Kazuki Maeda

Kazuki Maeda

Stanford University

H-index: 11

North America-United States

About Kazuki Maeda

Kazuki Maeda, With an exceptional h-index of 11 and a recent h-index of 11 (since 2020), a distinguished researcher at Stanford University, specializes in the field of Fluid Mechanics, Propulsion, Hypersonics, Computational Science, Cavitation.

His recent articles reflect a diverse array of research interests and contributions to the field:

Regressing bubble cluster dynamics as a disordered many-body system

Clustering, rotation, and swirl of inertial particles in turbulent channel flow

Neural network models for preferential concentration of particles in two-dimensional turbulence

Investigation on population-based optimization of complex flows

An integrated heterogeneous computing framework for ensemble simulations of laser-induced ignition

Scale-dependent divergence of inertial particle velocity in isotropic turbulence

A heterogeneous computing approach to coupled simulation and machine-learning deployment for high-speed flows

Physics-informed neural networks for synthesizing preferential concentration of particles in turbulent flows

Kazuki Maeda Information

University

Position

Center for Turbulence Research

Citations(all)

719

Citations(since 2020)

548

Cited By

342

hIndex(all)

11

hIndex(since 2020)

11

i10Index(all)

13

i10Index(since 2020)

12

Email

University Profile Page

Google Scholar

Kazuki Maeda Skills & Research Interests

Fluid Mechanics

Propulsion

Hypersonics

Computational Science

Cavitation

Top articles of Kazuki Maeda

Regressing bubble cluster dynamics as a disordered many-body system

Journal of Fluid Mechanics

2024/4

Kazuki Maeda
Kazuki Maeda

H-Index: 8

Daniel Fuster
Daniel Fuster

H-Index: 19

Clustering, rotation, and swirl of inertial particles in turbulent channel flow

International Journal of Multiphase Flow

2024/2/13

Neural network models for preferential concentration of particles in two-dimensional turbulence

arXiv preprint arXiv:2312.14829

2023/12/22

Investigation on population-based optimization of complex flows

Bulletin of the American Physical Society

2023/11/20

Kazuki Maeda
Kazuki Maeda

H-Index: 8

An integrated heterogeneous computing framework for ensemble simulations of laser-induced ignition

2023

Scale-dependent divergence of inertial particle velocity in isotropic turbulence

Bulletin of the American Physical Society

2022/11/21

A heterogeneous computing approach to coupled simulation and machine-learning deployment for high-speed flows

Bulletin of the American Physical Society

2022/11/21

Kazuki Maeda
Kazuki Maeda

H-Index: 8

Physics-informed neural networks for synthesizing preferential concentration of particles in turbulent flows

Bulletin of the American Physical Society

2022/11/20

On divergence, curl, and helicity of the inertial particle velocity in a 4-way coupled channel flow

Bulletin of the American Physical Society

2022/11/20

Development of Large-Eddy Simulation Combustion Models for Thermodiffusive Instabilities in Turbulent Hydrogen Flames

Center for Turbulence Research, Proceedings of the Summer Program 2022

2022

Flow physics characterization of microconfined high-pressure transcritical fluids turbulence

Proceedings of the Summer Program

2022

Francesco Capuano
Francesco Capuano

H-Index: 9

Kazuki Maeda
Kazuki Maeda

H-Index: 8

Divergence and curl of the inertial particle velocity in a four-way coupled turbulent channel flow

Center for Turbulence Research, Proceedings of the Summer Program 2022

2022

Multiresolution analysis of inertial particle tessellations for clustering dynamics

Center for Turbulence Research, Proceedings of the Summer Program 2022

2022

Viscid–inviscid interactions of pairwise bubbles in a turbulent channel flow and their implications for bubble clustering

Journal of Fluid Mechanics

2021/7

Kazuki Maeda
Kazuki Maeda

H-Index: 8

On the cloud interaction parameter and its connections with the coherence and discrete spectrum of bubble cloud dynamics

2021/5/10

Kazuki Maeda
Kazuki Maeda

H-Index: 8

Daniel Fuster
Daniel Fuster

H-Index: 19

Controlling the dynamics of cloud cavitation bubbles through acoustic feedback

Physical Review Applied

2021/3/11

Kazuki Maeda
Kazuki Maeda

H-Index: 8

Application-oriented investigation of task-based ensemble co-processing on heterogeneous supercomputers

Center for Turbulence Research Annual Research Briefs

2021

Assessment of a high-order curvilinear finite-difference method for compressible reacting flows

Center for Turbulence Research Annual Research Briefs

2021

Analysis of core-noise contributions in a realistic gas-turbine combustor operated near lean blow-out

Proceedings of the Combustion Institute

2021/1/1

Kazuki Maeda
Kazuki Maeda

H-Index: 8

Matthias Ihme
Matthias Ihme

H-Index: 35

A task-based parallel framework for ensemble simulations of rocket ignition

APS Division of Fluid Dynamics Meeting Abstracts

2021

See List of Professors in Kazuki Maeda University(Stanford University)