This work aims to assess human nasal blockage by investigating its influence on nasal airflow dynamics, both computationally and experimentally. An in-house CFD code (Lithium) computes the steady (mean) nasal airflow for a cavity constructed from CT images of a healthy adult, for the internal cavity and for the first time for the external flow. To account for turbulence occurrence, the low Reynolds number k-ω Reynolds-Averaged-Navier-Stokes (RANS) model is used. The flow field is calculated at different breathing rates by varying the influx rate. Blockages are introduced at various locations inside the cavity to investigate common nasal blockages. The computational results are assessed against published literature and the Particle Image Velocimetry experimental (PIV) results, carried out on a 2.54:1 scale model of the computational nasal cavity. Schlieren optical technique is also used for external nasal airflow visualizations of a human subject, to comment on using an optical system for clinical application. These computations reveal a significant dependency of both, the internal and external nasal airflow fields on the nasal cavity’s geometry. Although for this model, the flow is found to be turbulent in the inspiratory phase of 200 ml/s and higher, it is suggested that the nature of flow can vary depending on the nasal cavity’s structure which is influenced by genetics. Nevertheless, some common flow features were revealed such as higher flow rate in the olfactory region and main flow passage through lower airways during inspiration. More uniform flow passage was found in expiration. The results also suggest a possible correlation between the internal geometry of the cavity and the external nasal airflow angle and thickness. This correlation can allow an application of optical systems such as Schlieren which is shown to give accurate qualitative images of the external nasal airflow for assessment of the nasal blockage.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:554359 |
Date | January 2012 |
Creators | Nayebossadri, Shahrzad |
Publisher | Queen Mary, University of London |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://qmro.qmul.ac.uk/xmlui/handle/123456789/8611 |
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