Vorhersage der Turbulenz in Reaktoren und Motoren : High-Performance Computing in der Strömungssimulation

Kempf, Andreas M. LSF; Proch, Fabian GND; Rittler, Andreas GND; Rieth, Martin GND; Nguyen, Thuong M. GND

Die möglichst akkurate Vorhersage des Strömungsverhaltens von Fluiden ist nach wie vor eine der größten Herausforderungen der Ingenieurwissenschaften. Hier setzt die Arbeitsgruppe von Andreas Kempf an.

The accurate prediction of fluid flows is still one of the most challenging engineering problems. This is due to the turbulent nature of fluid flows that can only be resolved by numerical simulations for small and simplified problem sizes, even with the massive computational resources that are available today. When chemical reactions and combustion processes are involved, the computational costs become even larger due to the stiff and non-linear interaction between turbulence and chemistry. Therefore, reduction techniques have been developed in the past, namely the Reynolds averaged Navier-Stokes (RANS) and the large-eddy simulation technique (LES). The latter has the potential to describe the turbulent combustion process more precisely, but still requires models for the unresolved turbulent scales. These models are developed in the group of Prof. Kempf at the University of Duisburg- Essen, where a broad range of applications is covered. Examples are the combustion of coal, the synthesis of nano-particles in flames, and the combustion processes in internal combustion engines. To perform the required simulations on the largest supercomputers in the world, the group has developed its own inhouse code that is suitable for massively parallel simulations.



Citation style:
Kempf, A.M., Proch, F., Rittler, A., Rieth, M., Nguyen, T.M., 2017. Vorhersage der Turbulenz in Reaktoren und Motoren: High-Performance Computing in der Strömungssimulation. Natur-, Ingenieur- und Wirtschaftswissenschaften - High-Performance und Cloud Computing. https://doi.org/10.17185/duepublico/70374
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