Wednesday, March 24th, 2021. Time: 12 noon
ONLINE! - Link for online session: https://meet.google.com/qjo-sttx-dgo
Pseudo-DNS (P-DNS) is a multiscale methodology developed with the aim of reproducing the reliable solutions of the direct numerical simulation (DNS) but easing its computational burden. In P-DNS, both the coarse and the fine scales are solved numerically without including any additional model. The most expensive part of the computations, the solutions of the fine-scale, are parametrized to be performed offline and store their results in dimensionless databases. This latter allows us to construct synthetic models to emulate the fine-scale behavior when global solutions are computed.
In this talk, an introduction of the methodology is presented through the solution of the equations for scalar transport and homogeneous turbulent flows, and evaluated in some standard benchmarks where advantages over other numerical approaches are established. Also, the first attempts towards the application of the methodology to the treatment of multiphase turbulent flows are shown. Here, the turbulence modulation phenomenon is discussed and solutions obtained are compared with predictions from the bibliography.
Juan Marcelo Giménez
Informatics Engineering (2011), M.Sc. in Computation (2014) and Ph.D. in Engineering (2015, mention Computational Mechanics) by the Universidad Nacional del Litoral of Santa Fe, Argentina. He is a Severo Ochoa's postdoctoral researcher at CIMNE and has an Adjoint Researcher position in CONICET (Argentina). He has worked on topics as particle methods (PFEM-2, PFVM), turbulence modeling, HPC, and machine learning, with a special interest in technology development and transfer. His current research is focused on the development of multiscale Lagrangian-Eulerian methodologies for the simulation of multiphase and turbulent flows.