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Computational fluid dynamics benchmark dataset of airflow in tracheas

机译:气管内气流的计算流体动力学基准数据集

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摘要

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.
机译:计算流体动力学(CFD)通过提供能够提供信息的能力而迅速成为一种有用的工具,可帮助临床医生进行手术前的计划,否则,即使不是不可能获得的信息,这些信息也将极为困难。但是,为了提供临床相关指标,计算方法的准确性必须足够高。在气道内执行CFD模拟的过程中采用了许多替代方法,包括不同的分割和网格划分策略,以及解决Navier-Stokes方程的替代方法。但是,由于不可能对气道内的模拟流型进行体内验证,因此各种模拟技术的验证方式几乎没有。此处显示的数据由非常高分辨率的流量数据组成。将分辨率与Kolmogorov长度和时标的最高必要分辨率进行比较。因此,此数据非常适合用作基准案例,可以将较便宜的计算方法与之进行比较。还介绍了一种数据集和解决方案设置,其中包括一种更有效的方法,即大涡流仿真(LES)。

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