220921.jpg

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

2022-12-16ConferenceIshize (M1) and Omichi (B4) made presentations at 36th CFD Symposium (online).
2022-12-10221210-suzuki.jpgSuzuki (B4) received the Outstanding Presentation Award at 28th Inter-University Workshop on Turbulence Control (Tokyo).
2022-12-05ConferenceFukagata gave a special lecture at 12th Syposium on Compuational Mechanics, Science Council of Japan (Tokyo).
2022-10-14220929-fujima.jpgFujima (M2) received Japan Society of Fluid Mechanics Outstanding Young Presenter Award.
2022-09-29220929.jpgFujima (M2) and Sato (M2) made presentations at JSFM Annual Meeting 2022 (Kyoto).
2022-09-12ConferenceIshize (M1) and Miura (M1) made presentations at Mechanical Engineering Congress, 2022 Japan (MECJ-22) (Toyama).
2022-08-01ConferenceFujima (M2), Matsuo (M2), Sato (M2), Chida (M1), and Miura (M1) made presentations at WCCM-APCOM 2022, Yokohama (Online).
2022-07-23Out now!M. Morimoto, K. Fukami, R. Maulik, R. Vinuesa, and K. Fukagata, "Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression," Physica D 440, 133454 (2022).
2022-07-20ConferenceOkochi (M2) and Nabae (Alumni) made presentations at TSFP12, Osaka (Online).
2022-06-25Out now!M. Morimoto, K. Fukami, R. Maulik, R. Vinuesa, and K. Fukagata, Featured Research in CFD35: "Model-form uncertainty quantification in neural-network-based fluid-flow estimation," Nagare - J. Jpn. Soc. Fluid Mech. 41, 89-92 (2022).
2022-06-22Out now!Y. Nabae and K. Fukagata, "Drag reduction effect of streamwise traveling wave-like wall deformation with spanwise displacement variation in turbulent channel flow," Flow Turbul. Combust. 109, 11751194 (2022).
2022-05-31Out now!T. Nakamura and K. Fukagata, "Robust training approach of neural networks for fluid flow state estimations," Int. J. Heat Fluid Flow 96, 108977 (2022).
2022-05-26ConferenceFukagata gave an invited lecture at ParCFD 2022 (Alba, Italy (Hybrid)).

Old news

Visitors: 8 today, 204912 since 2009-03-31

Last-modified: 2022-12-22 (Thu) 11:10:07 (49d)
Copyright © 2007-2023 Fukagata Lab., Keio University, All rights reserved.