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Masaki Morimoto
Masaki Morimoto
Keio University
Dirección de correo verificada de kflab.jp
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Experimental velocity data estimation for imperfect particle images using machine learning
M Morimoto, K Fukami, K Fukagata
Physics of Fluids 33, 087121, 2021
762021
Convolutional neural networks for fluid flow analysis: toward effective metamodeling and low-dimensionalization
M Morimoto, K Fukami, K Zhang, AG Nair, K Fukagata
Theoretical and Computational Fluid Dynamics 35, 633-658, 2021
752021
Model order reduction with neural networks: Application to laminar and turbulent flows
K Fukami, K Hasegawa, T Nakamura, M Morimoto, K Fukagata
SN Computer Science 2, 1-16, 2021
592021
Generalization techniques of neural networks for fluid flow estimation
M Morimoto, K Fukami, K Zhang, K Fukagata
Neural Computing and Applications, 2021
542021
Supervised convolutional network for three-dimensional fluid data reconstruction from sectional flow fields with adaptive super-resolution assistance
M Matsuo, T Nakamura, M Morimoto, K Fukami, K Fukagata
arXiv preprint arXiv:2103.09020, 2021
302021
Inserting machine-learned virtual wall velocity for large-eddy simulation of turbulent channel flows
N Moriya, K Fukami, Y Nabae, M Morimoto, T Nakamura, K Fukagata
arXiv preprint arXiv:2106.09271, 2021
182021
Assessments of model-form uncertainty using Gaussian stochastic weight averaging for fluid-flow regression
M Morimoto, K Fukami, R Maulik, R Vinuesa, K Fukagata
arXiv preprint arXiv:2109.08248 [physics.flu-dyn], 2021
16*2021
Supervised convolutional networks for vol-umetric data enrichment from limited sec-tional data with adaptive super resolution
M Matsuo, K Fukami, T Nakamura, M Morimoto, K Fukagata
en. In, 5, 2021
32021
Reconstructing Three-Dimensional Bluff Body Wake from Sectional Flow Fields with Convolutional Neural Networks
M Matsuo, K Fukami, T Nakamura, M Morimoto, K Fukagata
SN Computer Science 5 (3), 306, 2024
2024
非線形ダイナミカルシステムに対するニューラルネットワークを用いた異常検知
森本将生, 深見開, 中村太一, 深潟康二
日本機械学会関東支部総会講演会講演論文集 2021.27, 11C07, 2021
2021
Supervised machine learning for wall-modeling in large-eddy simulation of turbulent channel flow
N MORIYA, KAI FUKAMI, Y NABAE, M MORIMOTO, T NAKAMURA, ...
数値流体力学シンポジウム講演論文集 (CD-ROM) 34, 10-2, 2020
2020
Improvement of PIV by data augmentation based on machine learning
M MORIMOTO, KAI FUKAMI, K HASEGAWA, T MURATA, H MURAKAMI, ...
ながれ 39 (2), 84-87, 2020
2020
Three-dimensional flow field reconstruction from two-dimensional sectional data using machine learning
M MATSUO, M MORIMOTO, T NAKAMURA, KAI FUKAMI, K FUKAGATA
数値流体力学シンポジウム講演論文集 (CD-ROM) 34, 6-4, 2020
2020
Convolutional neural network based wall modeling for large eddy simulation in a turbulent channel flow
N Moriya, K Fukami, Y Nabae, M Morimoto, T Nakamura, K Fukagata
APS Division of Fluid Dynamics Meeting Abstracts, R01. 019, 2020
2020
Visualization of internal procedure in neural networks for fluid flows
M Morimoto, K Fukami, K Fukagata
APS Division of Fluid Dynamics Meeting Abstracts, R01. 015, 2020
2020
機械学習に基づくデータ拡張によるPIVの精度向上
森本将生, 深見開, 長谷川一登, 村田高彬, 村上光, 深潟康二
第33回数値流体力学シンポジウム, B09-1, 2019
2019
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
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