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

SGER：颗粒润滑：新型润滑机制的渐进建模和实验

• 批准号: 0520670
• 负责人: Cecil Higgs
• 金额: --
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-10-01 至 2006-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0520670&HistoricalAwards=false
• 关键词: SGER; Granular; Lubrication; Progressive; modeling

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.

SGER：颗粒状润滑：新型润滑机理的进行性建模和实验摘要液体润滑剂在极端温度下分解，研究人员建议将固体流动颗粒作为宏观尺度滑动接触中的润滑机制。另外，已知纳米/微尺度接触中的液体润滑剂因交配组件之间的陈述而破坏MEMS设备的动态操作。 已知颗粒颗粒（被认为是干润滑剂）在剪切细胞实验中降低摩擦和单独的滑动表面。尽管流动的颗粒一直被认为让人联想到流体流，但颗粒流科学界在对这些流动进行建模方面并没有取得相同的成功。已经开发了模型来预测料斗，输送机，斜坡和剪切细胞中流动颗粒的行为。但是，这些模型已实施了总体假设（例如，均匀的粒径/形状，无摩擦表面，被忽视的重力等），并已针对最简单的情况和流量几何形状进行了解决。第一原理统计力学和连续方法结合使用，与实验数据提供了适度的，通常仅定性的一致性。 宏观尺度上的相互作用颗粒已使用应用于液体的相同Navier-Stokes流体模型进行建模。关键区别在于，必须得出混合物特性（例如粘度，热导率和密度）的组成关系，以使颗粒碰撞并解释非弹性。这表明一种模拟这些离散粒子系统的简化，新颖的方法将具有很大的价值。基于晶格的蜂窝自动机（LBCA）建模是使用明确定义的规则来开发能够预测真实离散的时空系统的计算机仿真，例如在粒状流中看到的。离散的，时间，颗粒系统分别出现在摩擦学，生物学和自然中，分别是润滑颗粒物，分子单体和干碎屑流。由于定义明确的规则必须来自对实际系统的观察，因此必须从中得出规则的实验。 拟议的SGER时期将具有丰富的知识分子。我们将开发一种新的基于晶格的建模方法，用于建模颗粒状润滑流，称为蜂窝自动机，该流量能够模拟滑动触点几何形状中碰撞颗粒的相互作用。 LBCA模拟基于将从粒状杂志轴承获得的基于规则的粒子相互作用数学，该数学将在这项工作中开发。此外，将将CA模拟的结果与现有连续模型的结果进行比较。 颗粒流测试轴承将能够测量流程参数速度，固体分数，颗粒温度和滑动。它将具有透明的包围，以启用粒子相互作用的数字摄影并制定碰撞规则。数字粒子跟踪速度计（DPTV）方案将从视频中开发出来，以便可以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的第一个颗粒状润滑期刊。对多组分摩擦学流的基础，能够测量摩擦学参数的实验性颗粒状轴承将为这些极其复杂的流动在收敛间隙几何形状时的行为提供宝贵的见解。 LBCA建模方法能够预测随着时间的流逝而发展的离散，相互作用的颗粒系统的行为，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用于运行LBCA的lbca在线运行LBCA来广泛影响未来的粒度流量和摩擦学劳动力。该模块将位于网站上，并将在匹兹堡公立高中进行简单的演示。此外，PI和研究生将在高中进行演讲，以开发用于多组分流的新实验和模型的重要性，并难以预测物理实验。最后，这项工作将成为增加LBCA的催化剂，以预测多组分流量，即用于摩擦学应用的颗粒流。