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Multiscale Simulation of Gas Cleaning Processes

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Mathematical Models and Computer Simulations Aims and scope

Abstract

This paper considers modeling the processes of cleaning air from finely dispersed solid contaminants clustered in the form of nanoparticles. The purification technology chosen for the study involves the use of a system consisting of nanofilters and sorbents. Both cleaning methods used in it are currently in high demand and are often combined in appropriate devices. The first cleaning method using nanofilters ensures a high purification quality. However, this method is expensive as it requires frequent replacement of the filter elements (membranes) and the disposal of these elements. The second method of cleaning with sorbents gives a relatively low quality of cleaning but enables multiply repeated a purification procedure after washing the sorbent with special liquids. The optimization of air cleaning devices using nanofilters and sorbents requires a detailed investigation of the processes occurring in the cleaning system. The proposed study addresses part of the problem associated with the passage of an air flow containing solid contaminant nanoparticles through a layer of granular sorbent. For this purpose, a multiscale mathematical model, a numerical algorithm, and a parallel implementation of the model on a macroscopic scale have been developed. The novelty of the approach consists in the use of a quasigasdynamic model for describing the flow in the absorbing layer and in the proposed multiscale formulation of the problem. The preliminary calculations based on the macromodel showed the efficiency of the proposed approach.

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Correspondence to S. V. Polyakov.

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This work was supported by the Russian Foundation for Basic Research, project nos. 18-51-18004-Bolg_a, 18-07-01292_a, and 18-07-00841_a.

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Translated by I. Pertsovskaya

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Polyakov, S.V., Karamzin, Y.N., Kudryashova, T.A. et al. Multiscale Simulation of Gas Cleaning Processes. Math Models Comput Simul 12, 302–315 (2020). https://doi.org/10.1134/S2070048220030151

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