OIST-Keio Showcase Talk Series Vol. 10: Diverse Approaches to Fluid Dynamics"
Description
Title
OIST-Keio Showcase Talk Series Vol. 10: Diverse Approaches to Fluid Dynamics
Symposium Abstract
The 10th OIST-Keio Joint Symposium brings together various perspectives on fluid dynamics, highlighting recent advances across theory, computation, and experiment. Through a series of focused talks and poster presentations, the event spans fundamental flow phenomena, complex and multiscale fluids, and engineering‑relevant applications. This 10th showcase continues a series of events bringing Keio and OIST researchers together to foster discussion and enable innovation through interdisciplinary collaboration.
Registration
Deadline: Wednesday, March 4Program
Coming soon
Keio University Speaker
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1 |
Dr. Satoko Fujioka Associate Professor |
Faculty of Science and Technology, Department of Applied Chemistry
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Dr. Koji Fukagata Professor
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Faculty of Science and Technology, Department of Mechanical Engineering Koji Fukagata received his PhD at KTH (Sweden) as well as The University of Tokyo (Japan) in 2000. Since he moved to Keio University in 2007, he has worked in diverse fields of fluid mechanics including flow control and machine learning. He has served as an editor of Flow, Turbulence and Combustion (Springer-Nature) since 2015, and currently he is a Director of the Japan Society of Fluid Mechanics (JSFM), the Chair of the Fluids Engineering Division of the Japan Society of Mechanical Engineers (JSME-FED), and also serving as the Advisor for JST PRESTO and JST FOREST. |
Flow control studies at Keio University Friction drag in turbulent flow is much larger than that of the laminar flow at the same Reynolds number, and its reduction is of crucial importance for improving the energy efficiency of industrial products and mitigating environmental burden. My talk will begin with our early attempts on feedback control for turbulent friction drag reduction, then I present our recent attempts on predetermined control using streamwise traveling waves. I will also briefly introduce our ongoing attempts for flow control design based on machine learning.
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2 |
Dr. Yutaka Kazoe Professor
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Faculty of Science and Technology, Department of System Design Engineering
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4 |
Dr. Norihiko Sugimoto Professor
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Faculty of Law / Research and Education Center for Natural Sciences Norihiko Sugimoto received BA, MSci, and PhD from the Kyoto University. In 2005, he moved to Nagoya University as a post-doctoral fellow. He joined to Keio University in 2008 as a lecturer and was promoted to associate professor in 2015, and professor in 2020. His current research focuses on the geophysical fluid dynamics and Venus atmosphere and has published >50 papers in this area of research. He is an Associate Editor for Journal of Geophysical Research: Planets of the American Geophysical Union and SOLA (Scientific Online Letters on the Atmosphere) of the Meteorological Society of Japan. |
Numerical study of the general circulation of the Venus Atmosphere We have released the first analysis dataset for the Venus atmosphere, in which horizontal winds derived by ultra-violet images observed by the Venus climate orbiter “Akatsuki” were assimilated. In the analysis, super-rotation and cold collar consistent with observations has been reproduced. We will introduce recent results of Venusian general circulation model (AFES-Venus; Atmospheric GCM for the Earth Simulator for Venus) and the data assimilation system for the Venus atmosphere (ALEDAS-V; AFES-LETKF (Local Ensemble Transform Kalman Filter) data assimilation system for Venus).
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OIST Speaker
| Speakers | Affiliation | Talk Title/Abstract | |
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1 |
Dr. Pinaki Chakraborty Professor
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Dr. Eliot Fried Professor
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3 |
Dr. Marco Edoardo Rosti Associate Professor
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4 |
Dr. Amy Shen Professor
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Poster Presenter
Coming soon
Co-hosts
Contact
Please email academic-partnerships@oist.jp if you have any questions.
※ Please note that this event may be recorded, and the videos may be uploaded by OIST/Keio U. Additionally, photos may be taken during the event for publication online (e.g., the OIST website, social media, etc.). Any non-published information will not be shared. ※Add Event to My Calendar
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