Uncertainty Quantification Analysis of DNS Data with RANS-DNS Simulations

Speaker: Svetlana V. Poroseva, Department of Mechanical Engineering, University of New Mexico
March 2, 2017

Presentation

Abstract

In RANS-DNS simulations of incompressible turbulent flows, the Reynolds-averaged Navier-Stokes (RANS) equations are solved, with all terms but molecular diffusion being represented by the data from Direct Numerical Simulations (DNS). No turbulence modeling is involved in such simulations. Results of RANS-DNS simulations conducted with four DNS datasets in planar wall-bounded flows – Sillero et al. (2013), Lee & Moser (2015), Jeyapaul et al. (2015), Poroseva et al. (2016) – will be presented and discussed. In particular, it will be shown that the results of RANS-DNS simulations are in a strong disagreement with the DNS profiles for velocity moments, and that the dominant uncertainty source in such simulations is the DNS data inaccuracies. A contribution of statistical errors in DNS data to the accuracy of RANS-DNS simulation results will also be demonstrated. RANS simulations were conducted with the open-source software OpenFOAM.

Biography

Svetlana Poroseva is an Associate Professor at the Mechanical Engineering Department of the University of New Mexico. She holds a Ph.D. in fluid and plasma mechanics and an M.S. degree in physics from the Novosibirsk State University (Russia). Her current research is focused on developing physics-based turbulence models, DNS, uncertainty analysis in turbulent flow simulations, and efficient rotor design for small rotorcrafts. Prior joining UNM, she was affiliated with the Center for Turbulence Research at the Stanford University, Aerospace Engineering Department at the Texas A&M University, and the Center for Advanced Power Systems and the School of Computational Science at the Florida State University. She is an Associate Fellow of AIAA, a member of AIAA Fluid Dynamics TC and TMBWG, also APS DFD, SWE, as well as a Honorary Member of the Pi Tau Sigma Society.

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