New spatial decomposition method for accurate, mesh-independent agglomeration predictions in particle-laden flows
نویسندگان
چکیده
This article presents a new data-driven spatial decomposition algorithm that allows the splitting of domain containing point particles into elementary cells, each cell spatially-uniform distribution particles. For purpose, relies on use statistical information for and then extracts an optimal decomposition. After evaluating convergence accuracy homogeneous inhomogeneous cases, this is applied to study case particle agglomeration. Indeed, in CFD context, recent developments numerical simulations agglomeration complex turbulent flows increasingly resort Euler-Lagrange approaches. These methods are coupled with population balance equation (PBE)-like algorithms compute inside Eulerian mesh. One key issues such approaches related condition, i.e. should be computed set uniformly distributed locally cell. Yet, realistic industrial/environmental cases often involve non-homogeneous concentrations (due local injection or accumulation specific regions). We show more accurate mesh-independent predictions made possible by application algorithm.
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ژورنال
عنوان ژورنال: Applied Mathematical Modelling
سال: 2021
ISSN: ['1872-8480', '0307-904X']
DOI: https://doi.org/10.1016/j.apm.2020.08.064