A fast particle-locating method is proposed for the hybrid Euler–Lagrangian models on the arbitrary polyhedral mesh, which is of essential importance to improve the computational efficiency by searching the host cells for the tracked particles very efficiently. A background grid, i.e., a uniform Cartesian grid with a grid spacing much smaller than computational mesh, is constructed over the whole computational domain. The many-to-many mapping relation between the computational mesh and the background grid is then specified through a recursive tetrahedron neighbor searching procedure, after the tetrahedral decomposition of computational cells and a mapping inverse operation. Finally, the host cell is straightforwardly identified by the point-in-cell test among the optional elements determined based on the mapping relation. The proposed method is checked on three meshes with different types of the cells and compared with the existing methods in the literatures. The results reveal that the present method is highly efficient and easy to implement on the arbitrary polyhedral mesh.
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