Computational fluid dynamics (CFD) analysis of human upper airway in sleep apnea patients under various breathing conditions / Wan Mohd Faizal Wan Abd Rahim

• Main Author: Wan Mohd Faizal , Wan Abd Rahim
• Format: Thesis
• Published: 2022
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://studentsrepo.um.edu.my/14343/1/Wan_Mohd_Faizal.pdf; http://studentsrepo.um.edu.my/14343/2/Wan_Mohd_Faizal.pdf; http://studentsrepo.um.edu.my/14343/
• Institution: Universiti Malaya

Obstructive Sleep Apnea (OSA) is a sleeping disorder that has troubled a sizeable population. There is an active area of research on OSA that intends to understand the airflow mechanism better and treat patients more effectively. These help medical practitioners or surgeons in the decision-making process of treating diseased airways. Moreover, the flow mechanisms and patterns of the airflow in the airway can be visualised in a Three-Dimensional (3D) space. Research is needed to enhance the diagnosis technique and future upper airway surgical therapy quality. ENT doctors can utilise the data analysed on the specific flow mechanism of the upper airways to detect probable obstruction locations and lead them to the anatomical blockage site for surgical treatments. Computational fluid dynamic (CFD) analysis was used as a solution tool to evaluate the overall breathing conditions, including inhalation, exhalation, light breathing (during resting), and heavy breathing (during running). A medical imaging technique extracted the 3D model from the Computed Tomography (CT) scan images. Mesh generation and simulation were carried out via CFD software to evaluate the flow mechanism related to OSA patients. A Steady-state Reynold Averaged Navier-Stoke (RANS) with the k-ro Shear Stress Transport (SST) turbulence model was utilised. The airflow characteristics were quantified using pressure distribution, skin friction coefficient, velocity profile, Reynolds number, Turbulent Reynolds Number, and Turbulent Kinetic Energy (TKE). Contour plots at different planes were used to visualise the airflow distribution as it passed through different cross-sectional areas of the airway. The results-revealed-that-a smaller cross-sectional area of the airway caused, an increase in airflow parameters. Because of this discovery, the TKE can show the severity and location of the obstruction during breathing and the flow mechanism concentration. It is anticipated that this study will produce significant results by visualising the concentration in TKE or airflow mechanisms and characteristics of a patient's airway during comprehensive breathing. The findings of this study suggest that TKE may assist the practitioner in improving the diagnosis technique and the quality of future upper airway surgical therapy. Finally, CT scan data was used to create a 3D model of the patient's airway using the Mimic software. The simulation was carried out using the ANSYS FLUENT simulation software package. The current findings are beneficial to medical practitioners who work in the research field. The researchers hope to provide a clear representation of the characteristics of airflow.