CHAOTIC MIXING OF AEROSOL IN RHYTHMICALLY EXPANDING LUNG

基本的气溶胶动力学知识是理解 许多重要的生理过程，如环境暴露 致病颗粒，或治疗和诊断的应用 气雾剂输送的物质。我们的主要目标是了解气溶胶 肺部周围的行为。目前存在的数学模型 考虑粘性流动的气溶胶输送和沉积模型 可逆的，因此，理论上排除了 腺泡区域内的对流(流动诱导)混合。与这些相反的是 理论，实验数据表明，在对流混合 腺泡。最近发现粘性流动在以下情况下是不可逆的 流动呈现出一种混乱的结构(Ottino等人，《自然》， 333(6172)，419-425,1988)开辟了流体力学的新途径， 将流体的混沌行为描述为混合中的一个重要因素。 研究了腺泡导管结构特性对其的影响， 特别是与时间相关的几何展开的影响 在肺泡壁的流动行为上，我们观察到了一些现象 具有混乱流的特点。基于这些观察，我们 假设复杂的混沌流动可以有节奏地发生在 正常呼吸时肺泡管的扩张-收缩结构 这会导致强烈的流动诱导(混沌)混合。我们建议 为了结合数学分析来检验这一假设-- 物理肺泡内的拉格朗日粒子跟踪和流动显示 模型和动物的肺。我们将通过以下方式量化混合的程度 计算示踪粒子的熵随时间的演化。这 新的概念带来了一幅完全不同的、可以量化的图景 以前使用的传播和扩散的想法。我们相信， 这项拟议研究的结果将使我们对气溶胶有新的认识。 并将帮助我们理解重要的生理学 流程。

Basic knowledge of aerosol kinetics is essential for the understanding of many important physiological processes, such as environmental exposure to pathogenic particles, or therapeutic and diagnostic application of aerosol delivered substances. Our major goal is to understand aerosol behavior in the lung periphery. The currently existing mathematical models of aerosol transport and deposition consider the viscous flow reversible and, therefore, theoretically exclude the possibility of convective (flow-induced) mixing in the acinar region. Contrary to these theories, experimental data suggest appreciable convective mixing in the acinus. The recent discovery that viscous flow can be irreversible if the flow exhibits a chaotic structure (Ottino, et al., Nature, 333(6172),419-425, 1988) has opened up a new avenue in fluid mechanics, describing chaotic behavior of fluids as an important factor in mixing. Studying the influence of structural characteristics of the acinar duct, in particular the effects of time-dependent geometric expansion of alveolar walls on flow behavior, we have observed phenomena characteristic of chaotic flow. Based on these observations we hypothesize that complex chaotic flow can occur in the rhythmically expanding-contracting alveolated duct structure during normal breathing and it can result in strong flow-induced (chaotic) mixing. We propose to test this hypothesis with a combination of mathematical analyses - Lagrangian particle tracking and flow visualization in physical alveolus models and with animal lungs. We will quantify the extent of mixing by computing the time evolution of the entropy of tracer particles. This new concept leads to a totally different and quantifiable picture of the previously used ideas of spreading and dispersion. We believe that the results of this proposed study would give us new insight into aerosol kinetics and would help us in understanding important physiological processes.