the elucidation of multidimensional correlations of shape and operating parameters on the process scale to improve selectivity in the size range of the separation gap.

Multidimensional fractionation KIT
Figure 1: Multidimensional fractionation

Contact: Maurus Bauer
Fundings: This research is funded by the German Research Foundation (DFG) withing the priority program “Hochspezifische mehrdimensionale Fraktionierung von technischen Feinstpartikelsystemen”.

Publications:
Marquardt, J. E., Arlt, C.-R., Trunk, R., Franzreb, M., Krause, M. J., Numerical and experimental examination of the retention of magnetic nanoparticles in magnetic chromatography. Computers & Mathematics with Applications, 2021, 89, p. 34-43.
DOI: 10.1016/j.camwa.2021.02.010

Trunk, R., Weckerle, T., Hafen, N., Thäter, G., Nirschl, H., Krause, M. J., Revisiting the Homogenized Lattice Boltzmann Method with Applications on Particulate Flows. Computation, 2021, 9(2), 11.
DOI: 10.3390/computation9020011 Open Access

Trunk, R., Bretl, C., Thäter, G., Nirschl, H., Dorn, M., Krause, M. J., A Study on Shape-Dependent Settling of Single Particles with Equal Volume Using Surface Resolved Simulations. Computation, 2021, 9(4), 40.
DOI: 10.3390/computation9040040 Open Access


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