Computational fluid dynamics benchmark dataset of airflow in tracheas

Area of Science:

• Medical Imaging
• Computational Science
• Fluid Dynamics

Background:

• Computational Fluid Dynamics (CFD) is increasingly used for pre-surgical planning, offering insights difficult to obtain otherwise.
• Accurate CFD simulations are crucial for generating clinically relevant metrics in airway analysis.
• Validation of CFD simulation techniques for airway flows is limited due to the impossibility of in vivo verification.

Purpose of the Study:

• To provide a highly resolved dataset of airway flow dynamics.
• To establish a benchmark case for validating computational methods in airway simulations.
• To present a dataset and setup for Large Eddy Simulation (LES) as a more efficient alternative.

Main Methods:

• Generation of highly resolved flow data in airways.
• Comparison of data resolution to Kolmogorov length and time scales.
• Development of a Large Eddy Simulation (LES) dataset and solution setup.

Main Results:

• The presented data offers a high degree of resolution suitable for benchmark comparisons.
• The data serves as a reference for validating less computationally intensive CFD methods.
• A dataset and setup for LES are provided for efficient airway flow simulation.

Conclusions:

• The highly resolved flow data serves as a critical benchmark for CFD validation in airway simulations.
• This resource enables the assessment and improvement of computationally cheaper methods like LES.
• Accurate CFD, validated against such benchmarks, will enhance pre-surgical planning capabilities.