title: Computational fluid dynamics benchmark dataset of airflow in tracheas.
abstract: 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, asin vivovalidation 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.
authors.affiliation: Department of Aeronautics, Imperial College, London, United Kingdom.
authors.forename: A J
authors.initials: AJ
authors.lastname: Bates
authors.affiliation: Department of Aeronautics, Imperial College, London, United Kingdom.
authors.forename: A
authors.initials: A
authors.lastname: Comerford
authors.affiliation: Department of Aeronautics, Imperial College, London, United Kingdom; Department of Otolaryngology, St. Mary׳s Hospital, Imperial College Healthcare Trust, United Kingdom.
authors.forename: R
authors.initials: R
authors.lastname: Cetto
authors.affiliation: Department of Aeronautics, Imperial College, London, United Kingdom.
authors.forename: D J
authors.initials: DJ
authors.lastname: Doorly
authors.affiliation: Department of Bioengineering, Imperial College, London, United Kingdom.
authors.forename: R C
authors.initials: RC
authors.lastname: Schroter
authors.affiliation: Department of Otolaryngology, St. Mary׳s Hospital, Imperial College Healthcare Trust, United Kingdom.
authors.forename: N S
authors.initials: NS
authors.lastname: Tolley
keywords: Airflow; CFD; DNS; Goiters; LES; Tracheas