Wang Yong, Elghobashi S
Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA 92697, USA.
Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA 92697, USA.
Respir Physiol Neurobiol. 2014 Mar 1;193:1-10. doi: 10.1016/j.resp.2013.12.009. Epub 2013 Dec 31.
The fluid dynamical properties of the air flow in the upper airway (UA) are not fully understood at present due to the three-dimensional (3D) patient-specific complex geometry of the airway, flow transition from laminar to turbulent and flow-structure interaction during the breathing cycle. It is quite difficult at present to experimentally measure the instantaneous velocity and pressure at specific points in the human airway. On the other hand, direct numerical simulation (DNS) can predict all the flow properties and resolve all its relevant length- and time-scales. We developed a DNS solver with the state-of-the-art lattice Boltzmann method (LBM), and used it to investigate the flow in two patient-specific UAs reconstructed from CT scan data. Inspiration and expiration flows through these two airways are studied. The time-averaged first spatial derivative of pressure (pressure gradient), ∂p/∂z, is used to locate the region of the UA obstruction. But the time-averaged second spatial derivative, ∂(2)p/∂z(2), is used to pinpoint the exact location of the obstruction. The present results show that the DNS-LBM solver can be used to obtain accurate flow details in the UA and is a powerful tool to locate its obstruction.
由于上呼吸道（UA）具有三维（3D）的患者特异性复杂几何形状、呼吸周期中气流从层流到湍流的转变以及流固相互作用，目前对上呼吸道内气流的流体动力学特性尚未完全了解。目前，要通过实验测量人体气道中特定点的瞬时速度和压力相当困难。另一方面，直接数值模拟（DNS）可以预测所有的流动特性，并解析所有相关的长度和时间尺度。我们用最先进的格子玻尔兹曼方法（LBM）开发了一个DNS求解器，并用它来研究从CT扫描数据重建的两个患者特异性上呼吸道内的气流。研究了通过这两个气道的吸气和呼气气流。压力的时间平均一阶空间导数（压力梯度）∂p/∂z用于定位上呼吸道阻塞区域。而压力的时间平均二阶空间导数∂²p/∂z²则用于精确确定阻塞的位置。目前的结果表明，DNS-LBM求解器可用于获得上呼吸道内准确的流动细节，是定位其上呼吸道阻塞的有力工具。
