Date of Award
Doctor of Philosophy (PhD)
C. Fred Higgs, III
Tribology – the science and technology of interacting surfaces in relative motion and the related subjects of friction, lubrication and wear – is an important aspect in industrial and natural systems. Multiphase flows, specifically particle-fluid flows, are present in many such tribological processes. Therefore, an increased understanding of the dynamics of particles in fluids and their interaction with the surrounding surfaces is a critical step in improving related industrial processes, many of which contain fluid-mediated sliding contacts. Interestingly, the primary physics which govern a vast number of particle-fluid processes are often similar. As a result, in this work a modeling framework is developed as a general approach to study particle-fluid systems. The modeling approach employs a physics-based, Eulerian-Lagrangian framework in order to predict the performance of applications that involve particle flow and tribological phenomena. More specifically, computational fluid dynamics (CFD) is used to model the Eulerian fluid phase, while the discrete element method (DEM) is used to model the particulate phase from a Lagrangian perspective. The modeling framework is applied to study abrasive wear and erosive wear processes and the results are validated with experimental data obtained during the course of this research.
In this thesis, the Eulerian CFD solver is introduced and validated for its spatial and temporal accuracy with analytical solutions for fluid flow. Two different spatial discretization schemes for the CFD were studied and their comparison is presented in Chapter 2. Similarly to the Eulerian phase, a lengthy discussion of the Lagrangian, DEM v solver is presented in Chapter 3. The implementation of Verlet tables to increase computational efficiency is detailed.
A critical step in the implementation of the framework is in determining the phase interactions. Chapter 4 is dedicated to discussing the particle-particle, particle-fluid, particle-surface, and surface-fluid interactions which are captured by the framework. Stokes drag and Ergun drag are implemented in the framework to provide solutions for different flow conditions. Additionally, the framework can capture the effect of particle heat transfer which is important in heated, packed particle beds. Various case studies are preformed and compared to experiments or analytical solutions to validate the model’s phase coupling. The framework’s ability to predict vortex shedding frequencies for flow around a cylinder using the immersed boundary method matches well to experimental results.
Erosive wear and rotary drilling (Chapters 6 and 7) are two particle-fluid applications to which the framework is applied. By modeling the behavior of the multi-phase flow in those tribo-systems, it is possible to predict their tribological behavior prior to observing them in real life. As a result, money and time can be saved by having a ―virtual laboratory‖ in which the effect of design and/or operational parameters on the system’s behavior can be simulated.
Mpagazehe, Jeremiah N., "A Physics-Based, Eulerian-Lagrangian Computational Modeling Framework to Predict Particle Flow and Tribological Phenomena" (2013). Dissertations. 294.