COMPUTATIONAL FLUID DYNAMICS (CFD) MODELLING OF TURBULENT FLOWS IN A CT-BASED ACTUAL HEALTHY HUMAN LOWER AIRWAY (G0-G4) GEOMETRY TO AID PATIENTS WITH ACUTE RESPIRATORY DISTRESS SYNDROME (ARDS) / COVID

Acute Respiratory Distress Syndrome (ARDS), commonly associated with high patient mortality rates, causes acute lung injury and often leads to respiratory failure. The recent pandemic causing Corona Virus Disease (COVID) is a subset of ARDS. The treatment requires the use of mechanical ventilation, which can lead to potential complications and is termed as Ventilator Induced Lung Injury (VILI). To enumerate the mechanisms leading to VILI, a computational fluid dynamics (CFD) model is developed and implemented to study the velocity profiles, flow rates and pressure distribution in an actual healthy human tracheobronchial airway. A piecewise CFD approach of the G0-G4 airway of a single healthy lung model is implemented to obtain the flow patterns for each of the 14 bifurcations considered in this study of a single healthy lung model. The simulations are conducted for five different inlet flowrates corresponding to Reynolds number (Re) 3000, 3500, 4000, 4500 and 5000 within the transition/ turbulent flow regime. Suitable assumptions are considered in this study to achieve the goal of understanding the dynamics and mechanics of flow in the bifurcations of lung airways using a computational domain (solid model of geometry, mesh generation, etc.) using Computed Tomography (CT) data of human lungs. The resulting asymmetric velocity profiles and pressure contours from the Computational Fluid Dynamics (CFD) simulations are discussed in detail while also highlighting their implications to ARDS. Sensitive areas were identified using the computational model developed in this study of the actual lung airway geometry. This work is a preliminary attempt for developing a prediction tool using lumped parameter and reduced order model for treating patients with ARDS.