Numerical investigation on the interaction between particles and eddies in gas-particle flows behind a backward-facing step

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Numerical investigation on the interaction between particles and eddies in gas-particle flows behind a backward-facing step

 

Author: Yu, Kin-fung
Title: Numerical investigation on the interaction between particles and eddies in gas-particle flows behind a backward-facing step
Degree: Ph.D.
Year: 2006
Subject: Hong Kong Polytechnic University -- Dissertations.
Turbulence -- Mathematical models.
Gas flow -- Mathematical models.
Department: Dept. of Applied Physics
Pages: 159 leaves : ill. (some col.) ; 30 cm.
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b2059318
URI: http://theses.lib.polyu.edu.hk/handle/200/2654
Abstract: In this study, two-dimensional and three-dimensional numerical investigation of a low speed particle-laden turbulent flow over a backward-facing step has been carried out. An assumption of incompressibility of the flow is used due to low Mach number of the flow. The gas phase is performed by Large Eddy Simulation (LES) and the particle phase is solved by a Lagrangian particle tracking model. Effect of both drag and gravitational forces on particle motion is considered. Numerical simulation results reveal evolution of detailed vortical structures with different Reynolds numbers of 18,400 and 1,290 respectively in the backward-facing step flow. Simulation also predicts the instantaneous concentration of particles with different Reynolds numbers, Stokes numbers, initial velocity slip and the effect of gravitational force . Both the 2D and 3D simulations predict mean properties, such as mean velocity profiles for both phases and reattachment lengths for the gas phase, are in good agreement with experimental results. However, there is large discrepancy between 2D predicted fluctuating properties and experimental results, such as the rms velocity profiles, especially those near the top and bottom wall regions. The 3D simulation, on the other hand, has successfully predicted fluctuating properties that are in good agreement with experimental results. In other words, 3D computation can successfully reveal the properties of both the mean flow and the fluctuating properties of turbulence flows. Further comparison indicates that although both simulations can reveal the evolutions of the turbulent flow of the fluid phase, the 3D simulation predicts much frequent activity of vortex evolutions such as rolling up, growing, merging and breaking up. Evolutions of vortices are regular and orderly in 2D simulation. In 3D simulation, breaking up of vortices is common throughout the flow, so that the flow field becomes complex and diverse. Particle dispersions are numerically investigated by introducing spherical particles with different Stokes numbers and inlet velocity slip into the backward facing step. Both 2D and 3D simulations give similar results on particle dispersions. Smallest particles are strongly controlled by the vortex structure of the gas phase and follow closely the gas vortices. Particles with time scales of similar order as the fluid time scale are centrifuged out by a vortex and are preferentially concentrated along the edge of the gas vortice. Large particles essentially do not respond to the vortex motion within the fluid time scale available and are also not preferentially concentrated. The success of 3D simulation in predicting a two-phase turbulent flow using the Lagrangian trajectory model provides a numerical basis for revisiting the fluid-particle correlations model. In two-fluid model, the fluid phase and particle phase are regarded as two separate continuous flows, which are governed by separate transport equations. The approach has the advantage of a simpler formulation but will lead to closure problems due to fluid-particle correlations. Several second-order closure models for gas-particle covariance are evaluated in the present study. The predicted results by the models are in agreement with the numerical simulation results. However, a proper empirical constant is needed for different cases and there is no formula to determine the constant. A modified model is proposed in this study so that an empirical constant is no longer necessary. The predicted results using our model are as good as those from other models. Therefore, a better closure model is introduced for the gas-particle covariance model.

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