Keigo Matsuda
Cited by
Cited by
Lagrangian tracking simulation of droplet growth in turbulence–turbulence enhancement of autoconversion rate
R Onishi, K Matsuda, K Takahashi
Journal of the Atmospheric Sciences 72 (7), 2591-2607, 2015
Super-resolution simulation for real-time prediction of urban micrometeorology
R Onishi, D Sugiyama, K Matsuda
Sola 15, 178-182, 2019
Challenge toward the prediction of typhoon behaviour and down pour
K Takahashi, R Onishi, Y Baba, S Kida, K Matsuda, K Goto, H Fuchigami
Journal of Physics: Conference Series 454 (1), 012072, 2013
Tree-crown-resolving large-eddy simulation coupled with three-dimensional radiative transfer model
K Matsuda, R Onishi, K Takahashi
Journal of Wind Engineering and Industrial Aerodynamics 173, 53-66, 2018
Turbulence effect on cloud radiation
K Matsuda, R Onishi, R Kurose, S Komori
Physical Review Letters 108 (22), 224502, 2012
A localized turbulent mixing layer in a uniformly stratified environment
T Watanabe, JJ Riley, K Nagata, R Onishi, K Matsuda
Journal of Fluid Mechanics 849, 245-276, 2018
Hairpin vortices and highly elongated flow structures in a stably stratified shear layer
T Watanabe, JJ Riley, K Nagata, K Matsuda, R Onishi
Journal of Fluid Mechanics 878, 37-61, 2019
Influence of microscale turbulent droplet clustering on radar cloud observations
K Matsuda, R Onishi, M Hirahara, R Kurose, K Takahashi, S Komori
Journal of the Atmospheric Sciences 71 (10), 3569-3582, 2014
Divergence and convergence of inertial particles in high-Reynolds-number turbulence
T Oujia, K Matsuda, K Schneider
Journal of Fluid Mechanics 905, A14, 2020
Scale-dependent statistics of inertial particle distribution in high Reynolds number turbulence
K Matsuda, K Schneider, K Yoshimatsu
Physical Review Fluids 6 (6), 064304, 2021
Scale-similar clustering of heavy particles in the inertial range of turbulence
T Ariki, K Yoshida, K Matsuda, K Yoshimatsu
Physical Review E 97 (3), 033109, 2018
Influence of gravitational settling on turbulent droplet clustering and radar reflectivity factor
K Matsuda, R Onishi, K Takahashi
Flow, Turbulence and Combustion 98, 327-340, 2017
Linear and nonlinear inversion schemes to retrieve collision kernel values from droplet size distribution change
R Onishi, K Matsuda, K Takahashi, R Kurose, S Komori
International journal of multiphase flow 37 (2), 125-135, 2011
Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets
K Matsuda, R Onishi
Atmospheric Chemistry and Physics 19 (3), 1785-1799, 2019
Clustering of inertial particles in turbulent flow through a porous unit cell
SV Apte, T Oujia, K Matsuda, B Kadoch, X He, K Schneider
Journal of Fluid Mechanics 937, A9, 2022
Extreme divergence and rotation values of the inertial particle velocity in high Reynolds number turbulence using Delaunay tesselation
T Oujia, K Matsuda, K Schneider
12th International Symposium on Turbulence and Shear Flow Phenomena (TSFP12), 2022
Computing differential operators of the particle velocity in moving particle clouds using tessellations
T Maurel–Oujia, K Matsuda, K Schneider
Journal of Computational Physics 498, 112658, 2024
Super-Resolution of Three-Dimensional Temperature and Velocity for Building-Resolving Urban Micrometeorology Using Physics-Guided Convolutional Neural Networks with Image …
Y Yasuda, R Onishi, K Matsuda
arXiv preprint arXiv:2303.16684, 2023
Multiresolution analysis of inertial particle tessellations for clustering dynamics
K Matsuda, K Schneider, T Oujia, J West, SS Jain, K Maeda
Proceedings of the Summer Program, Stanford University, 2022
Retrieval of collision kernels from the change of droplet size distributions with linear inversion
R Onishi, K Matsuda, K Takahashi, R Kurose, S Komori
Physica Scripta 2008 (T132), 014050, 2008
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