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Designing optimally‐graded depth filter media using a novel multiscale method
Author(s) -
Geerling Constantin,
Azimian Mehdi,
Wiegmann Andreas,
Briesen Heiko,
Kuhn Michael
Publication year - 2020
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.16808
Subject(s) - filtration (mathematics) , filter (signal processing) , deposition (geology) , scale (ratio) , computer science , trajectory , biological system , materials science , mechanics , algorithm , mathematics , physics , computer vision , geology , statistics , paleontology , quantum mechanics , astronomy , sediment , biology
Even though current manufacturing methods allow to build precisely‐defined graded depth filter media, it remains unclear which local filtration properties are desirable. We, therefore, introduce a multiscale approach which links pore and continuum scale (PS and CS) to address this question. Based on data from PS simulations, local filtration performance, as described by the filter coefficient, is predicted on the CS by an optimal control solution and the obtained trajectory is translated back to the PS where it is validated. Two case studies are presented: a bidisperse fibrous medium and a granular depth filter composed of bidisperse particles. Both media are optimized to achieve a homogenous deposition of separated impurities along the filter depth. It is found that the presented method allows to reach this goal reasonably well in both cases. We claim that our method forms a good basis for further developments for which promising possibilities are highlighted.