Euler-Lagrange simulation of dense gas-solid flow with local grid refinement

Euler-Lagrange method is powerful for studying dense gas-solid flow, where the Eulerian grid is typically 3-5 times of particle diameter to ensure the accuracy of information mapping between gas and solid phases. This condition limits its applications in simulating reactors with complex geometries which require the use of Eulerian grids that are comparative to or smaller than particle diameter. In this study, eight methods for mapping discrete particle information to continuous fluid field were compared first via the simulation of a packed bed, their pros and cons were analyzed and discussed in detail; A kernel function method (the normalized kernel function method II, NKFMII) was then selected to simulate the hydrodynamics and heat transfer of gas-solid bubbling fluidized beds, the results not only validated NKFMII for interphase information mapping but also indicated that a grid-size-independent solution can be achieved; Finally, in order to balance the computational efficiency and accuracy a hybrid particle centroid method (PCM) and NKFMII method was proposed to achieve the interphase information mapping and then to simulate the hydrodynamics of a fluidized bed with immersed tubes, the ability of local grid refinement and the effectiveness of the coupled PCM and NKFMII method were demonstrated. This study proved that Euler-Lagrange simulation with local grid refinement is able to simulate gas-solid reactors with complex geometries. (c) 2022 Elsevier B.V. All rights reserved.

Automated summary

The Euler-Lagrange method is powerful for studying dense gas-solid flow but is limited in simulating reactors with complex geometries. This study compared eight methods for mapping particle information to fluid field and proposed a kernel function method (NKFMII) for interphase information mapping. The study demonstrated the ability of local grid refinement and the effectiveness of the coupled PCM and NKFMII method.