Dust explosions are among the most hazardous accidents affecting industrial facilities processing particulate solids. Describing the severity parameters of dust clouds is critical to the safety management and risk assessment of dust explosions. These parameters are determined experimentally in a 20 L spherical vessel, following the ASTM E1226 or UNE 14034 standards. Since their reproducibility depends on the levels of turbulence associated with the dust cloud, a computational model of the multi-phase (gas-solid) flow is used to simulate the dispersion process with the open-source CFD code OpenFOAM. The model is successfully validated against experimental measurements from the literature and numerical results of a commercial CFD code. In addition, this study considers the impact of particle size on the turbulence of the carrier phase, suggesting that particles attenuate its turbulence intensity. Moreover, the model predicts well the formation of a two-vortex flow pattern, which has a negative impact on the distribution of the particle-laden flows with d(p)<= 100 mu m, as most of the particles concentrate at the near-wall region. Contrarily, an improved homogeneity of dust cloud is observed for a case fed with larger particles (d(p) = 200 mu m), as the increased inertia of these particles allows them to enter into the re-circulation regions. (C) 2021 The Authors. Published by Elsevier B.V.
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Department of Mining and Nuclear Engineering,Missouri University of Science and TechnologyDepartment of Mining and Nuclear Engineering,Missouri University of Science and Technology
Robert Eades
Kyle Perry
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Department of Mining and Nuclear Engineering,Missouri University of Science and TechnologyDepartment of Mining and Nuclear Engineering,Missouri University of Science and Technology
Kyle Perry
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Catherine Johnson
Jacob Miller
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Department of Mining and Nuclear Engineering,Missouri University of Science and TechnologyDepartment of Mining and Nuclear Engineering,Missouri University of Science and Technology
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Iowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USAIowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USA
Hu, Xiaofei
Ilgun, Aziz Dogan
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Iowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USA
Iowa State Univ, Dept Chem & Biol Engn, 618 Bissell Rd, Ames, IA 50011 USAIowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USA
Ilgun, Aziz Dogan
Passalacqua, Alberto
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Iowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USAIowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USA
Passalacqua, Alberto
Fox, Rodney O.
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Iowa State Univ, Dept Chem & Biol Engn, 618 Bissell Rd, Ames, IA 50011 USAIowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USA
Fox, Rodney O.
Bertola, Francesco
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SABIC, Urmonderbaan 22,POB 319, NL-6160 AH Geleen, NetherlandsIowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USA
Bertola, Francesco
Milosevic, Miran
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SABIC, Urmonderbaan 22,POB 319, NL-6160 AH Geleen, NetherlandsIowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USA
Milosevic, Miran
Visscher, Frans
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SABIC, Urmonderbaan 22,POB 319, NL-6160 AH Geleen, NetherlandsIowa State Univ, Dept Mech Engn, 2529 Union Dr, Ames, IA 50011 USA