The Effects of Fluid-Particle and Particle-Particle Interactions on the Structure and Flow Properties of Suspensions of Fibers and Disks

流体-颗粒和颗粒-颗粒相互作用对纤维和圆盘悬浮液结构和流动性能的影响

• 批准号: 0332902
• 负责人: Donald Koch
• 金额: $ 27.95万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-01 至 2008-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0332902&HistoricalAwards=false
• 关键词: Effects; Fluid; Particle; Interactions; Structure

AbstractCTS-0332902D. Koch, Cornell UniversityIntellectual Merit: A major challenge for the scientific understanding and engineering design of structured materials and complex fluids is to determine the effects of fluid flow on the structure and properties of non-spherical-particle suspensions. A balanced approach of analytical theory, computer simulation and experiment will be applied to two problems on the forefront of this topic: (a) The orientation of slender fibers in high Reynolds number laminar and turbulent flows; and (b) The effects of fluid-mediated particle-particle interactions on the structure and rheology of suspensions of disks. While detailed theoretical models and careful experimental measurements are available for the flow-induced structure in fiber suspensions in viscous fluids, relatively little is known about the rotation of fibers when fluid inertia is important on the fibers length scale. More generally, the proper description of particle-fluid interactions for particles whose size is comparable to or larger than the size of the smallest eddies of a turbulent flow constitutes the most important current challenge in the description of particle-laden turbulent flows. In the proposed project, a novel simulation method will be developed that couples a slender-body description of the force distribution along a fiber with a spectral solution of the Navier-Stokes equations to describe particle-fluid interactions in a turbulent flow when the fiber length is comparable with the size of the eddies of the turbulent flow and inertia influences the fluid velocity disturbances produced by the fiber. This model will be applied to predict the turbulence-induced dispersion of fiber positions and orientations and the rate of sedimentation of fibers in turbulent flows. The most basic question concerning the motion of fibers at finite Reynolds number is how a fiber will rotate in a moderate Reynolds number simple shear flow. In the PIs current NSF sponsored research, analytical predictions have been obtained indicating that inertial effects cause a fibers orientation to drift toward the vorticity axis of a simple shear flow. The proposed study includes an experimental investigation of the motion of single fibers in a Couette cell to validate the predictions for the direction and rate of migration of fiber orientation. The proposed project will also extend the experimental and analytical approaches used to study fluid-mediated fiber-fiber interactions to understand the nature of such interactions in materials filled with disk-shaped particles. Microlithography methods will be used to produce model systems of rigid disks suitable for studies of the rheology and flow-induced orientation of disks in Newtonian fluids over a range of particle concentrations. This experimental study will be complemented by a theoretical analysis of disk-disk interactions to predict the effects of hydrodynamic interactions on the orientation distribution and rheology of the disk suspensions. Broader Impacts: High-aspect ratio fibers and disks are commonly used to enhance the mechanical, thermal and electrical properties of polymeric materials. These properties are highly sensitive to the structure induced by fluid flow when the materials are processed in the molten state. At the present time, commercial software based on the rotation of fibers in a low Reynolds number Newtonian fluid with a rotary diffusion to describe fiber-fiber interactions is widely used to predict structure in fiber composites. The experimental and theoretical studies of the effects of disk-disk interactions on disk orientation will provide the first step toward developing engineering models for the flow-induced structure in polymeric materials filled with platelet shaped particles such as mica flakes and silica clay particles. During the production of paper, pulp fibers suspended in water flow onto a porous conveyer belt to form a fiber network. It is desirable to use a turbulent fluid flow to disperse the fibers uniformly in space with isotropic orientations. In these flows, the Reynolds number based on the fiber length is O (10). The simulation method developed in this project will provide the first rigorous description of fiber motion under these conditions. The project will train a doctoral student and undergraduate researchers with the ability to interface analytical approaches with computer simulation and validate their models experimentally.

Abstractcts-0332902d。 Koch，Cornell UniversityIntellectual的优点：对结构化材料和复杂流体的科学理解和工程设计的主要挑战是确定流体流对非球形粒子悬浮液的结构和特性的影响。 分析理论，计算机模拟和实验的平衡方法将应用于该主题最前沿的两个问题：（a）高雷诺数层层层层层状和湍流中细长纤维的方向； （b）流体介导的颗粒粒子相互作用对磁盘悬浮液的结构和流变的影响。 虽然详细的理论模型和仔细的实验​​测量可用于粘性流体中纤维悬浮液的流动结构，但对于纤维惯性在纤维长度上很重要时，纤维旋转相对较少。 更笼统地说，对粒子的颗粒相互作用的正确描述与粒子相当或大于湍流的最小涡流的大小是构成粒子含量湍流流的描述中最重要的当前挑战。 在拟议的项目中，将开发一种新型的仿真方法，该方法将沿着纤维的力分布的细长描述与Navier-Stokes方程的光谱溶液沿着纤维溶液相结合，以描述纤维长度时湍流中的粒子流体相互作用与湍流和惯性的涡流的大小相当，会影响纤维产生的流体速度干扰。 该模型将应用于预测纤维位置和方向的湍流诱导的分散体以及湍流中纤维沉积的速率。 关于有限雷诺数在有限的雷诺数下运动的最基本问题是，纤维将如何在中等雷诺数中旋转简单剪切流。 在PIS当前NSF赞助的研究中，已经获得了分析预测，表明惯性效应会导致纤维取向向简单剪切流的涡度轴漂移。 拟议的研究包括对COUETTE细胞中单纤维运动的运动，以验证纤维取向迁移的方向和速率的预测。 拟议的项目还将扩展用于研究流体介导的纤维纤维相互作用的实验和分析方法，以了解填充有盘形颗粒的材料中这种相互作用的性质。 微观造影方法将用于生成刚性磁盘的模型系统，适用于牛顿流体在一系列颗粒浓度上的流变学和流动诱导的磁盘方向。 这项实验研究将通过对磁盘盘相互作用的理论分析来补充，以预测流体动力相互作用对磁盘悬浮液的方向分布和流变学的影响。更广泛的影响：高空纤维纤维和磁盘通常用于增强聚合物材料的机械，热和电性能。 当材料以熔融状态处理时，这些特性对流体流量引起的结构高度敏感。 目前，基于低雷诺数中纤维旋转的商业软件具有旋转扩散的牛顿流体，以描述纤维纤维相互作用，可广泛用于预测纤维复合材料中的结构。 关于磁盘相互作用对磁盘方向的影响的实验和理论研究将为开发用于流动诱导的结构的工程模型的第一步，以填充有血小板形颗粒的聚合物材料，例如云母片和硅胶粘土颗粒。 在生产纸过程中，悬浮在水流到多孔输送带的纸浆纤维形成纤维网络。 希望使用湍流流以各向同性方向将纤维均匀地分散在太空中。 在这些流中，基于光纤长度的雷诺数为O（10）。 该项目中开发的仿真方法将在这些条件下对纤维运动的第一个严格描述。 该项目将培训博士生和本科研究人员，能够通过计算机模拟进行分析方法并通过实验验证其模型。