Computational Fluid Dynamics in Spray Drying Processes

Computational Fluid Dynamics (CFD) has become an indispensable tool for elucidating the complex interplay of multiphase flow, heat and mass transfer, droplet evaporation and particle dynamics within spray dryers. By resolving turbulent gas flow fields alongside atomised liquid droplets or particulate slurries, CFD models capture key mechanisms such as droplet breakup, drying kinetics, wall deposition and re‐entrainment. The Eulerian–Lagrangian framework enables coupling of continuous air phases with discrete particle trajectories, while advanced turbulence closures and drying models reproduce real‐world behaviour from laboratory to full‐scale units. These simulations support optimisation of nozzle configurations, chamber geometry and operating conditions to improve yield, energy efficiency and product quality. Moreover, CFD aids in diagnosing fouling phenomena and guiding scale‐up strategies, thereby addressing industrial challenges across food, pharmaceutical and environmental applications on a global scale.

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Computational Fluid Dynamics in Spray Drying Processes publication trend

The graph below shows the total number of articles in computational fluid dynamics in spray drying processes across all publications each year (not limited to Nature Index journals).

Technical terms

Eulerian–Lagrangian framework: CFD approach treating the fluid phase as a continuous field (Eulerian) and particles or droplets as discrete entities tracked individually (Lagrangian).

Discrete Parcel Method (DPM): Numerical technique that groups many particles or droplets into representative parcels to reduce computational cost while preserving trajectory statistics.

Residence time distribution (RTD): Probability distribution describing the time particles spend in the drying chamber, critical for predicting drying completeness and product uniformity.

Restitution coefficient: Dimensionless parameter characterising the elasticity of particle collisions with walls, influencing rebound, deposition and overall residence times.

Hindered‐drying mechanistic model: Drying model accounting for reduced internal moisture diffusion rates due to surface crust formation or solute effects during particle drying.

References

1. Using CFD Simulations to Guide the Development of a New Spray Dryer Design. Processes (2020).
2. The Use of Optimized Restitution Coefficients to Improve Residence Time Prediction in Computational Fluid Dynamics-Discrete Parcel Method Models for Counter-Current Spray Dryers. Industrial & Engineering Chemistry Research (2021).
3. Computational Fluid Dynamics Modeling and Analysis of Lime Slurry Drying in a Laboratory Spray Dry Scrubber. Industrial & Engineering Chemistry Research (2024).