Carlos A. Grande

Understanding the flow dynamics of chemical species is important for characterizing, analyzing, and designing chemical reactors. Computational fluid dynamics (CFD) provides accurate flow patterns, but this approach can be computationally expensive for large or complex geometries. To overcome this limitation, a new Lagrangian‐based method is developed using smoothed particle hydrodynamics (SPH) to forecast the flow patterns and residence time distribution of two different fluids for various reactor geometries: (laminar, fractal, T‐mixer, Hartridge–Roughton (H‐R) mixer and packed bed with a gyroid internal packing) and compared the results with computational fluid dynamics (CFD) simulations. The SPH method is less accurate than the CFD analysis, but it obtained the approximate flow behavior much faster. Consequently, the SPH method has significant potential as a first screening technique to optimize reactor topologies and internal packing structures.