Cargando…
Computational fluid dynamics benchmark dataset of airflow in tracheas
Computational Fluid Dynamics (CFD) is fast becoming a useful tool to aid clinicians in pre-surgical planning through the ability to provide information that could otherwise be extremely difficult if not impossible to obtain. However, in order to provide clinically relevant metrics, the accuracy of t...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144758/ https://www.ncbi.nlm.nih.gov/pubmed/27981200 http://dx.doi.org/10.1016/j.dib.2016.11.091 |
_version_ | 1782473175188111360 |
---|---|
author | Bates, A.J. Comerford, A. Cetto, R. Doorly, D.J. Schroter, R.C. Tolley, N.S. |
author_facet | Bates, A.J. Comerford, A. Cetto, R. Doorly, D.J. Schroter, R.C. Tolley, N.S. |
author_sort | Bates, A.J. |
collection | PubMed |
description | Computational Fluid Dynamics (CFD) is fast becoming a useful tool to aid clinicians in pre-surgical planning through the ability to provide information that could otherwise be extremely difficult if not impossible to obtain. However, in order to provide clinically relevant metrics, the accuracy of the computational method must be sufficiently high. There are many alternative methods employed in the process of performing CFD simulations within the airways, including different segmentation and meshing strategies, as well as alternative approaches to solving the Navier–Stokes equations. However, as in vivo validation of the simulated flow patterns within the airways is not possible, little exists in the way of validation of the various simulation techniques. The data presented here consists of very highly resolved flow data. The degree of resolution is compared to the highest necessary resolutions of the Kolmogorov length and time scales. Therefore this data is ideally suited to act as a benchmark case to which cheaper computational methods may be compared. A dataset and solution setup for one such more efficient method, large eddy simulation (LES), is also presented. |
format | Online Article Text |
id | pubmed-5144758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-51447582016-12-15 Computational fluid dynamics benchmark dataset of airflow in tracheas Bates, A.J. Comerford, A. Cetto, R. Doorly, D.J. Schroter, R.C. Tolley, N.S. Data Brief Data Article Computational Fluid Dynamics (CFD) is fast becoming a useful tool to aid clinicians in pre-surgical planning through the ability to provide information that could otherwise be extremely difficult if not impossible to obtain. However, in order to provide clinically relevant metrics, the accuracy of the computational method must be sufficiently high. There are many alternative methods employed in the process of performing CFD simulations within the airways, including different segmentation and meshing strategies, as well as alternative approaches to solving the Navier–Stokes equations. However, as in vivo validation of the simulated flow patterns within the airways is not possible, little exists in the way of validation of the various simulation techniques. The data presented here consists of very highly resolved flow data. The degree of resolution is compared to the highest necessary resolutions of the Kolmogorov length and time scales. Therefore this data is ideally suited to act as a benchmark case to which cheaper computational methods may be compared. A dataset and solution setup for one such more efficient method, large eddy simulation (LES), is also presented. Elsevier 2016-11-28 /pmc/articles/PMC5144758/ /pubmed/27981200 http://dx.doi.org/10.1016/j.dib.2016.11.091 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Bates, A.J. Comerford, A. Cetto, R. Doorly, D.J. Schroter, R.C. Tolley, N.S. Computational fluid dynamics benchmark dataset of airflow in tracheas |
title | Computational fluid dynamics benchmark dataset of airflow in tracheas |
title_full | Computational fluid dynamics benchmark dataset of airflow in tracheas |
title_fullStr | Computational fluid dynamics benchmark dataset of airflow in tracheas |
title_full_unstemmed | Computational fluid dynamics benchmark dataset of airflow in tracheas |
title_short | Computational fluid dynamics benchmark dataset of airflow in tracheas |
title_sort | computational fluid dynamics benchmark dataset of airflow in tracheas |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144758/ https://www.ncbi.nlm.nih.gov/pubmed/27981200 http://dx.doi.org/10.1016/j.dib.2016.11.091 |
work_keys_str_mv | AT batesaj computationalfluiddynamicsbenchmarkdatasetofairflowintracheas AT comerforda computationalfluiddynamicsbenchmarkdatasetofairflowintracheas AT cettor computationalfluiddynamicsbenchmarkdatasetofairflowintracheas AT doorlydj computationalfluiddynamicsbenchmarkdatasetofairflowintracheas AT schroterrc computationalfluiddynamicsbenchmarkdatasetofairflowintracheas AT tolleyns computationalfluiddynamicsbenchmarkdatasetofairflowintracheas |