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#NASA AMES RESEARCH CENTER BADGING OFFICE HOURS HOW TO#

Please ensure that you've muted your microphone in Teams before you select 'Join Now' to enter the meeting lobby.Credits: Science: NASA, ESA, CSA, Cristina Thomas (Northern Arizona University), Ian Wong (NASA-GSFC) image processing: Joseph DePasquale (STScI) You can connect through the desktop Teams App if you have it, or you can select 'Watch on the Web Instead' to enter the meeting as a guest.

To attend an AMS seminar, click on the Microsoft Teams link in the seminar description. In-person participants without NASA badges will need a valid visitor badge (US citizenship or permanent residency is required) to enter the facility. Sessions available to attend in-person will be indicated in the announcement information. These AMS seminars are held in Building N258 in Room 127, just off the front lobby. Her main research is numerical methods for compressible turbulent flow, HPC and the integration of data-driven methods into CFD.įor select seminars, you may wish to attend in-person if you are in the vicinity of NASA Ames Research Center. She is a co-developer and maintainer of the open source high order Discontinuous Galerkin framework FLEXI for multiscale, multiphase and Multiphysics flows. in numerical methods from the University of Stuttgart. in aerospace engineering from Georgia Tech and a Ph.D. While this is work in progress, the presented approach can help reduce uncertainty in LES.Īndrea Beck is a professor for Numerical Methods in Fluid Mechanics at the faculty of Aerospace Engineering and Geodesy and the Center for Simulation Science at the University of Stuttgart. Overall, the results demonstrate that the proposed RL optimization can provide discretization-consistent closures for state of the art high order schemes. I will also explore a novel implicit modelling approach based on a Finite Volume / DG with RL-governed blending.

Our results indicate that an RL-trained eddy viscosity model can adapt to the inhomogeneous dissipation properties of the baseline scheme and give excellent results compared to state of the art models. I will briefly discuss our RL strategy and methods employed as well as present our framework for a solver-in-the-loop on hybrid HPC architectures as well as its application to closure strategies for a discontinuous Galerkin (DG) spectral element scheme for canonical turbulence.

Thus, this approach evaluates and optimizes the model performance in an a posteriori manner. This allows to adjust the model to the actual discretization as it also incorporates the interaction between the discretization and the model itself. For this purpose, the task is formulated as a Markov decision process and solved by Reinforcement Learning (RL).

#NASA AMES RESEARCH CENTER BADGING OFFICE HOURS HOW TO#

In this talk, I will discuss how to find optimal, discretization-specific LES closure strategies. This interaction of the discretized PDE and the model terms contributes to the overall uncertainties of LES and the observed inconsistent closure model performance across schemes and codes. In this so-called implicitly filtered LES, the induced filter kernel and thus the closure terms are determined by the properties of the grid and the discretization operator, leading to additional unclosed computational subgrid terms that are generally unknown in a priori analysis. The vast majority of LES formulation is based on the concept of grid-filtering. Speaker: Andrea Beck, University of Stuttgart

Nasa ames research center badging office hours