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Monte-Carlo simulation of colliding particles or coalescing droplets transported by a turbulent flow in the framework of a joint fluid–particle pdf approach

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Academic year: 2021

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Fig. 2. Dependence of the CCV Monte-Carlo algorithm predictions of the inter- inter-particle collision time scale of inter-particles suspended in homogeneous isotropic gas turbulence on the number of parcels per section N par =N 3 sec
Fig. 6. Dependence of the CCV Monte-Carlo algorithm predictions of the inter- inter-particle collision time scale of inter-particles suspended in homogeneous isotropic gas turbulence on the size of the mesh used to discretize the gas velocity space (c f -
Fig. 7. Dependence of the particle kinetic energy (normalized by the fluid turbulent kinetic energy seen by the particle) on the inverse of the Stokes number measured in deterministic simulation DPS/DNS
Fig. 9. Fluid–particle velocity covariance normalized by the value in case without collisions with respect to the collision frequency
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