26 citations · 56 across the 5 of their papers we have counts for
5 papers
Machine learning approaches to close the filtered two-fluid model for gas-solid flows: Models for subgrid drag force and solid phase stress
Baptiste Hardy, Stefanie Rauchenzauner, Pascal Fede +4
Gas-particle flows are commonly simulated through two-fluid model at industrial-scale. However, these simulations need very fine grid to have accurate flow predictions, which is pr…
Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks
Josh Williams, Haavard Ahlqvist, Alexander Cunningham +7
For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved wit…
pyssam -- a Python library for statistical modelling of biomedical shape and appearance
Josh Williams, Ali Ozel, Uwe Wolfram
pyssam is a Python library for creating statistical shape and appearance models (SSAMs) for biological (and other) shapes such as bones, lungs or other organs. A point cloud best d…
Neural stochastic differential equations for particle dispersion in large-eddy simulations of homogeneous isotropic turbulence
Josh Williams, Uwe Wolfram, Ali Ozel
In dilute turbulent particle-laden flows, such as atmospheric dispersion of pollutants or virus particles, the dynamics of tracer-like to low inertial particles are significantly a…
Charge Transport Equation for Bidisperse Collisional Granular Flows with Nonequipartitioned Fluctuating Kinetic Energy
Lise Ceresiat, Jari Kolehmainen, Ali Ozel
Starting from the Boltzmann-Enskog kinetic equations, the charge transport equation for bidisperse granular flows with contact electrification is derived with separate mean velocit…