(140f) Euler-Euler Anisotropic Gaussian Mesoscale Direct Numerical Simulation of Cluster-Induced Turbulent Flow

Gas-particle flows are common in many fields of engineering, such as in fluidized beds and risers, which are widely used in a variety of chemical processes. The accurate simulation of such flows is crucial for the design and optimization of their industrial applications. Although gas-particles flows in industrial applications are often turbulent, available multiphase turbulence models in commercial CFD codes often lack a rigorous conceptual foundation. In our previous works, the exact Reynolds-averaged (RA) equations were derived for the particle phase in a collisional gas-particle flow (Fox, 2014), and detailed Euler-Lagrange particle simulations of cluster-induced turbulence (CIT) were performed to aid the development of this model (Capecelatro et.al. 2013, 2014). However, sophisticated filtering techniques have to be used to extract particle-phase information consistent with the Eulerian turbulence model from Euler-Lagrange simulations, and the results can be sensitive to various aspects of the filtering process. By comparison, Euler-Euler approaches of gas-particle flows can directly provide particle-phase turbulence statistics, and are well suited for high performance computations. In the current work, a novel Euler-Euler Anisotropic Gaussian approach (EE-AG), in which particle velocities are assumed to follow a multi-variate anisotropic Gaussian distribution, is used to perform mesoscale DNS of CIT cases, which were studied in our previous Euler-Lagrange simulations. A constant Stokes drag model is used to compute the momentum exchange between phases. A three-dimension Hermite Quadrature formulation is used to calculate kinetic flux for ten velocity moments in a finite-volume frame work. The Bhatnagar-Gross-Krook (BGK) model is applied here to account for the inelastic particle collisions. Finally, the particle-phase volume-fraction and momentum equations are coupled with the Eulerian solver for the gas phase. This approach is implemented in an open-source CFD package, and detailed simulation results are compared with Euler-Lagrange simulations. The results demonstrat that the AG assumption for particle velocity is valid and this novel method can be used to perform mesoscale DNS for gas-particle flows. The advantage of EE-AG approach over traditional kinetic theory model with two-fluid method approach (KT-TFM) in gas-particle flow simulation will also be discussed.