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Classification of Ultrafine Particles Using a Novel 3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling
[Image: see text] Ultrafine particle classification can be realized using hydrocyclones with novel structures to overcome the limitations of conventional hydrocyclones with tangential inlets or cone structures. Herein, the hydrocyclones with different inlet structures and cone angles were investigat...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9835633/ https://www.ncbi.nlm.nih.gov/pubmed/36643565 http://dx.doi.org/10.1021/acsomega.2c06383 |
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author | Xu, Yanxia Ye, Junxiang Song, Xingfu Yu, Jianguo |
author_facet | Xu, Yanxia Ye, Junxiang Song, Xingfu Yu, Jianguo |
author_sort | Xu, Yanxia |
collection | PubMed |
description | [Image: see text] Ultrafine particle classification can be realized using hydrocyclones with novel structures to overcome the limitations of conventional hydrocyclones with tangential inlets or cone structures. Herein, the hydrocyclones with different inlet structures and cone angles were investigated for classifying ultrafine particles. Computational fluid dynamics (CFD) simulations were performed using the Eulerian–Eulerian method, and ultrafine MnO(2) powder was used as a case study. The simulation results show a fine particle (≤5 μm) removal efficiency of 0.89 and coarse particle (>5 μm) recovery efficiency of 0.99 for a hydrocyclone design combining an arc inlet and a 30° cone angle under a solid concentration of 2.5 wt %. Dynamic analysis indicated that the novel arc inlet provided a preclassification effect to reduce the misplacement of fine/coarse particles, which cannot be provided by conventional tangential or involute inlets. Furthermore, the proposed design afforded comprehensive improvement in the flow field by regulating the residence time and radial acceleration. Subsequently, a novel hydrocyclone with an arc inlet and 30° cone angle was manufactured using the three-dimensional (3D) printing technology. Experiments were conducted for classifying ultrafine MnO(2) particles using the novel 3D-printed hydrocyclone and conventional hydrocyclone. The results demonstrate that the classification performance of the 3D-printed hydrocyclone was superior to that of the conventional one, in particular, the removal efficiency of fine particles from 0.719 to 0.930 using a 10 wt % feed slurry. |
format | Online Article Text |
id | pubmed-9835633 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-98356332023-01-13 Classification of Ultrafine Particles Using a Novel 3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling Xu, Yanxia Ye, Junxiang Song, Xingfu Yu, Jianguo ACS Omega [Image: see text] Ultrafine particle classification can be realized using hydrocyclones with novel structures to overcome the limitations of conventional hydrocyclones with tangential inlets or cone structures. Herein, the hydrocyclones with different inlet structures and cone angles were investigated for classifying ultrafine particles. Computational fluid dynamics (CFD) simulations were performed using the Eulerian–Eulerian method, and ultrafine MnO(2) powder was used as a case study. The simulation results show a fine particle (≤5 μm) removal efficiency of 0.89 and coarse particle (>5 μm) recovery efficiency of 0.99 for a hydrocyclone design combining an arc inlet and a 30° cone angle under a solid concentration of 2.5 wt %. Dynamic analysis indicated that the novel arc inlet provided a preclassification effect to reduce the misplacement of fine/coarse particles, which cannot be provided by conventional tangential or involute inlets. Furthermore, the proposed design afforded comprehensive improvement in the flow field by regulating the residence time and radial acceleration. Subsequently, a novel hydrocyclone with an arc inlet and 30° cone angle was manufactured using the three-dimensional (3D) printing technology. Experiments were conducted for classifying ultrafine MnO(2) particles using the novel 3D-printed hydrocyclone and conventional hydrocyclone. The results demonstrate that the classification performance of the 3D-printed hydrocyclone was superior to that of the conventional one, in particular, the removal efficiency of fine particles from 0.719 to 0.930 using a 10 wt % feed slurry. American Chemical Society 2022-12-16 /pmc/articles/PMC9835633/ /pubmed/36643565 http://dx.doi.org/10.1021/acsomega.2c06383 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Xu, Yanxia Ye, Junxiang Song, Xingfu Yu, Jianguo Classification of Ultrafine Particles Using a Novel 3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling |
title | Classification of Ultrafine Particles Using a Novel
3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling |
title_full | Classification of Ultrafine Particles Using a Novel
3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling |
title_fullStr | Classification of Ultrafine Particles Using a Novel
3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling |
title_full_unstemmed | Classification of Ultrafine Particles Using a Novel
3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling |
title_short | Classification of Ultrafine Particles Using a Novel
3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling |
title_sort | classification of ultrafine particles using a novel
3d-printed hydrocyclone with an arc inlet: experiment and cfd modeling |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9835633/ https://www.ncbi.nlm.nih.gov/pubmed/36643565 http://dx.doi.org/10.1021/acsomega.2c06383 |
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