Numerical simulation of the unsteady flow field in the human pulmonary acinus


ÇİLOĞLU D.

SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, vol.46, no.4, 2021 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 46 Issue: 4
  • Publication Date: 2021
  • Doi Number: 10.1007/s12046-021-01704-2
  • Title of Journal : SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES
  • Keywords: Acinar flow dynamics, CFD modeling, breathing conditions, wall motion, Covid-19, PARTICLE-TRANSPORT, AEROSOL DEPOSITION, ALVEOLAR ZONE, AIR-FLOW, MICROPARTICLE DEPOSITION, BIFURCATION PHENOMENA, HUMAN AIRWAYS, LUNG INJURY, MODELS, SPIRONOLACTONE

Abstract

Understanding of airflow dynamics in the human pulmonary acinus is important for increasing targeted drug effectiveness and determining the health impact of toxic aerosols. However, there is a lack of quantitative data about the pulmonary airflow in realistic and flexible idealized geometries. This paper aims to numerically analyse the flow field of the pulmonary acinus using the computational fluid dynamics (CFD) model during transient breathing. Three-dimensional models with rhythmically expanding-contracting alveolar walls were developed for representing the pulmonary region of the human lung. Three different breathing scenarios were applied in the CFD simulations. The results showed that the transient flow conditions determined the transitions between flow types. The recirculating flow in the alveoli was observed for all cases and it was determined that its intensity depended on the breathing scenario. The flow velocity in the alveoli was slower than that of the channel flow. As we moved deeper into the lung, the flow pattern inside the alveoli exhibited a radial velocity profile. It was found that the alveolar flow exhibited a typical stenotic channel flow characteristics. As a result, the acinus models used in this study takes into account the alveolar wall motion based on physiological breathing conditions. To simulate or estimate the airflow dynamics, thus, the results obtained in this study can be easily utilized in the human lung airway models.