The field of Computational Fluid Dynamics (CFD) primarily involves the approximation of the Navier-Stokes equations. However, these equations are only valid when the flow is considered continuous such that molecular interactions are abundant and predictable. The Knudsen number, $Kn$, which is defined as the ratio of the flow's mean free path, $\lambda$, to some characteristic length, $L$, quantifies the continuity of any flow, and when this parameter is large enough, alternative methods must be employed to simulate gases. The Direct Simulation Monte Carlo (DSMC) method is one which simulates rarefied gas flows by directly simulating the particles that compose the flow and using probabilistic methods to determine their collisions and properties.
This thesis discusses the development of a new DSMC simulation code, named SINATRA, which was written in object-oriented C++ and validated on Cartesian grids. The code demonstrates the ability to perform standard simulation code tasks which include reading-in a user-made input file, performing the specified simulation, and generating visualization files compatible with Tecplot 360\texttrademark, a commercial post-processing software. SINATRA strategically uses an octree data structure as a storage scheme for computational grid data and uses this a backbone for particle interactions. The discussed validation cases include comparisons of initial particle properties to theoretical data, convergence studies for the sampling of macroscopic properties, and validation of transport properties through natural diffusion and Couette flow simulations. The results show successful implementation of simple DSMC procedures, and a path for future development of the code is thoroughly discussed.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-3289 |
| Date | 01 August 2018 |
| Creators | Galvez, David Matthew |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
Page generated in 0.0019 seconds