Gas-solid fluidization technology has been commercialized in many industrial applications
since its implementation in the fluid catalytic cracking process in the early 1940s, however …

In the past few decades, multi-scale numerical methods have been developed to model
dense gas-solid flow in fluidized beds with different resolutions, accuracies, and efficiencies …

Abstract Machine learning (ML) is experiencing an immensely fascinating resurgence in a
wide variety of fields. However, applying such powerful ML to construct subgrid interphase …

This article reviews the general features of the multiscale structures in particle–fluid systems
and the characterization, modeling, and simulation methods for these systems. The …

This study presents conventional and artificial neural network‐based data‐driven modeling
(DDM) methods to model simultaneously the filtered mesoscale drag, heat transfer and …

Filtered two-fluid model (fTFM) for gas-particle flows require closures for the sub-filter scale
corrections to interphase drag force and stresses, the former being more significant. In this …

This study develops filtered two-fluid model (fTFM) closures by coupling computational fluid
dynamics (CFD) and deep learning algorithm (DL) for enabling coarse-grid simulations at …

Simulations of large-scale gas-particle flows using coarse meshes and the filtered two-fluid
model approach depend critically on the constitutive model that accounts for the effects of …

A fluidized bed of Geldart-A particles is promoted as heat transfer fluid in the tubular solar
receivers of solar towers. A pressure-driven upward particle flow affects the hydrodynamic …

Developing, verifying and validating sub-grid methods is of crucial significance for enabling
accurate coarse-grained two-fluid modeling of rapid gas-fluidized flows. However, very few …