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A coarse-grained parcel method for heat and mass transfer simulations of spray coating processes. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2022.103590] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Dataset for the Heat-Up and Heat Transfer towards Single Particles and Synthetic Particle Clusters from Particle-Resolved CFD Simulations. DATA 2022. [DOI: 10.3390/data7020023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Heat transfer to particles is a key aspect of thermo-chemical conversion of pulverized fuels. These fuels tend to agglomerate in some areas of turbulent flow and to form particle clusters. Heat transfer and drag of such clusters are significantly different from single-particle approximations commonly used in Euler–Lagrange models. This fact prompted a direct numerical investigation of the heat transfer and drag behavior of synthetic particle clusters consisting of 44 spheres of uniform diameter (60 μm). Particle-resolved computational fluid dynamic simulations were carried out to investigate the heat fluxes, the forces acting upon the particle cluster, and the heat-up times of particle clusters with multiple void fractions (0.477–0.999) and varying relative velocities (0.5–25 m/s). The integral heat fluxes and exact particle positions for each particle in the cluster, integral heat fluxes, and the total acting force, derived from steady-state simulations, are reported for 85 different cases. The heat-up times of individual particles and the particle clusters are provided for six cases (three cluster void fractions and two relative velocities each). Furthermore, the heat-up times of single particles with different commonly used representative particle diameters are presented. Depending on the case, the particle Reynolds number, the cluster void fraction, the Nusselt number, and the cluster drag coefficient are included in the secondary data.
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Abstract
Heat transfer is a crucial aspect of thermochemical conversion of pulverized fuels. Over-predicting the heat transfer during heat-up leads to under-estimation of the ignition time, while under-predicting the heat loss during the char conversion leads to an over-estimation of the burnout rates. This effect is relevant for dense particle jets injected from dense-phase pneumatic conveying. Heat fluxes characteristic of such dense jets can significantly differ from single particles, although a single, representative particle commonly models them in Euler–Lagrange models. Particle-resolved direct numerical simulations revealed that common representative particles approaches fail to reproduce the dense-jet characteristics. They also confirm that dense clusters behave similar to larger, porous particles, while the single particle characteristic prevails for sparse clusters. Hydrodynamics causes this effect for convective heat transfer since dense clusters deflect the inflowing fluid and shield the center. Reduced view factors cause reduced radiative heat fluxes for dense clusters. Furthermore, convection is less sensitive to cluster shape than radiative heat transfer. New heat transfer models were derived from particle resolved simulations of particle clusters. Heat transfer increases at higher void fractions and vice versa, which is contrary to most existing models. Although derived from regular particle clusters, the new convective heat transfer models reasonably handle random clusters. Contrary, the developed correction for the radiative heat flux over-predicts shading effects for random clusters because of the used cluster shape. In unresolved Euler–Lagrange models, the new heat transfer models can significantly improve dense particle jets’ heat-up or thermochemical conversion modeling.
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Forgber T, Toson P, Madlmeir S, Kureck H, Khinast JG, Jajcevic D. Extended validation and verification of XPS/AVL-Fire™, a computational CFD-DEM software platform. POWDER TECHNOL 2020. [DOI: 10.1016/j.powtec.2019.11.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Blais B, Vidal D, Bertrand F, Patience GS, Chaouki J. Experimental Methods in Chemical Engineering: Discrete Element Method—DEM. CAN J CHEM ENG 2019. [DOI: 10.1002/cjce.23501] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Bruno Blais
- Department of Chemical EngineeringPolytechnique Montréal C.P. 6079, Succ. CV Montréal QC, H3C 3A7 Canada
| | - David Vidal
- Department of Chemical EngineeringPolytechnique Montréal C.P. 6079, Succ. CV Montréal QC, H3C 3A7 Canada
| | - Francois Bertrand
- Department of Chemical EngineeringPolytechnique Montréal C.P. 6079, Succ. CV Montréal QC, H3C 3A7 Canada
| | - Gregory S. Patience
- Department of Chemical EngineeringPolytechnique Montréal C.P. 6079, Succ. CV Montréal QC, H3C 3A7 Canada
| | - Jamal Chaouki
- Department of Chemical EngineeringPolytechnique Montréal C.P. 6079, Succ. CV Montréal QC, H3C 3A7 Canada
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