A 3D Monte Carlo Simulation of Convective Diffusional Deposition of Ultrafine Particles on Fiber Surfaces
The microscale simulation of ultrafine particle transport and deposition in fibrous filtration media was achieved with a novel particle tracking model using a 3D Monte Carlo model. The particle deposition process is governed by the convection–diffusion field. Simulations were performed by considerin...
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MDPI AG
2022-08-01
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author | Shixian Wu Yongping Chen Can Qi Chunyu Liu Gang Li Hui Zhu |
author_facet | Shixian Wu Yongping Chen Can Qi Chunyu Liu Gang Li Hui Zhu |
author_sort | Shixian Wu |
collection | DOAJ |
description | The microscale simulation of ultrafine particle transport and deposition in fibrous filtration media was achieved with a novel particle tracking model using a 3D Monte Carlo model. The particle deposition process is governed by the convection–diffusion field. Simulations were performed by considering the fibrous filtration media as an array of identical parallel fibers, in which the flow field was accurately described by an analytical solution. The model of particle movement was described by the random probability distribution characterized by a dimensionless factor, the Peclet number (<i>Pe</i>), based on a convection–diffusive equation of particle transport in fluid. The influence of the particle Peclet number (<i>Pe</i>) on the particle deposition process and the resulting deposition morphology was investigated. The results were analyzed in terms of dust layer growth, particles’ trajectories and dust layer porosity for a vast range of Peclet numbers. The development of distinct deposition morphologies was found by varying the Peclet number (<i>Pe</i>). With a small Peclet number, diffusion dominated deposition and led to the formation of a more open and looser dust layer structure, while with larger Peclet numbers, convection dominated deposition and was found to form compact deposits. According to the change in the location of the packing densities along the dust layer height direction, the dust layer structure could be divided into three typical parts: the substructure, main profile and surface layer. In addition, the deposit morphologies observed for a high Pe were in good agreement with the experimental results found in the literature. |
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spelling | doaj.art-cff30877af4c47c49360d50e927b31112023-12-03T13:19:45ZengMDPI AGAtmosphere2073-44332022-08-01138131910.3390/atmos13081319A 3D Monte Carlo Simulation of Convective Diffusional Deposition of Ultrafine Particles on Fiber SurfacesShixian Wu0Yongping Chen1Can Qi2Chunyu Liu3Gang Li4Hui Zhu5School of Energy and Building Environment, Guilin University of Aerospace Technology, Guilin 541004, ChinaSchool of Energy and Building Environment, Guilin University of Aerospace Technology, Guilin 541004, ChinaSchool of Energy and Building Environment, Guilin University of Aerospace Technology, Guilin 541004, ChinaSchool of Energy and Building Environment, Guilin University of Aerospace Technology, Guilin 541004, ChinaSinosteel Maanshan General Institute of Mining Research Co., Ltd., Maanshan 243000, ChinaSchool of Energy and Building Environment, Guilin University of Aerospace Technology, Guilin 541004, ChinaThe microscale simulation of ultrafine particle transport and deposition in fibrous filtration media was achieved with a novel particle tracking model using a 3D Monte Carlo model. The particle deposition process is governed by the convection–diffusion field. Simulations were performed by considering the fibrous filtration media as an array of identical parallel fibers, in which the flow field was accurately described by an analytical solution. The model of particle movement was described by the random probability distribution characterized by a dimensionless factor, the Peclet number (<i>Pe</i>), based on a convection–diffusive equation of particle transport in fluid. The influence of the particle Peclet number (<i>Pe</i>) on the particle deposition process and the resulting deposition morphology was investigated. The results were analyzed in terms of dust layer growth, particles’ trajectories and dust layer porosity for a vast range of Peclet numbers. The development of distinct deposition morphologies was found by varying the Peclet number (<i>Pe</i>). With a small Peclet number, diffusion dominated deposition and led to the formation of a more open and looser dust layer structure, while with larger Peclet numbers, convection dominated deposition and was found to form compact deposits. According to the change in the location of the packing densities along the dust layer height direction, the dust layer structure could be divided into three typical parts: the substructure, main profile and surface layer. In addition, the deposit morphologies observed for a high Pe were in good agreement with the experimental results found in the literature.https://www.mdpi.com/2073-4433/13/8/1319fibrous filtrationparticle depositionconvection-diffusiondust layerMonte Carlo simulation |
spellingShingle | Shixian Wu Yongping Chen Can Qi Chunyu Liu Gang Li Hui Zhu A 3D Monte Carlo Simulation of Convective Diffusional Deposition of Ultrafine Particles on Fiber Surfaces Atmosphere fibrous filtration particle deposition convection-diffusion dust layer Monte Carlo simulation |
title | A 3D Monte Carlo Simulation of Convective Diffusional Deposition of Ultrafine Particles on Fiber Surfaces |
title_full | A 3D Monte Carlo Simulation of Convective Diffusional Deposition of Ultrafine Particles on Fiber Surfaces |
title_fullStr | A 3D Monte Carlo Simulation of Convective Diffusional Deposition of Ultrafine Particles on Fiber Surfaces |
title_full_unstemmed | A 3D Monte Carlo Simulation of Convective Diffusional Deposition of Ultrafine Particles on Fiber Surfaces |
title_short | A 3D Monte Carlo Simulation of Convective Diffusional Deposition of Ultrafine Particles on Fiber Surfaces |
title_sort | 3d monte carlo simulation of convective diffusional deposition of ultrafine particles on fiber surfaces |
topic | fibrous filtration particle deposition convection-diffusion dust layer Monte Carlo simulation |
url | https://www.mdpi.com/2073-4433/13/8/1319 |
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