Gas-solid fluidized beds have drawn the attention of engineers and researchers as an
effective technology for a large variety of applications, and numerical simulations can play …

The coupling between fluid and granular materials is commonly encountered in nature and
engineering practice. Moreover, the shape of granular materials in practical applications is …

Symbolic regression (SR) is a machine learning-based regression method based on genetic
programming principles that integrates techniques and processes from heterogeneous …

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 last decade, a few of the early attempts to bring CFD-DEM of fluidized beds beyond
the limits of small, lab-scale units to larger scale systems have become popular. The …

Fluid–solid systems play a major role in a wide variety of industries, from pharmaceutical
and consumer goods to chemical plants and energy generation. Along with this variety of …

This study introduces a new point-particle force model that attempts to account for the
hydrodynamic influence of the neighbouring particles in an Eulerian–Lagrangian simulation …

The coupling of computational fluid dynamics (CFD) and discrete element method (DEM)
has become an important method for studying dense fluidized beds. Since DEM can track …

Numerical methods like computational fluid dynamics (CFD) for predicting multiphase flow
involving solid particles potentially offer promising benefits to a wide range of applications …

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 …