Mechanical Engineering Commons^™

Modelling Three-Phase Flow In Metallurgical Processes, Christoph Goniva, Gijsbert Wierink, Kari Heiskanen, Stefan Pirker, Christoph Kloss

Gijsbert Wierink

The interaction between gasses, liquids, and solids plays a critical role in many processes, such as coating, granulation and the blast furnace process. In this paper we present a comprehensive numerical model for three phase flow including droplets, particles and gas. By means of a coupled Computational Fluid Dynamics (CFD) - Discrete Element Method (DEM) approach the physical core phenomena are pictured at a detailed level. Sub-models for droplet deformation, breakup and coalescence as well as droplet-particle and wet particle-particle interaction are applied. The feasibility of this model approach is demonstrated by its application to a rotating drum coater. The …

Development And Verification Of A Navier-Stokes Solver With Vorticity Confinement Using Openfoam, Austin Barrett Kimbrell

Masters Theses

Vorticity Confinement (VC) is a numerical technique which enhances computation of fluid flows by acting as negative diffusion within the limit of vortical regions, preventing the inherent numerical dissipation present with conventional methods. VC shares similarities with large eddy simulation (LES), but its behavior is based on a stable negative dissipation of vortical structures controlled by the automatic balance between two parameters, μ [mu] and ε [epsilon].

In this thesis, three-dimensional, parallel-computing Navier-Stokes solvers with VC are developed using the OpenFOAM computational framework. OpenFOAM is an open-source collection of C++ libraries developed for computational fluid dynamics. Object-oriented programming concepts are …

Feature-Based Neuro-Symbolic Networks For Global Diagnostics, Tracy Lynn Schantz

Electronic Theses and Dissertations

Engineered system diagnostics have been researched over the years with many successful results. From transportation systems to office technologies, many have been equipped with self-diagnostic capabilities and are called Smart Machines. In spite of these advances, current diagnostic systems are driven by direct sensory information without much concern for patterns of the system behavior or features associated with them. For large-scale systems with complex dynamics, global as well as local diagnostics become of great importance, where sensory information is used as input for the local diagnostics, and patterns of behavior or features are utilized for global diagnostics.

The main objective …