20 mai 2021

Webinaire Charles Meneveau

Charles Meneveau is the Louis M. Sardella Professor in the Department of Mechanical Engineering, is Associate Director of the Institute for Data Intensive Engineering and Science (IDIES) and is jointly appointed as Professor in the Department of Physics and Astronomy at Johns Hopkins. He received his B.S. degree in Mechanical Engineering from the Universidad Técnica Federico Santa María in Valparaíso, Chile, in 1985 and M.S, M.Phil. and Ph.D. degrees from Yale University in 1987, 1988 and 1989, respectively. During 1989/90 he was a postdoctoral fellow at the Center for Turbulence Research at Stanford. He has been on the Johns Hopkins faculty since 1990 and during 2000 he was on sabbatical at Ecole Centrale de Paris. His area of research is focused on understanding and modeling hydrodynamic turbulence, and complexity in fluid mechanics in general. The insights that have emerged from Professor Meneveau’s work have led to new numerical models for Large Eddy Simulations (LES) and applications in engineering and environmental flows, including wind farms. He also focuses on developing methods to share the very large data sets that arise in computational fluid dynamics. He is Deputy Editor of the Journal of Fluid Mechanics and has served as the Editor-in-Chief of the Journal of Turbulence. Professor Meneveau is a member of the US National Academy of Engineering, a foreign corresponding member of the Chilean Academy of Sciences, a Fellow of APS, ASME, AMS and recipient of the Stanley Corrsin Award from the APS, the JHU Alumni Association's Excellence in Teaching Award, and the APS' François N. Frenkiel Award for Fluid Mechanics.
An Update on a Turbulence Database and its Application to Elucidating Geometric Scaling Properties of Turbulent Spots During Boundary Layer Bypass Transition

Abstract: In this presentation, an update on a turbulence database system is provided, together with a sample application to a transitional boundary layer flow focusing on scaling properties of turbulent spots during boundary layer transition. The Johns Hopkins Turbulence Databases (JHTDB) exposes large-scale turbulent data to the research community while at the same time providing easy-to-use client interfaces based on Web Services that act as “virtual flow sensors” that can be placed in the turbulent flows. This approach has greatly facilitated retrieving and interacting with the data. At present JHTDB contains over 1/2 Petabyte of data from various turbulent flow simulations. The data have been used in over 150 peer-reviewed journal publications on turbulence from authors world-wide. We also present an application of the transitional (by-pass) boundary layer dataset contained in JHTDB. Specifically, we develop a new approach to detect the interface that separates the turbulent boundary layer from the laminar or outer regions of the flow using machine learning. A self-organized map based clustering method is shown to enable determination of the interface without having to prescribe arbitrary threshold values as traditional interface detection methods require. Scaling properties of the interface are studied and links to fractal properties of turbulent non-turbulent interfaces in high Reynolds number flows are established. This work has been performed with Drs. Zhao Wu and Tamer Zaki, while the database (supported by the NSF) has resulted from a long-term collaboration with the JHTDB team.

20 mai 2021, 16h3017h30
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08 décembre 2022

Webinaire Fabian Denner

Fabian Denner a obtenu son doctorat à l'Imperial College de Londres en 2013 sur les méthodes numériques pour les écoulements multiphasiques avec tension de surface, suivi d'un post-doc à l'Imperial College. En 2015, Fabian a obtenu une bourse prestigieuse

Fabian Denner a obtenu son doctorat à l'Imperial College de Londres en 2013 sur les méthodes numériques pour les écoulements multiphasiques avec tension de surface, suivi d'un post-doc à l'Imperial College. En 2015, Fabian a obtenu une bourse prestigieuse du Conseil de recherche en ingénierie et en sciences physiques (EPSRC) du Royaume-Uni, avec laquelle il a poursuivi ses travaux fructueux sur les écoulements avec tension de surface et a étendu ses recherches à de nouveaux domaines, tels que les écoulements compressibles et chargés de tensioactifs. Depuis 2018, Fabian est professeur junior de modélisation des écoulements multiphasiques à l'Otto-von-Guericke-Université de Magdebourg (Allemagne). Ses recherches tournent autour du développement de méthodes numériques et d'outils logiciels pour prédire les écoulements multiphasiques, et de l'application de ces méthodes pour répondre aux questions liées à la physique et aux applications de ces écoulements. Actuellement, les travaux de Fabian se concentrent sur les écoulements interfaciaux avec des surfactants, les écoulements viscoélastiques, les écoulements multiphasiques dans les applications biomédicales, ainsi que sur la cavitation et l'acoustique.