Related references
Note: Only part of the references are listed.Learning nonlocal constitutive models with neural networks
Xu-Hui Zhou et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2021)
Machine Learning for Fluid Mechanics
Steven L. Brunton et al.
ANNUAL REVIEW OF FLUID MECHANICS, VOL 52 (2020)
Physics-informed neural networks for high-speed flows
Zhiping Mao et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2020)
Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical systems
Jin-Long Wu et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2020)
Turbulence Modeling in the Age of Data
Karthik Duraisamy et al.
ANNUAL REVIEW OF FLUID MECHANICS, VOL 51 (2019)
A high-bias, low-variance introduction to Machine Learning for physicists
Pankaj Mehta et al.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS (2019)
A hybrid point-particle force model that combines physical and data-driven approaches
W. C. Moore et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2019)
Prediction of aerodynamic flow fields using convolutional neural networks
Saakaar Bhatnagar et al.
COMPUTATIONAL MECHANICS (2019)
Lagrangian investigation of pseudo-turbulence in multiphase flow using superposable wakes
W. C. Moore et al.
PHYSICAL REVIEW FLUIDS (2019)
Computing curvature for volume of fluid methods using machine learning
Yinghe Qi et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2019)
tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow
You Xie et al.
ACM TRANSACTIONS ON GRAPHICS (2018)
Pairwise-interaction extended point-particle model for particle-laden flows
G. Akiki et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2017)
Pairwise interaction extended point-particle model for a random array of monodisperse spheres
G. Akiki et al.
JOURNAL OF FLUID MECHANICS (2017)
Immersed boundary method with non-uniform distribution of Lagrangian markers for a non-uniform Eulerian mesh
G. Akiki et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2016)
Force variation within arrays of monodisperse spherical particles
G. Akiki et al.
PHYSICAL REVIEW FLUIDS (2016)
Drag correlation for dilute and moderately dense fluid-particle systems using the lattice Boltzmann method
Simon Bogner et al.
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW (2015)
Direct numerical simulation of moderate-Reynolds-number flow past arrays of rotating spheres
Qiang Zhou et al.
PHYSICS OF FLUIDS (2015)
A New Drag Correlation from Fully Resolved Simulations of Flow Past Monodisperse Static Arrays of Spheres
Y. (Yali) Tang et al.
AICHE JOURNAL (2015)
A new relation of drag force for high Stokes number monodisperse spheres by direct numerical simulation
Ali Abbas Zaidi et al.
ADVANCED POWDER TECHNOLOGY (2014)
Lattice-Boltzmann simulation of fluid flow through packed beds of uniform spheres: Effect of porosity
L. W. Rong et al.
CHEMICAL ENGINEERING SCIENCE (2013)
Drag law for monodisperse gas-solid systems using particle-resolved direct numerical simulation of flow past fixed assemblies of spheres
S. Tenneti et al.
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW (2011)
Turbulent Dispersed Multiphase Flow
S. Balachandar et al.
ANNUAL REVIEW OF FLUID MECHANICS (2010)
VORO plus plus : A three-dimensional Voronoi cell library in C plus
Chris H. Rycroft
CHAOS (2009)
Drag force of intermediate Reynolds number flow past mono- and bidisperse arrays of spheres
R. Beetstra et al.
AICHE JOURNAL (2007)
An immersed boundary method with direct forcing for the simulation of particulate flows
M Uhlmann
JOURNAL OF COMPUTATIONAL PHYSICS (2005)
Hydrodynamic and transport properties of packed beds in small tube-to-sphere diameter ratio: pore scale simulation using an Eulerian and a Lagrangian approach
P Magnico
CHEMICAL ENGINEERING SCIENCE (2003)
Share Paper
