Literature DB >> 33175592

Computational modelling of nasal respiratory flow.

H Calmet1, K Inthavong2, H Owen1, D Dosimont1, O Lehmkuhl1, G Houzeaux1, M Vázquez1.   

Abstract

CFD has emerged as a promising diagnostic tool for clinical trials, with tremendous potential. However, for real clinical applications to be useful, overall statistical findings from large population samples (e.g., multiple cases and models) are needed. Fully resolved solutions are not a priority, but rather rapid solutions with fast turn-around times are desired. This leads to the issue of what are the minimum modelling criteria for achieving adequate accuracy in respiratory flows for large-scale clinical applications, with a view to rapid turnaround times. This study simulated a highly-resolved solution using the large eddy simulation (LES) method as a reference case for comparison with lower resolution models that included larger time steps and no turbulence modelling. Differences in solutions were quantified by pressure loss, flow resistance, unsteadiness, turbulence intensity, and hysteresis effects from multiple cycles. The results demonstrated that sufficient accuracy could be achieved with lower resolution models if the mean flow was considered. Furthermore, to achieve an established transient result unaffected by the initial start-up quiescent effects, the results need to be taken from at least the second respiration cycle. It was also found that the exhalation phase exhibited strong turbulence. The results are expected to provide guidance for future modelling efforts for clinical and engineering applications requiring large numbers of cases using simplified modelling approaches.

Keywords:  CFD; LES; airways; human nasal cavity

Year:  2020        PMID: 33175592     DOI: 10.1080/10255842.2020.1833865

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


  5 in total

1.  Use of computational fluid dynamics (CFD) to model observed nasal nitric oxide levels in human subjects.

Authors:  Dennis J Shusterman; Barak M Spector; Andrew N Goldberg; Edward M Weaver; Bradley A Otto; Kai Zhao
Journal:  Int Forum Allergy Rhinol       Date:  2021-12-18       Impact factor: 5.426

2.  Wet surface wall model for latent heat exchange during evaporation.

Authors:  Kiao Inthavong; David F Fletcher; Mehrdad Khamooshi; Sara Vahaji; Hana Salati
Journal:  Int J Numer Method Biomed Eng       Date:  2022-02-21       Impact factor: 2.648

3.  Research Active Posterior Rhinomanometry Tomography Method for Nasal Breathing Determining Violations.

Authors:  Oleg G Avrunin; Yana V Nosova; Ibrahim Younouss Abdelhamid; Sergii V Pavlov; Natalia O Shushliapina; Natalia A Bouhlal; Ainur Ormanbekova; Aigul Iskakova; Damian Harasim
Journal:  Sensors (Basel)       Date:  2021-12-20       Impact factor: 3.576

4.  Large eddy simulation of cough jet dynamics, droplet transport, and inhalability over a ten minute exposure.

Authors:  Hadrien Calmet; Kiao Inthavong; Ambrus Both; Anurag Surapaneni; Daniel Mira; Beatriz Egukitza; Guillaume Houzeaux
Journal:  Phys Fluids (1994)       Date:  2021-12-15       Impact factor: 3.521

5.  Computational modelling of an aerosol extraction device for use in COVID-19 surgical tracheotomy.

Authors:  Hadrien Calmet; Pablo Ferrer Bertomeu; Charlotte McIntyre; Catherine Rennie; Kevin Gouder; Guillaume Houzeaux; Christian Fletcher; Robert Still; Denis Doorly
Journal:  J Aerosol Sci       Date:  2021-07-27       Impact factor: 3.433

  5 in total

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