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Modeling the separation performance of depth filter considering tomographic data
Author(s) -
Hoppe Kevin,
Maricanov Michail,
Schaldach Gerhard,
Zielke Reiner,
Renschen Dirk,
Tillmann Wolfgang,
Thommes Markus,
Pieloth Damian
Publication year - 2020
Publication title -
environmental progress and sustainable energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.495
H-Index - 66
eISSN - 1944-7450
pISSN - 1944-7442
DOI - 10.1002/ep.13423
Subject(s) - filtration (mathematics) , filter (signal processing) , porosity , deposition (geology) , work (physics) , porous medium , materials science , process engineering , computer science , environmental science , composite material , mathematics , geology , engineering , mechanical engineering , statistics , computer vision , paleontology , sediment
Fibrous depth filters are frequently used for the purification of gas streams with low dust loadings, as well as processes where a high initial filtration efficiency is required (e.g., clean rooms for aseptic production). One tool suitable for supporting the development of optimized filter media is the use of numerical simulations. The drawback of this technique is the high computational resources required. In this work, a new and fast approach based on a one‐dimensional model was applied. Structural characteristics (e.g., porosity distribution and fiber diameter) of two different filter media were successfully determined using a novel X‐ray microscope. These characteristics were incorporated in the filtration model, and their influence on the calculations was evaluated. It was found that the porosity distribution does have an impact on local (microscopic) deposition rates, but only a minor influence on the macroscopic filtration efficiency (around 3%). Benefits of the model are the application of measured structural data and the low computational expense. Compared to experimental data (VDI 3926 / ISO 11057), the prediction of the filtration efficiency can be improved by incorporating the structural data in the model.