Venkata K. Jasti

A Review of Dry Particulate Lubrication: Powder and Granular Materials

Research efforts related to dry particulates in sliding contacts are reviewed. In the tribology community, there are primarily two types of dry particulate lubricants that are studied—granular and powder. Granular lubricants usually refer to dry, cohesionless, hard particles which transfer momentum and accommodate surface velocity differences through shearing and rolling at low shear rates, and collisions at high shear rates. Powder lubricants refer to dry, cohesive, soft particles which accommodate surface velocity differences mostly by adhering to surfaces and shearing in the bulk medium, in a manner similar to hydrodynamic fluids. Spanning the past five decades, this review proposes a classification system for the scientific works in the dry particulate tribology literature in terms of theory, experiments, and numerical simulations. It also suggests that these works can be further categorized based on their tribosystem geometry—annular, parallel, and converging.Copyright

On the Behavior of Granular Materials in Rough Wheel Contacts on Mars

The extremely remote location of Mars suggests that it is not possible to carry enough flight resources to make a roundtrip. Therefore, in-situ mining, conveyance, and transporting of Martian soil must be conducted with the aid of wheel-based vehicles. However, there is limited understanding of the behavior of granular materials in rough rolling contacts with prescribed wheel roughness (or traction). On earth, rolling contacts in the presence of liquid surfaces oftentimes exhibit boundary-traction and hydrodynamic slip, where accurate prediction of the traction behavior between the wheel and the surface is governed by dry friction and hydrodynamic theory. Since granular materials have been known to behave as solids and liquids, a predictive modeling framework is needed to study the behavior of these complex materials under load and as a function of wheel roughness in interfaces. This work describes the usefulness of employing a tribology-based continuum modeling approach, known as granular kinetic lubrication (GKL), to model granular flows in a rough and fixedload parallel shear cell. Additionally, a lattice, rule-based mathematics modeling approach, known as cellular automata, is explored as a more simplified tool for modeling complex granular systems in shear cells. Results from the two modeling approaches are compared and comments about their usefulness in advancing an understanding of vehicle transport on Martian regolith are made. Lastly, preliminary experimental results are presented on granular flows with varying wheel roughness

Modeling the Motion of Slurry Nanoparticles During Chemical Mechanical Polishing

Chemical mechanical polishing (CMP) has emerged as a commonly used method for achieving global surface planarization of micro-/nano-scale systems during fabrication. During CMP, the wafer to be polished is pressed against a rotating polymeric pad that is flooded with slurry. The motion of the wafer surface against the asperities of the pad and the abrasive nanoscale particles in the slurry causes the surface of the wafer to be polished to an atomically smooth level. Past studies have shown that the wear distribution is a function of the distribution of slurry particles in the wafer/pad interface, and thus it is desirable to model the migration of particles in order to predict the wear of the wafer surface. The current study involves the creation and simulation of a mathematical model which predicts the paths of slurry particles in a Lagrangian reference frame. The model predicts the effects of the various forces on each particle to determine its motion. The model also accounts for interparticle collisions and wafer/particle and pad/particle collisions. It is expected that the particle motion that is predicted from this model will allow for a more accurate correlation of the wafer surface wear distribution.© 2005 ASME

An Experimental Study of the Effect of Global Solid Fraction and Surface Material on Couette Granular Flow

The flow of solid granular material has been proposed as an alternative lubricant to conventional liquid lubricants. Since granular flows are also in numerous industrial and natural processes, they have been the subject of numerous studies. However, it has been a challenge to understand them because of their non-linear and multiphase behavior. There have been several past experiments, which have gained insight into granular flows. For example, previous work by the authors sheared grains in a two-dimensional annular shear cell by varying the velocity and roughness [1]. The present experimental work attempts to further insights from the previous work by specifically studying the interaction between rough surfaces and granular flows when the global solid fraction and grain materials are varied. A two dimensional annular (granular) shear cell, with a stationary outer ring and inner driving wheel, was used for this work. Digital particle tracking velocimetry was used to obtain local granular flow data such as velocity, local solid fraction, and granular temperature. Slip between the driving wall and first layer of granules is also extracted. This slip can be interpreted as momentum transfer or traction performance in granular systems such as wheel-terrain interaction. Parametric studies of global solid fraction and the material of the rough driving surface, attempt to show how these parameters affect the local granular flow properties.Copyright

