In this study, flow field characteristics in the trachea region in a realistic human upper airway model were firstly measured by particle image velocimetry (PIV) in the air under three constant inhalation and exhalation conditions: 36 L/min, 64 L/min and 90 L/min, representing flow rates of 18 L/min, 32 L/min and 45 L/min in real human airway (the model was twice the size of a human airway). Computational fluid dynamics (CFD) analyses were performed on four turbulence models, with boundary conditions corresponding to the PIV experiments. The effects of flow rates and breathing modes on the airflow patterns were investigated. The CFD prediction results were compared with the PIV measurements and showed relatively good agreement in all cases. During inhalation, the higher the flow rates, the less significant the “glottal jet” phenomenon, and the smaller the area of the separation zone. The air in the nasal inhalation condition accelerated more dramatically after glottis. The SST-Transition model was the best choice for predicting inhalation velocity profiles. For exhalation condition, the maximum velocity was much smaller than that during inhalation due to the more uniform flow field. The exhalation flow rates and breathing modes had little effect on the flow characteristics in the trachea region. The RNG k − ε model and SST k − ω model were recommended to simulate the flow field in the respiratory tract during exhalation.

在这项研究中，首先在三种恒定的吸气和呼气条件下：空气36 L / min，64 L / min和90的条件下，通过空气中的颗粒图像测速（PIV）测量了真实的人类上呼吸道模型中气管区域的流场特性。 L / min，代表实际人呼吸道中的流速为18 L / min，32 L / min和45 L / min（模型是人呼吸道大小的两倍）。在四个湍流模型上进行了计算流体动力学（CFD）分析，其边界条件对应于PIV实验。研究了流速和呼吸模式对气流模式的影响。将CFD预测结果与PIV测量结果进行了比较，并在所有情况下均显示出较好的一致性。吸入期间，流速越高，“声门喷射”现象的重要性越小，分离区的面积越小。声门吸入后，处于鼻吸入状态的空气加速更为剧烈。SST-Transition模型是预测吸入速度曲线的最佳选择。对于呼气条件，由于流场更均匀，因此最大速度远小于吸气过程中的最大速度。呼气流速和呼吸方式对气管区域的流动特性影响很小。RNG 呼气流速和呼吸方式对气管区域的流动特性影响很小。RNG 呼气流速和呼吸方式对气管区域的流动特性影响很小。RNG建议使用k  -  ε模型和SST k  -  ω模型来模拟呼气过程中呼吸道中的流场。