Committee Chair
Karman, Steve L., Jr.
Committee Member
Swafford, Timothy W.; Hyams, Daniel G.
College
College of Engineering and Computer Science
Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
This study examines the improvement of near-field sonic boom prediction of an inviscid supersonic configuration using two grid generation refinement procedures. The first method uses P_HUGG, a parallel hierarchical Cartesian mesh generation algorithm to generate a volume mesh, with the solution-based mesh adaptation capability of P_HUGG being exploited. The mesh quality was improved using P_OPT, a parallel optimization-based mesh-smoothing program. In the second method, the commercially-available software POINTWISE™ is used for volume mesh generation. Then, P_REFINE, a parallel subdivision refinement code, is used t o adaptively refine the mesh. The effectiveness of capturing far field shocks was examined using TENASI, an unstructured flow solver developed at the SimCenter at the University of Tennessee at Chattanooga. The grids are adapted to high pressure gradient using SPACING, a program that computes the desired spacing at all points in the mesh. Results from both methods are compared with wind-tunnel based experimental data.
Degree
M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.
Date
12-2009
Subject
Computer programs
Discipline
Computational Engineering
Document Type
Masters theses
DCMI Type
Text
Extent
ix, 46 leaves
Language
English
Rights
https://rightsstatements.org/page/InC/1.0/?language=en
License
http://creativecommons.org/licenses/by-nc-nd/3.0/
Recommended Citation
Varghese, Jacob Chackasseril, "Sonic boom prediction methods using feature-based adaptation of unstructured meshes" (2009). Masters Theses and Doctoral Dissertations.
https://scholar.utc.edu/theses/221
Department
Dept. of Computational Engineering