A data‐driven memory model for solving turbulent flows with the pseudo‐direct numerical simulation method

• Published in: International journal for numerical methods in fluids Vol. 95; no. 1; pp. 44 - 80
• Main Authors: Larreteguy, Axel E., Gimenez, Juan M., Nigro, Norberto M., Sívori, Francisco M., Idelsohn, Sergio R.
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01.01.2023
• Subjects: computational fluid dynamics; Direct numerical simulation; Domain names; Fluid dynamics; Mathematical models; memory fluids; Methods; multiscale; Parameters; representative volume element; Simulation; Spatial variations; Temporal variations; turbulence modeling
• ISSN: 0271-2091; 1097-0363
• DOI: 10.1002/fld.5139

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. A novel, parameter‐free, data‐driven memory model is introduced for the solution of the temporal evolution of turbulent flows with the P‐DNS multiscale approach. The predictive model is based on the compilation of off‐line DNS solutions of turbulent flows in simple domains transitioning between statistically steady states. The new P‐DNS model is tested and successfully compared against existing methods in selected three‐dimensional turbulent flows.