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Welcome to Keio Univ. Fukagata Laboratory!

Fukagata laboratory, Department of Mechanical Engineering, Keio University, is a relatively new (?) laboratory, born in 2007.

Our research interests are numerical simulation and mathematical modeling of complex heat and fluid flow phenomena including turbulent flows and development of advanced control methods for such flow phenomena. The research area is being expanded toward establishment of design methodology for thermo-fluids systems by integrating control theories, optimization methods, machine learning, and large-scale flow simulation techniques.

News

2024-06-22240622-oura.jpgOura (D2) received Best Presentation Award at 34th Inter-University Workshop on Turbulence Control (Yokohama).
2024-04-16240502-hirota.jpgHirota (B4 at that time) received the Best Presentation Award at 63rd JSME Kanto Student Union Conference.
2024-03-25240325-oishi.jpgOishi (B4) received The Best Bachelor Thesis Presentation Award from Department of Mechanical Engineering, Keio University.
2024-03-13240313.jpgOishi (B4), Saeki (B4), Takagi (B4), Hirota (B4), and Funai (B4) made presentations at 63rd JSME Kanto Student Union Conference (Tokyo).
2024-03-11AwardTakagi (B4) received the Outstanding Presentation Award at 33rd Inter-University Workshop on Turbulence Control (Tokyo).
2024-03-07Out now!M. Matsuo, K. Fukami, T. Nakamura, M. Morimoto, and K. Fukagata, "Reconstructing three-dimensional bluff body wake from sectional flow fields with convolutional neural networks, SN Comput. Sci. 5, 306 (2024).
2024-03-04240304.jpgIwasawa (M1) made a presentation at FY2023 AICE Annual Meeting (Tokyo).
2024-01-22Out now!K. Fukagata, K. Iwamoto, and Y. Hasegawa, "Turbulent drag reduction by streamwise traveling waves of wall-normal forcing," Annu. Rev. Fluid Mech. 56, 69-90 (2024).
2024-01-13Out now!Y. Nabae and K. Fukagata, "Theoretical and numerical analyses of turbulent plane Couette flow controlled using uniform blowing and suction," Int. J. Heat Fluid Flow 106, 109286 (2024).
2023-12-22231222.jpgIshize (M2) received the Outstanding Presentation Award at 32nd Inter-University Workshop on Turbulence Control (Tokyo).
2023-12-17231216.jpgIshize (M2), Miura (M2)シ薫ishi (B4), Saeki (B4), and Takagi (B4) made presentations at CFD37 (Nagoya).
2023-11-21231121.jpgChida (M2), Ishize (M2), Miura (M2), and Omichi (M1) made presentations at APS-DFD 2023 (Washington DC).
2023-11-16PreprintT. Ishize, H. Omichi, and K. Fukagata, "Flow control by a hybrid use of machine learning and control theory," arXiv preprint, arXiv:2311.08624 [physics.flu-dyn].
2023-11-16PreprintR. Miura and K. Fukagata, "Semi-supervised machine learning model for Lagrangian flow state estimation," arXiv preprint, arXiv:2311.08754 [physics.flu-dyn].
2023-11-16PreprintH. Omichi, T. Ishize, and K. Fukagata, "Machine learning based dimension reduction for a stable modeling of periodic flow phenomena," arXiv preprint, arXiv:2311.08765 [physics.flu-dyn].
2023-10-30Out now!K. Fukagata, "Fundamentals of machine learning and its applicatios to fluid flow problems," Turbomachinery 51(11), 10-16 (2023) (in Japanese).

Old news

Visitor: 222508 since 2009-03-31

Last-modified: 2024-06-24 (Mon) 13:44:32