Prediction of Transport and Deposition of Porous Particles in the Respiratory System Using Eulerian-Lagrangian Approach.

Deep lung delivery is crucial for respiratory disease treatment. Although nano and submicron particles exhibited a good deposition efficiency in deep regions of the lung, powder nonuniformity and particle agglomeration reduce their efficiency. Inhalation of porous particles (PPs) can overcome the mentioned challenges due to their larger size and low-density.

In silico investigation of inhalation condition impacts on hygroscopic growth and deposition of salbutamol sulphate in human airways.

The objective of this study is to explore the transport, size growth, and deposition of Salbutamol Sulphate (SS) using Computational Fluid Dynamics (CFD). A CT-based realistic model of human airways from the oral cavity to the 5th generation of the lung was utilized as the computational domain. Four Test Cases (TC) with varying temperature and relative humidity (RH) under two inspiratory waveforms were considered to completely evaluate the impact of inhalation conditions on particle growth.

Numerical analysis of an obstacle motion in the human ureter using the dynamic mesh approach.

Peristalsis is a common motion in various biological systems, especially the upper urinary tract, where it plays a pivotal role in conveying urine from the kidneys to the bladder. Using computational fluid dynamics, this study aims to investigate the effect of various peristaltic parameters on the motion of an obstacle through a two-dimensional ureter. Methodologically, Incompressible Navier-Stokes equations were utilized as the fluid domain's governing equations, and the Dynamic Mesh method (DM) was employed to simulate the peristaltic and obstacle motion.