A data-driven memory model for solving turbulent flows with the pseudo-direct numerical simulation method |
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Authors: | Axel E. Larreteguy Juan M. Gimenez Norberto M. Nigro Francisco M. Sívori Sergio R. Idelsohn |
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Affiliation: | 1. Universidad Argentina de la Empresa (UADE), Instituto de Tecnología (INTEC), Buenos Aires, Argentina;2. Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Barcelona, Spain;3. Centro de Investigación de Métodos Computacionales (CIMEC, UNL-CONICET), Santa Fe, Argentina;4. CONICET - Universidad Argentina de la Empresa (UADE), Instituto de Tecnología (INTEC), Buenos Aires, Argentina |
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Abstract: | It is well known that the inherent three-dimensional and unsteady nature of turbulent flows is a stumbling block for all approaches aimed at resolving their spatial and temporal variability. The pseudo-direct numerical simulation (P-DNS) method for turbulent flows, proposed by the authors in a previous publication, focused on resolving the spatial variability, leaving the task of solving the temporal evolution to a highly simplified, parameter dependent model, to be adjusted in a case by case basis. Although some auspicious results were obtained, the applicability of P-DNS for problems of industrial interest required a more sophisticated method to deal with the temporal variability. In this sense, the present work proposes a new, parameter free, data-driven memory model for P-DNS. The model is based on the study of off-line DNS solutions of turbulent flows transitioning between statistically steady states in simple domains. The new P-DNS model is tested and successfully compared against existing methods in selected three-dimensional turbulent flows. |
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Keywords: | computational fluid dynamics direct numerical simulation memory fluids multiscale representative volume element turbulence modeling |
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