Including Friction and Spin Rules in the Lattice-Based Cellular Automata Approach to Model Granular Flows

Granular flows have been proposed as an alternative lubrication mechanism to conventional liquid lubricants in sliding contacts due to their ability to carry loads and accommodate surface velocities. Their load carrying capacity has been demonstrated in the experiments of Yu and Tichy [1]. Alternate lubrication techniques are becoming necessary due to the failure of conventional liquid lubricants in extreme temperature environments, and their promotion of stiction in micro-/nanoscale environments. Yet, understanding granular behavior has been difficult due to its non-linear and multiphase behavior. Cellular Automata (CA) has been shown to be a viable first order approach to modeling some complex aspects of granular flow. Previous work by the authors successfully modeled granular shear with a CA model [2]. Additional work combined CA computational efficiency with particle dynamics to effectively model collision events. This work builds upon and modifies the prior CA modeling approaches by adding friction modeling and spin of particles. This modification maintains the computational efficiency of CA, while increasing accuracy of the predicted granular flow properties, such as speed, solid fraction, and granular temperature. The current work compares the CA model with friction and spin physics relations to the authors’ prior CA model which neglected friction. Both CA models are also evaluated against experimental data to quantify the benefits of including friction and spin in the CA modeling approach for granular flows.Copyright

Explicit Finite Element Simulation of Granular Flow in an Annular Shear Cell

Explicit finite element method modeling of granular flow behavior in an annular shear cell has been studied and presented in this paper. The explicit finite element method (FEM) simulations of granular flow in an annular shear cell with around 1633 particles were performed, where the inner wheel rotated at a very high speed and the outer disk remained stationary. The material properties of the particles and the outer wheel were defined as elastic steel whereas the inner wheel was elastic aluminum. In this investigation, the explicit FEM model mimicked granular flow in an experimental set up where the inner wheel was rotated at a speed of 240 rpm. The FEM results for shearing motion and solid fraction were compared with experimental results from a granular shear cell.Copyright

Using a Lattice-Based Cellular Automata Approach to Model the Load Carrying Capacity of Granular Flows

Flows of solid granular particles are proposed as an alternate lubrication mechanism to conventional liquid lubrication in sliding contacts, because of their ability to carry loads and to accommodate surface velocities. Alternate lubrication is becoming necessary in extreme temperature environments where liquid lubricants fail and in micro/nanoscale environments were they promote stiction. However understanding granular behavior has been a challenge because of their ability to behave as solids, liquids and gases with varying circumstances. Cellular automata (CA), a deterministic rule based mathematics approach, has been successful in modeling some complex aspects of granular behavior. Our previous work successfully modeled granular shear with CA model. This work introduces a more versatile and novel cellular automata framework which combines the computational efficiency of CA with the power of particle dynamics to capture collision events. In the past, the load carrying capacity of granular flows was demonstrated in the experiments conducted by Yu and Tichy [2] and later, local flow properties were modeled using the granular kinetic lubrication continuum modeling approach. These results were used as a benchmark for determining the effectiveness of the current CA model.Copyright

Granular Flows in an Annular Shear Cell With Varying Roughness: Experiments and Modeling

Flows of granular particles in sliding contacts have been proposed as a “dry” lubrication mechanism. Granular flows are complex flows that exhibit fluid and solid behavior. A transparent granular shear cell (GSC) with an annular geometry was constructed to study their behavior. The GSC operates at variable speeds and its wheel roughness was fabricated to physically match the well-known theoretical boundary conditions of Jenkins and Richman. Effects of the physical variables on the local granular flow parameters are presented. A continuum modeling approach, known as granular kinetic lubrication (GKL), was employed to predict the experimental data. Good qualitative and modest quantitative agreements between the experiments and model were obtained.Copyright