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PMID: 29337433 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Video-Audio Media

Numerical simulation of two consecutive nasal respiratory cycles: toward a better understanding of nasal physiology.

International forum of allergy & rhinology ·Vol. 8 ·No. 6 ·2018-00-00 ·Pages 676-685

de Gabory L, Reville N, Baux Y, Boisson N, Bordenave L

Abstract

Computational fluid dynamic (CFD) simulations have greatly improved the understanding of nasal physiology. We postulate that simulating the entire and repeated respiratory nasal cycles, within the whole sinonasal cavities, is mandatory to gather more accurate observations and better understand airflow patterns. A 3-dimensional (3D) sinonasal model was constructed from a healthy adult computed tomography (CT) scan which discretized in 6.6 million cells (mean volume, 0.008 mm3 ). CFD simulations were performed with ANSYS©FluentTMv16.0.0 software with transient and turbulent airflow (k-ω model). Two respiratory cycles (8 seconds) were simulated to assess pressure, velocity, wall shear stress, and particle residence time. The pressure gradients within the sinus cavities varied according to their place of connection to the main passage. Alternations in pressure gradients induced a slight pumping phenomenon close to the ostia but no movement of air was observed within the sinus cavities. Strong movements were observed within the inferior meatus during expiration contrary to the inspiration, as in the olfactory cleft at the same time. Particle residence time was longer during expiration than inspiration due to nasal valve resistance, as if the expiratory phase was preparing the next inspiratory phase. Throughout expiration, some particles remained in contact with the lower turbinates. The posterior part of the olfactory cleft was gradually filled with particles that did not leave the nose at the next respiratory cycle. This pattern increased as the respiratory cycle was repeated. CFD is more efficient and reliable when the entire respiratory cycle is simulated and repeated to avoid losing information.

Keywords
3D model Computational fluid dynamics (CFD) airflow nasal airway nasal cavity physiology velocity wall shear stress
MeSH 主题词
Adult Humans Models, Anatomic Nasal Cavity/physiology Particulate Matter/analysis Pressure Respiration Stress, Physiological/physiology Tomography, X-Ray Computed
化学物质
Particulate Matter
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
de Gabory Ludovic
Ear, Nose, and Throat (ENT) Department, University Hospital of Bordeaux, Hôpital Pellegrin, Bordeaux, France. | Centre d'Investigation Clinique et d'Innovation Technologique de Bordeaux (CIC-IT 14-01), University Hospital of Bordeaux, France. | University of Bordeaux, Bordeaux, France.
Reville Nicolas
Ear, Nose, and Throat (ENT) Department, University Hospital of Bordeaux, Hôpital Pellegrin, Bordeaux, France. | University of Bordeaux, Bordeaux, France.
Baux Yannick
OPTIFLUIDES, Computational Fluid Dynamics Unit, Villeurbanne, France.
Boisson Nicolas
OPTIFLUIDES, Computational Fluid Dynamics Unit, Villeurbanne, France.
Bordenave Laurence
Centre d'Investigation Clinique et d'Innovation Technologique de Bordeaux (CIC-IT 14-01), University Hospital of Bordeaux, France. | University of Bordeaux, Bordeaux, France. | Institut National de la Santé et de la Recherche Médicale (INSERM), Bioingénierie tissulaire U1026, Bordeaux, France.
Article Info
Journal
International forum of allergy & rhinology
Abbr.
Int Forum Allergy Rhinol
ISSN
2042-6984
Published
2018-00-00
Epub
2018-00-16
Pages
676-685
Language
English
Country/Region
United States
NLM ID
101550261
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