Filtration Kinetics of Depth Filters—Modeling and Comparison with Tomographic Data of Particle Depositions
Depth filtration is a widespread technique for the separation of airborne particles. The evolution of the pressure difference within this process is determined to a significant extent by the filter structure. Simulations are an important tool for optimizing the filter structure, allowing the develop...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/14/4/640 |
| _version_ | 1797606431502893056 |
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| author | Kevin Hoppe Lukas Wischemann Gerhard Schaldach Reiner Zielke Wolfgang Tillmann Markus Thommes Damian Pieloth |
| author_facet | Kevin Hoppe Lukas Wischemann Gerhard Schaldach Reiner Zielke Wolfgang Tillmann Markus Thommes Damian Pieloth |
| author_sort | Kevin Hoppe |
| collection | DOAJ |
| description | Depth filtration is a widespread technique for the separation of airborne particles. The evolution of the pressure difference within this process is determined to a significant extent by the filter structure. Simulations are an important tool for optimizing the filter structure, allowing the development of filter materials having high filtration efficiencies and low pressure differences. Because of the large number of physical phenomena and the complex structure of filter materials, simulations of the filtration kinetics are, however, challenging. In this context, one-dimensional models are advantageous for the calculation of the filtration kinetics of depth filters, due to their low computation requirements. In this work, an approach for combining a one-dimensional model with microstructural data of filter materials is presented. This enables more realistic modeling of the filtration process. Calculations were performed on a macroscopic as well as microscopic level and compared to experimental data. With the suggested approach, the influence of a measured microstructure on the results was examined and predictability was improved. Especially for small research departments and for the development of optimized filter materials adapted to specific separation tasks, this approach provides a valuable tool. |
| first_indexed | 2024-03-11T05:15:05Z |
| format | Article |
| id | doaj.art-79c949759e37401aadff538af59ad2df |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-11T05:15:05Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-79c949759e37401aadff538af59ad2df2023-11-17T18:16:43ZengMDPI AGAtmosphere2073-44332023-03-0114464010.3390/atmos14040640Filtration Kinetics of Depth Filters—Modeling and Comparison with Tomographic Data of Particle DepositionsKevin Hoppe0Lukas Wischemann1Gerhard Schaldach2Reiner Zielke3Wolfgang Tillmann4Markus Thommes5Damian Pieloth6Department of Applied Life Sciences and Process Engineering, Anhalt University of Applied Science, Bernburger Str. 55, D-06366 Koethen, GermanyLaboratory of Solids Process Engineering, Department of Bio- and Chemical Engineering, TU Dortmund University, Emil-Figge Str. 68, D-44227 Dortmund, GermanyLaboratory of Solids Process Engineering, Department of Bio- and Chemical Engineering, TU Dortmund University, Emil-Figge Str. 68, D-44227 Dortmund, GermanyRIF-Institut für Forschung und Transfer e.V., Joseph-von-Fraunhofer Str. 20, D-44227 Dortmund, GermanyRIF-Institut für Forschung und Transfer e.V., Joseph-von-Fraunhofer Str. 20, D-44227 Dortmund, GermanyLaboratory of Solids Process Engineering, Department of Bio- and Chemical Engineering, TU Dortmund University, Emil-Figge Str. 68, D-44227 Dortmund, GermanyDepartment of Applied Life Sciences and Process Engineering, Anhalt University of Applied Science, Bernburger Str. 55, D-06366 Koethen, GermanyDepth filtration is a widespread technique for the separation of airborne particles. The evolution of the pressure difference within this process is determined to a significant extent by the filter structure. Simulations are an important tool for optimizing the filter structure, allowing the development of filter materials having high filtration efficiencies and low pressure differences. Because of the large number of physical phenomena and the complex structure of filter materials, simulations of the filtration kinetics are, however, challenging. In this context, one-dimensional models are advantageous for the calculation of the filtration kinetics of depth filters, due to their low computation requirements. In this work, an approach for combining a one-dimensional model with microstructural data of filter materials is presented. This enables more realistic modeling of the filtration process. Calculations were performed on a macroscopic as well as microscopic level and compared to experimental data. With the suggested approach, the influence of a measured microstructure on the results was examined and predictability was improved. Especially for small research departments and for the development of optimized filter materials adapted to specific separation tasks, this approach provides a valuable tool.https://www.mdpi.com/2073-4433/14/4/640filtrationtomographysimulationmicrostructurefiltration kinetics |
| spellingShingle | Kevin Hoppe Lukas Wischemann Gerhard Schaldach Reiner Zielke Wolfgang Tillmann Markus Thommes Damian Pieloth Filtration Kinetics of Depth Filters—Modeling and Comparison with Tomographic Data of Particle Depositions Atmosphere filtration tomography simulation microstructure filtration kinetics |
| title | Filtration Kinetics of Depth Filters—Modeling and Comparison with Tomographic Data of Particle Depositions |
| title_full | Filtration Kinetics of Depth Filters—Modeling and Comparison with Tomographic Data of Particle Depositions |
| title_fullStr | Filtration Kinetics of Depth Filters—Modeling and Comparison with Tomographic Data of Particle Depositions |
| title_full_unstemmed | Filtration Kinetics of Depth Filters—Modeling and Comparison with Tomographic Data of Particle Depositions |
| title_short | Filtration Kinetics of Depth Filters—Modeling and Comparison with Tomographic Data of Particle Depositions |
| title_sort | filtration kinetics of depth filters modeling and comparison with tomographic data of particle depositions |
| topic | filtration tomography simulation microstructure filtration kinetics |
| url | https://www.mdpi.com/2073-4433/14/4/640 |
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