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Numerical Simulation of Particle-Laden Turbulent Flows Using LES

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Abstract

The paper is concerned with the simulation of particle-laden two-phase flows based on the Euler-Lagrange approach. The methodology developed is driven by two compulsory requirements: (i) the necessity to tackle complex turbulent flows by eddy-resolving schemes such as large-eddy simulation (LES); (ii) the demand to predict dispersed multiphase flows at high mass loadings. First, a highly efficient particle tracking algorithm was developed working on curvilinear, block-structured grids in general complex 3D domains. Second, to allow the prediction of dense two-phase flows, the fluid-particle interaction (two-way coupling) as well as particle-particle collisions (four-way coupling) had to be taken into account. For the latter instead of a stochastic collision model, in the present study a deterministic collision model is considered. Nevertheless, the computational burden is minor owing to the concept of virtual cells, where only adjacent particles are taken into account in the search for potential collision partners. The methodology is applied to different test cases. Here results of the two-phase flows in a plane channel and in a model combustion chamber are reported. The influence of particle-fluid (two-way coupling) as well as particle-particle interactions (four-way coupling) is investigated for a mass loadings of 22%. The computational results are compared with experimental measurements and an encouraging agreement is found. Results for a higher mass loading of 110% will be published in a subsequent report. The methodology developed will be further extended in the near future, e.g., to account for rough walls. Then even more challenging test cases will be tackled.

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Breuer, M., Alletto, M. (2012). Numerical Simulation of Particle-Laden Turbulent Flows Using LES. In: Nagel, W., Kröner, D., Resch, M. (eds) High Performance Computing in Science and Engineering '11. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23869-7_25

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