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Study of Aerosol Motion in Granular and Foam Filters with Equal Porosity of the Structure

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International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019 (EMMFT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1259))

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Abstract

This paper consider a comparison of granular and open cell foam filters based on the models of filters with different sizes of granules and cells. For all models, the porosity parameter of the medium remained fixed (ε = 0.44). Due to the random location of the cells to eliminate errors, the calculation results for each sample were averaged over the calculations of five different geometries with the same parameters. The results of numerical calculations are in a good agreement with the experimental data of the pressure drop value in the filters. It was found that open cell foam material shows the maximum pressure drop, and the efficiency of particle deposition in the model of open cell foam filter is higher in comparison with the model of granular filter. The largest cell size provides the maximum value of the filter quality factor in the case of open cell foam material, the reverse pattern is observed in the case of granular filter.

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Acknowledgments

This work is supported by the Russian Science Foundation under grant № 19-71-00100.

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Authors and Affiliations

  1. Kazan State Power Engineering University, Krasnoselskaja str., 51, Kazan, 420066, Russia

    Olga Soloveva

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  1. Olga Soloveva
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Correspondence to Olga Soloveva .

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Editors and Affiliations

  1. Peter the Great St. Petersburg Polytechnic, Saint Petersburg, Russia

    Vera Murgul

  2. Saint Petersburg State University of Architecture and Civil Engineering, Saint Petersburg, Russia

    Viktor Pukhkal

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Soloveva, O. (2021). Study of Aerosol Motion in Granular and Foam Filters with Equal Porosity of the Structure. In: Murgul, V., Pukhkal, V. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019. EMMFT 2019. Advances in Intelligent Systems and Computing, vol 1259. Springer, Cham. https://doi.org/10.1007/978-3-030-57453-6_61

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