Title:
A Systematic Process for Adaptive Concept Exploration

dc.contributor.advisor Mavris, Dimitri N.
dc.contributor.author Nixon, Janel Nicole en_US
dc.contributor.committeeMember Weston, Neil R.
dc.contributor.committeeMember Schrage,Daniel P
dc.contributor.committeeMember Vengazhiyil, Roshan J.
dc.contributor.department Aerospace Engineering en_US
dc.date.accessioned 2007-03-27T18:03:07Z
dc.date.available 2007-03-27T18:03:07Z
dc.date.issued 2006-11-29 en_US
dc.description.abstract This thesis presents a method for streamlining the process of obtaining and interpreting quantitative data for the purpose of creating a low-fidelity modeling and simulation environment. By providing a more efficient means for obtaining such information, quantitative analyses become much more practical for decision-making in the very early stages of design, where traditionally, quants are viewed as too expensive and cumbersome for concept evaluation. The method developed to address this need uses a Systematic Process for Adaptive Concept Exploration (SPACE). In the SPACE method, design space exploration occurs in a sequential fashion; as data is acquired, the sampling scheme adapts to the specific problem at hand. Previously gathered data is used to make inferences about the nature of the problem so that future samples can be taken from the more interesting portions of the design space. Furthermore, the SPACE method identifies those analyses that have significant impacts on the relationships being modeled, so that effort can be focused on acquiring only the most pertinent information. The results show that the combination of a tailored data set, and an informed model structure work together to provide a meaningful quantitative representation of the system while relying on only a small amount of resources to generate that information. In comparison to more traditional modeling and simulation approaches, the SPACE method provides a more accurate representation of the system using fewer resources to generate that representation. For this reason, the SPACE method acts as an enabler for decision making in the very early design stages, where the desire is to base design decisions on quantitative information while not wasting valuable resources obtaining unnecessary high fidelity information about all the candidate solutions. Thus, the approach enables concept selection to be based on parametric, quantitative data so that informed, unbiased decisions can be made. en_US
dc.description.degree Ph.D. en_US
dc.format.extent 2203606 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/13952
dc.language.iso en_US
dc.publisher Georgia Institute of Technology en_US
dc.subject Sequential design of experiments en_US
dc.subject Metamodels en_US
dc.subject Surrogate models en_US
dc.subject Concept selection en_US
dc.subject Decision making en_US
dc.subject Modeling and simulation en_US
dc.subject.lcsh Multidisciplinary design optimization en_US
dc.subject.lcsh Computer simulation en_US
dc.subject.lcsh Decision support systems en_US
dc.subject.lcsh Experimental design en_US
dc.title A Systematic Process for Adaptive Concept Exploration en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Mavris, