Particle accumulation model in 3D reconstructed wall of a catalytic filter validated with time-resolved X-ray tomography

A transient pore-scale model of particle deposit formation in 3D microstructure of a catalytic filter wall is introduced. It predicts location of particle deposits, dynamics of their growth, transition from deep to cake filtration regime as well as the impact on flow field, pressure drop and filtrat...

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Published inFuel (Guildford) Vol. 356; p. 129603
Main Authors Plachá, Marie, Isoz, Martin, Kočí, Petr, Jones, Matthew P., Svoboda, Miloš, Eastwood, David S., York, Andrew P.E.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 15.01.2024
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Summary:A transient pore-scale model of particle deposit formation in 3D microstructure of a catalytic filter wall is introduced. It predicts location of particle deposits, dynamics of their growth, transition from deep to cake filtration regime as well as the impact on flow field, pressure drop and filtration efficiency. The model is validated against time-resolved X-ray tomography (XRT) data acquired during a filtration experiment. The validated model is then used in transient simulations of the soot filtration process in several different microstructures using cordierite filter substrate with varied Pd/γ-Al2O3 catalyst distribution. The sample with the coating solely inside the wall pores provides the lowest initial pressure drop but suffers from low clean filtration efficiency and high pressure drop after the cake is formed. The sample with partial on-wall coating achieves not only a higher filtration efficiency but also a lower pressure drop in long-term operation. •Soot deposition model in 3D microstructure of catalytic filter wall developed.•Transient model describes growth of particle deposits that affect flow pattern.•Model predictions validated by 4D X-ray tomography during filtration experiment.•Catalytic particulate filters with in-wall, on-wall and combined washcoat compared.•Evolution of filtration efficiency and pressure drop with soot loading predicted.
ISSN:0016-2361
DOI:10.1016/j.fuel.2023.129603