Journal Article

FZJ-2019-05807

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Fluid mechanics based classification of the respiratory efficiency of several nasal cavities

Lintermann, A.FZJ* ; Meinke, M.RWTH* ; Schröder, W.RWTH*

2013
Elsevier Science Amsterdam [u.a.]

This record in other databases:

Please use a persistent id in citations: doi:10.1016/j.compbiomed.2013.09.003

Abstract: The flow in the human nasal cavity is of great importance to understand rhinologic pathologies like impaired respiration or heating capabilities, a diminished sense of taste and smell, and the presence of dry mucous membranes. To numerically analyze this flow problem a highly efficient and scalable Thermal Lattice-BGK (TLBGK) solver is used, which is very well suited for flows in intricate geometries. The generation of the computational mesh is completely automatic and highly parallelized such that it can be executed efficiently on High Performance Computers (HPC). An evaluation of the functionality of nasal cavities is based on an analysis of pressure drop, secondary flow structures, wall-shear stress distributions, and temperature variations from the nostrils to the pharynx. The results of the flow fields of three completely different nasal cavities allow their classification into ability groups and support the \textit{a priori} decision process on surgical interventions.

---

Research Program(s):

1. 511 - Computational Science and Mathematical Methods (POF3-511) (POF3-511)

---

Database coverage:
; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

---