Computational Modelling of Idealized Triple Bifurcating Tracheobronchial Tree for Therapy of ARDS Patients

Acute Respiratory Distress Syndrome (ARDS) refers to lung diseases including the recently observed “Corona Virus Disease (COVID)” that led to the worldwide pandemic. ARDS is caused due to acute infection of the lungs which precipitates respiratory failure and is commonly associated with high patient mortality rates. The treatment often requires use of mechanical ventilation that has a potential to lead to secondary health complications, commonly termed as Ventilator Induced Lung Injury (VILI). VILI can be caused by high inspiratory pressure and cyclical opening and collapse during the breathing cycle. 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 a healthy human tracheobronchial airway geometry from third to sixth generation (G3-G6) branches. The flow patterns are obtained for each branch in the bifurcating network from the CFD simulations conducted for four different inlet flowrates corresponding to Reynolds number (Re) 250, 750, 1250 and 1750 within the laminar flow regime. The aim of this study is to improve the cognition of the dynamics and mechanics of flow in lung airways using an idealized triple bifurcation geometry while using suitable assumptions for the computational model with the goal of optimizing mechanical ventilation parameters by predicting complex flow fields inside human lungs. This study successfully demonstrated a computational model to observe the flow fields in the various segments of the lung airways and identified the sensitive areas in the triple bifurcation geometry. This work is preliminary to developing a reduced order prediction model to deliver individualized treatment for patients with ARDS and similar lung diseases.