Analysis of the behavior of deposits in fibrous filters during non-steady state filtration using X-ray computed tomography

Jackiewicz, A.; Jakubiak, Szymon; Gradoń, Leon

doi:10.1016/j.seppur.2015.10.004

Cited by 23 publications

(9 citation statements)

References 26 publications

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“…As can be seen during the early stages of filtration  decreases monotonically with depth, while for the later stages the maximum is observed at some distance from the filter surface, which is caused by the re-entrainment and redeposition of particle clusters. Recently Jackiewicz et al (2015) reported similar behavior for experimental analysis of particles deposition in fibrous filters. This phenomenon was not observed by Skouras et al (2004) …”

Section: Resuspension Modelmentioning

confidence: 52%

Dynamics of particle loading in deep-bed filter. Transport, deposition and reentrainment

Przekop

Gradoń

2016

Chemical and Process Engineering

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Deep bed filtration is an effective method of submicron and micron particle removal from the fluid stream. There is an extensive body of literature regarding particle deposition in filters, often using the classical continuum approach. However, the approach is not convenient for studying the influence of particle deposition on filter performance (filtration efficiency, pressure drop) when nonsteady state boundary conditions have to be introduced. For the purposes of this work the latticeBoltzmann model describes fluid dynamics, while the solid particle motion is modeled by the Brownian dynamics. For aggregates the effect of their structure on displacement is taken into account. The possibility of particles rebound from the surface of collector or reentrainment of deposits to fluid stream is calculated by energy balanced oscillatory model derived from adhesion theory. The results show the evolution of filtration efficiency and pressure drop of filters with different internal structure described by the size of pores. The size of resuspended aggregates and volume distribution of deposits in filter were also analyzed. The model enables prediction of dynamic filter behavior. It can be a very useful tool for designing filter structures which optimize maximum lifetime with the acceptable values of filtration efficiency and pressure drop.

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Section: Resuspension Modelmentioning

confidence: 52%

Dynamics of particle loading in deep-bed filter. Transport, deposition and reentrainment

Przekop

Gradoń

2016

Chemical and Process Engineering

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“…on macroscopic parameters such as filtration efficiency and pressure. 10,11,36 However, the description of the macroscopic filtration efficiency of the filter media is still a challenge, and evaluations of the interaction between microscopic and macroscopic parameters are still sparse in literature. Possible reasons are the mentioned limitations in computational resources and also the frequent lack of access to high-resolution, structural parameters.…”

Section: Introductionmentioning

confidence: 99%

Modeling the separation performance of depth filter considering tomographic data

Hoppe

Maricanov

Schaldach

et al. 2020

Env Prog and Sustain Energy

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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.

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“…Charvet et al [8] performed X-ray holotomography to observe the three-dimensional structure of a fibrous filter containing cellulose fibers and to determine the liquid distribution in the filter clogged with a liquid aerosol of di-ethyl-hexyl-sebacate (DEHS). Jackiewicz et al [9] carried out X-ray micro-tomography analyses to observe the in-depth structure of silica particle deposits in two melt-blown polypropylene materials and calculate their porosity profiles. Thibault and Bloch [10] used micro-tomography to observe and characterize the 3D structure of a nonwoven papermaker felt through the calculation of the mean porosity, and the representation of porosity profiles.…”

Section: Introductionmentioning

confidence: 99%

Characterization of the porous structure of a non-woven fibrous medium for air filtration at local and global scales using porosimetry and X-ray micro-tomography

et al. 2017

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Analysis of the behavior of deposits in fibrous filters during non-steady state filtration using X-ray computed tomography

Cited by 23 publications

References 26 publications

Dynamics of particle loading in deep-bed filter. Transport, deposition and reentrainment

Dynamics of particle loading in deep-bed filter. Transport, deposition and reentrainment

Modeling the separation performance of depth filter considering tomographic data

Characterization of the porous structure of a non-woven fibrous medium for air filtration at local and global scales using porosimetry and X-ray micro-tomography

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