Publications
2020 |
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Lintermann, Andreas Application of Computational Fluid Dynamics Methods to Understand Nasal Cavity Flows Book Chapter In: Cingi, Celmal; Muluk, Nuray Bayar (Ed.): All Around the Nose - Basic Science, Diseases and Surgical Management, vol. 1, Chapter 9, pp. 75-84, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-21216-2. Abstract | Links | BibTeX | Tags: Allergic rhinitis, Endonasal rhinoplasty, Endoscopic sinus surgery, External rhinoplasty, Image-guided sinus surgery, Nasal polyposis, Nasal Reconstruction, Nasal trauma, Rhinosinusitis, Tumors of the nasal cavity @inbook{Lintermann2020c, Computational fluid dynamics methods enable to numerically predict complex flows with the help of computers. In the fields of Engineering and Physics they are already in use for decades to support design decissions and to get insight into complex physical phenomena. The simulation techniques have massively evolved over the past years and can nowadays be applied in medical context to analyze bio-fluidmechanical processes. Thanks to the continuous increase of computational power and parallelism as well as algorithmic advancements, accurate predictions of the flow in the nasal cavity are possible today. This chapter introduces the reader to the concepts of the computational fluid dynamics of the nose. It delivers some fundamentals on pre-processing medical image data, various techniques to generate computational meshes and gives an overview of methods to solve the governing equations of fluid motion. Thereby, advantages and disadvantages of the various approaches are explained. Subsequently, a variety of methods to analyze the flow and particle dynamics in the nasal cavity, ranging from streamline visualizations, pressure loss and temperature increase considerations, wall-shear stress and heat-flux distributions, to the analysis of the particle deposition behavior and transitional flow, is presented. The chapter concludes with how such methods can be used in clinical applications and elaborates how future developments might support decision making in medical pathways. |