Abstract
dc:description.abstractModern aerospace vehicle design requires the interaction of multiple disciplines, traditionally processed in a sequential order. Multidisciplinary optimization (MDO), a formal methodology for the integration of these disciplines, is evolving toward methods capable of replacing the traditional sequential methodology of aerospace vehicle design by concurrent algorithms, with both an overall gain in product performance and a decrease in design time. A parallel MDO paradigm using variable-complexity modeling and multipoint response surface approximations is presented here for the particular instance of the design of a high speed civil transport (HSCT). This paradigm interleaves the disciplines at one level of complexity, and processes them hierarchically at another level of complexity, achieving parallelism within disciplines, rather than across disciplines. A master-slave paradigm manages a coarse grained parallelism of the analysis and optimization codes required by the disciplines showing reasonable speedups and efficiencies on an Intel Paragon
Degree
thesis:*- Name thesis:degree_name
- Master of Science
- Level thesis:degree_level
- masters
- Discipline thesis:degree_discipline
- Computer Science and Applications
- Department dc:contributor.department
- Computer Science and Applications
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 1995
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Burgee, Susan L.
- Chair dc:contributor.committeechair
-
- Watson, Layne T.
- Committee members dc:contributor.committeemember
-
- Mason, William H.
- Ribbens, Calvin J.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Dc Identifier Other
- etd-08142009-040544
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/44241