{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1361"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1361","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Sonic boom prediction methods using feature-based adaptation of unstructured meshes","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Varghese, Jacob Chackasseril"],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Karman, Steve L., Jr.","Swafford, Timothy W.; Hyams, Daniel G.","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T05:46:19Z","subjects":["Computer programs"],"languages":["English","eng"],"rights":[],"rights_urls":["https://rightsstatements.org/page/InC/1.0/?language=en"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/221","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Karman, Steve L., Jr.","Swafford, Timothy W.; Hyams, Daniel G.","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Varghese, Jacob Chackasseril"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2009-12-01T08:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Masters theses","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computer programs"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://rightsstatements.org/page/InC/1.0/?language=en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/221"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Computational Engineering","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."]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Sonic boom prediction methods using feature-based adaptation of unstructured meshes"]}]}],"canonical_facts":{"dc:contributor":["Karman, Steve L., Jr.","Swafford, Timothy W.; Hyams, Daniel G.","College of Engineering and Computer Science"],"dc:creator":["Varghese, Jacob Chackasseril"],"dc:date":["2009-12-01T08:00:00Z"],"dc:description":["Dept. of Computational Engineering","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."],"dc:description.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."],"dc:identifier":["https://scholar.utc.edu/theses/221"],"dc:language":["English","eng"],"dc:publisher":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"],"dc:relation":["Masters Theses and Doctoral Dissertations"],"dc:rights":["https://rightsstatements.org/page/InC/1.0/?language=en"],"dc:subject":["Computer programs"],"dc:title":["Sonic boom prediction methods using feature-based adaptation of unstructured meshes"],"dc:type":["Masters theses","Text"]},"updated_at":"2026-07-24T05:46:19Z"}