MRI-Validated CFD-DEM Simulation of Bubbling Fluidized Beds: Drag Model Selection and Computational Speedup via Recurrence-Based CFD

MRI-Validated CFD-DEM and rCFD Dataset for Gas-Solid Fluidized Beds

This comprehensive research dataset provides complete computational and experimental data for validating coupled CFD-DEM (Computational Fluid Dynamics - Discrete Element Method) simulations and recurrence-based CFD (rCFD) predictions of gas-solid fluidized beds. The repository contains CFD-DEM simulation cases for four drag models (Beetstra, DiFelice, Gidaspow, Koch-Hill), rCFD time-extrapolation implementations achieving 100-1000× computational speedup, MRI experimental measurements of bubble dynamics in poppy seed fluidization, automated post-processing workflows, and quantitative validation results. This dataset enables researchers to reproduce published results, validate their own CFD-DEM models against MRI experimental data, develop and benchmark rCFD methodologies for real-time multiphase flow predictions, optimize drag model selection for fluidized bed applications, and apply advanced image processing and bubble detection algorithms. The data follows FAIR principles with open formats (CSV, OpenFOAM, Python scripts), comprehensive documentation in eight README files, complete provenance from CAD geometry to validation results, and example workflows for researchers, students, and engineers working with fluidized bed systems, particle technology, and multiphase flow simulations.