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Computational Flow Modeling of Human Upper Airway Breathing

Mylavarapu, Goutham

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, PhD, University of Cincinnati, Engineering and Applied Science: Aerospace Engineering.
Computational modeling of biological systems have gained a lot of interest in biomedical research, in the recent past. This thesis focuses on the application of computational simulations to study airflow dynamics in human upper respiratory tract. With advancements in medical imaging, patient specific geometries of anatomically accurate respiratory tracts can now be reconstructed from Magnetic Resonance Images (MRI) or Computed Tomography (CT) scans, with better and accurate details than traditional cadaver cast models. Computational studies using these individualized geometrical models have advantages of non-invasiveness, ease, minimum patient interaction, improved accuracy over experimental and clinical studies. Numerical simulations can provide detailed flow fields including velocities, flow rates, airway wall pressure, shear stresses, turbulence in an airway. Interpretation of these physical quantities will enable to develop efficient treatment procedures, medical devices, targeted drug delivery etc. The hypothesis for this research is that computational modeling can predict the outcomes of a surgical intervention or a treatment plan prior to its application and will guide the physician in providing better treatment to the patients. In the current work, three different computational approaches Computational Fluid Dynamics (CFD), Flow-Structure Interaction (FSI) and Particle Flow simulations were used to investigate flow in airway geometries. CFD approach assumes airway wall as rigid, and relatively easy to simulate, compared to the more challenging FSI approach, where interactions of airway wall deformations with flow are also accounted. The CFD methodology using different turbulence models is validated against experimental measurements in an airway phantom. Two case-studies using CFD, to quantify a pre and post-operative airway and another, to perform virtual surgery to determine the best possible surgery in a constricted airway is demonstrated. The unsteady Large Eddy simulations (LES) and a steady Reynolds Averaged Navier Stokes (RANS) approaches in CFD modeling are discussed. The more challenging FSI approach is modeled first in simple two-dimensional anatomical geometry and then extended to simplified three dimensional geometry and finally in three dimensionally accurate geometries. The concepts of virtual surgery and the differences to CFD are discussed. Finally, the influence of various drug delivery parameters on particle deposition efficiency in airway anatomy are investigated through particle-flow simulations in a nasal airway model.
Ephraim Gutmark, Ph.D. D.Sc. (Committee Chair)
Shaaban Abdallah, Ph.D. (Committee Member)
Jeffrey Kastner, Ph.D. (Committee Member)
Siddarth Khosla, M.D. (Committee Member)
225 p.

Recommended Citations

Citations

  • Mylavarapu, G. (n.d.). Computational Flow Modeling of Human Upper Airway Breathing [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1377871159

    APA Style (7th edition)

  • Mylavarapu, Goutham . Computational Flow Modeling of Human Upper Airway Breathing. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1377871159.

    MLA Style (8th edition)

  • Mylavarapu, Goutham . "Computational Flow Modeling of Human Upper Airway Breathing." Doctoral dissertation, University of Cincinnati. Accessed APRIL 19, 2024. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1377871159

    Chicago Manual of Style (17th edition)