Collaborative Research: Flow Instabilities in Gas-solid Flows

1236157/1236490PI：Hrenya/Yin气固流动在两个自然界(山体滑坡、雪崩、行星环等)中普遍存在。和工业(制药、食品、化工和石油工业)。尤其是在广泛的应用中(循环流化床、气动输送管道、沙流模拟、防蚀、行星环等)中的高速气固两相流动，通常会产生被称为团簇的不稳定性，这对系统性能有很大的影响。准确预测星系团的开始和演化对于相关系统的设计、扩大和优化至关重要。结果表明，非弹性粒子间碰撞和气固阻力都可以独立地导致不稳定；然而，在实际系统中，它们总是相互作用的，它们的相对重要性还没有得到检验。这项研究的目的有两个：(I)阐明高速气固流动中不稳定的各种来源的相对重要性，以及(Ii)批判性地评估新的运动论(连续体)模型预测这种不稳定的定量性质的能力。这项研究将从一个没有动能输入的简单的、与时间相关的冷却系统开始，然后转移到更复杂和实际相关的、有和没有固体边界的流态化系统，以研究与时间无关的统计数据。将使用四种不同的计算方法。解决颗粒周围详细流动的格子Boltzmann模拟将用于提供评估碰撞和气相效应以及星团形成和演化的相对重要性所需的基于第一原理的数据集。在连续介质水平上，首先用基于双流体动力学理论的线性稳定性分析来预测稳定性边界；然后用欧拉-拉格朗日方法和欧拉-欧拉模型来模拟团簇的演化。这些结果将与格子玻尔兹曼数据进行比较，以对各种连续介质模型的预测能力进行关键评估。这项研究将产生基于第一原理的高速气固两相流团簇形成和演化的模拟数据，这些数据将被用来建立一个准确的理论，能够在连续介质水平上预测成团不稳定性的开始和演化。仅举几例，气体和固体颗粒的同时流动发生在风暴、滑坡、用于能源生产的反应堆和制药工业使用的混合装置中。这些系统中发生的复杂物理相互作用使得仅从过去的实验很难预测它们。在本项目中，将开发没有拟合参数的数学模型，并用于预测这些系统特有的流动现象。这种建模工具的可获得性预计将减少到改进反应堆的设计，其周转时间更短，成本也比目前可能的更低。该模型将通过现有的开源代码提供给世界各地的研究人员，因此有望在许多领域找到未来的用途，包括制药、化学加工工业、能源生产、地质学和天体物理学。

1236157/1236490PI: Hrenya/YinGas-solid flows are ubiquitous in both nature (landslides, avalanches, planetary rings, etc.) and industry (pharmaceuticals, food products, chemical and petroleum industries). High-velocity gas-solids flows that are found in a wide range of applications (circulating fluidized beds, pneumatic transport lines, sand flow modeling, erosion prevention, planetary rings, etc.), in particular, often develop instabilities that are referred to as ?clusters?, which are known to have a large impact on system performance. Accurate prediction of onset and evolution of the clusters is critical to the design, scale-up, and optimization of related systems. It is shown that inelastic inter-particle collisions and gas-solid drag can both independently lead to instabilities; in real systems, however, they always cooperate and their relative importance has not been examined. The objective of this research is twofold: (i) to elucidate the relative importance of the various origins of the instabilities in high-velocity, gas-solid flows, and (ii) to critically assess the ability of a new kinetic-theory (continuum) model to predict the quantitative nature of such instabilities. This research will begin with a simplistic, time-dependent cooling system where kinetic energy input is absent, and then move to more complex and practically relevant fluidization systems with and without solid boundaries to investigate time-independent statistics. Four different computational methods will be used. Lattice Boltzmann simulations that solve the detailed flow around particles will be used to provide first-principle-based data sets needed to assess the relative importance of collisions and gas phase effects as well as cluster formation and evolution. On the continuum level, linear stability analyses based on two-fluid kinetic theories will first be used to predict the stability boundary; Euler-Lagrangian method where only gas phase is treated as a continuum and particles are discrete, and Euler-Euler models where both gas and particle phases are treated as continua, will then be used to simulate the evolution of the clusters. These results will be compared to the lattice Boltzmann data for a critical assessment of the predicative ability of the various continuum models. This research will generate first-principle-based simulation data on cluster formation and evolution for high-velocity gas-solid flows, and these data will be used to establish an accurate theory able to predict both onset and evolution of the clustering instability on the continuum level.The simultaneous flow of gas and solid particles occurs in windstorms, landslides, reactors used for energy production, and mixing units used by the pharmaceutical industry, to mention just a few. The complex physical interactions occurring in these systems make them difficult to predict from past experiments alone. In this project, mathematical models with no fitting parameters will be developed and used to predict flow phenomenon unique to these systems. The availability of such a modeling tool is expected to reduce to improved design of reactors in shorter turn-around times and at smaller costs than is currently possible. The model will be made available to researchers worldwide via an existing open-source code, and thus is expected to find future use in numerous sectors, including pharmaceuticals, chemical process industries, energy production, geology, and astrophysics.