SGER: Granular Lubrication: Progressive modeling and experimentation of a novel lubrication mechanism

SGER：颗粒润滑：一种新型润滑机制的逐步模拟和实验项目摘要由于液体润滑剂在极端温度下分解，研究人员提出在宏观范围的滑动接触中使用固体流动颗粒作为润滑机制。此外，已知纳米/微米级接触中的液体润滑剂由于匹配元件之间的粘连而扰乱MEMS器件的动态运行。颗粒颗粒被认为是干润滑剂，在剪切室实验中被认为可以降低摩擦并分离滑动面。虽然流动的颗粒一直被认为是流体流动的象征，但颗粒流动科学界在模拟这些流动方面并没有同样的成功。已经开发了模型来预测料斗、传送带、倾斜和剪切单元中流动颗粒的行为。然而，这些模型强加了粗略的假设(例如，均匀的颗粒大小/形状、无摩擦的表面、被忽略的重力等)。并已针对最简单的情况和流动几何进行了求解。首先，统计力学原理与连续统方法相结合，提供了与实验数据适度的、而且往往只是定性的一致。宏观尺度上相互作用的颗粒已使用适用于液体的相同的Navier-Stokes流体模型来模拟。关键的区别在于，对于碰撞的颗粒，必须推导出混合物性质的本构关系，如粘度、导热系数和密度，并考虑非弹性。这表明，一种简化的、新颖的方法来模拟这些离散的粒子系统将是非常有价值的。基于格子的元胞自动机(LBCA)建模是使用定义良好的规则来开发能够预测真实离散的时空系统的计算机模拟，例如在颗粒流中看到的那些。离散的、时间的、粒子型的系统在摩擦学、生物学和自然界中分别以润滑颗粒、分子单体和干泥石流的形式出现。由于明确定义的规则必须来自对真实系统的观察，因此必须开发可从中推导出规则的实验。拟议的SGER时期将具有丰富的智力价值。我们将开发一种新的基于格子的建模方法来模拟颗粒润滑流，称为元胞自动机，它能够模拟滑动接触几何中碰撞颗粒的相互作用。LBCA模拟是基于粒子相互作用的基于规则的数学，该数学将从将在本工作中开发的颗粒状滑动轴承中获得。此外，CA模拟的结果将与现有连续介质模型的结果进行比较。颗粒流试验装置将能够测量流动参数速度、固相分数、颗粒温度和滑移率。它将有一个透明的外壳，以实现粒子相互作用的数字摄像，并用于开发碰撞规则。将从视频中开发数字粒子跟踪测速(DPTV)方案，以便从颗粒轴承获得数据。这个复杂的机械颗粒系统将是迄今为止第一个颗粒润滑的轴颈轴承。作为多组分摩擦学流动的基础，能够测量摩擦学参数的实验颗粒轴承将为了解这些极其复杂的流动在收敛间隙几何形状中的行为提供有价值的见解。LBCA建模方法能够预测离散的、相互作用的颗粒系统随时间演化的行为，这项工作将突出其在颗粒流中的实施速度和灵活性。这项工作将通过开发一个基于Web的模块来在线运行离散时间系统的LBCA，从而广泛影响未来的颗粒流和摩擦学工作人员。该模块将放在一个网站上，并将在匹兹堡的一所城市公立高中介绍一个简单的演示。此外，PI和研究生将在高中进行演讲，介绍为多组分流动和难以预测的物理实验开发新实验和模型的重要性。最后，这项工作将成为增加LBCA预测多组分流动，即摩擦学应用中的颗粒流的催化剂。

SGER: Granular Lubrication: Progressive modeling and experimentation of a novel lubrication mechanismProject SummarySince liquid lubricants break down at extreme temperatures, researchers proposed using solid flowing particles as a lubricating mechanism in macro-scale sliding contacts. Additionally, liquid lubricants in nano/micro-scale contacts have been known to disrupt dynamic operation of MEMs devices due to stiction between mating components. Granular particles, proposed as dry lubricants, have been known to lower friction and separate sliding surfaces in shear cell experiments. While flowing granules have always been considered reminiscent of fluid flows, the granular flow scientific community has not had the same success in modeling these flows. Models have been developed to predict the behavior of flowing granules in hoppers, conveyors, inclines, and shear cells. However, these models have imposed gross assumptions (e.g., uniform particle sizes/shapes, frictionless surfaces, neglected gravity, etc.) and have been solved for the simplest cases and flow geometries. First principle statistical mechanics coupled with continuum approaches have provided modest and oftentimes qualitative-only agreement with experimental data. Interacting granules at the macro-scale have been modeled using the same Navier-Stokes fluid models applied to liquids. The key difference is that constitutive relationships for mixture properties such as viscosity, thermal conductivity, and density must be derived for colliding granules and account for inelasticity. This suggests that a simplified, novel approach to modeling these discrete particle systems would be of great value. Lattice-based cellular automata (LBCA) modeling is the use of well-defined rules to develop a computer simulation capable ofpredicting real discrete, spatial-temporal systems such as these seen in granular flows. Discrete, temporal, particletype systems appear in tribology, biology, and nature as lubricating particulates, molecules monomers, and dry debris flows, respectively. Since the well-defined rules must come from observations of the real systems, experiments from which the rules can be derived must be developed. The proposed SGER period will be rich in intellectual merit. We will develop a new lattice-based modelingapproach for modeling granular lubrication flows, known as cellular automata, which is capable of simulating the interactions of colliding granules in a sliding contact geometry. The LBCA simulation is based on the rule-based mathematics of particle interaction that will be obtained from the granular journal bearing that will be developed in this work. Additionally, results from the CA simulations will be compared to those from existing continuum models. The granular flow test bearing will be capable of measuring the flow parameters velocity, solid fraction, granular temperature and slip. It will have a transparent encasing to enable digital videography of the particle interactions and for developing the rules of collision. A digital particle tracking velocimetry (DPTV) scheme will be developed from the video, so that the data can be obtained from the granular bearing. This complex mechanical granular system will be the first granular-lubricated journal bearing to date. Fundamental to multi-component tribological flows, an experimental granular bearing capable of measuring tribological parameters would provide valuable insight into the behavior of these extremely complex flows in converging gap geometries. The LBCA modeling approach is capableof predicting the behavior of discrete, interacting particulate systems that evolve over time and this work will highlight its speed of implementation and flexibility in granular flows.This work will broadly impact the future granular flow and tribology workforce by developing a web-based module for running LBCA for discrete temporal systems online. The module will be located on a website and a simple demo will be introduced at an urban Pittsburgh public high school. Additionally, the PI and graduate student will conduct presentations at the high school on the importance of developing new experiments and models for multi-component flows and hard to predict physics experiments. Lastly, this work would serve as a catalyst for increasing LBCA approached to predicting multi-component flows, namely granular flows for tribological applications.