On the Use of Computational Fluid Dynamics (CFD) Modelling to Design Improved Dry Powder Inhalers

TL;DR

This study uses CFD simulations to optimize dry powder inhaler design by validating turbulence models against experimental data, emphasizing the importance of model selection for accurate flow and particle behavior predictions.

Contribution

It demonstrates the critical impact of choosing appropriate turbulence models and boundary conditions in CFD simulations of inhalers, validated against experimental flow and particle dispersion data.

Findings

SBES model shows excellent agreement with PIV data

Particle tracking aligns with dispersion experiments

Proper turbulence modeling improves inhaler flow predictions

Abstract

Purpose: Computational Fluid Dynamics (CFD) simulations are performed to investigate the impact of adding a grid to a two-inlet dry powder inhaler (DPI). The purpose of the paper is to show the importance of the correct choice of closure model and modeling approach, as well as to perform validation against particle dispersion data obtained from in-vitro studies and flow velocity data obtained from particle image velocimetry (PIV) experiments. Methods: CFD simulations are performed using the Ansys Fluent 2020R1 software package. Two RANS turbulence models (realisable $k - \epsilon$ and $k - \omega$ SST) and the Stress Blended Eddy Simulation (SBES) models are considered. Lagrangian particle tracking for both carrier and fine particles is also performed. Results: Excellent comparison with the PIV data is found for the SBES approach and the particle tracking data are consistent with the dispersion results, given the simplicity of the assumptions made. Conclusions: This work shows the importance of selecting the correct turbulence modelling approach and boundary conditions to obtain good agreement with PIV data for the flow-field exiting the device. With this validated, the model can be used with much higher confidence to explore the fluid and particle dynamics within the device.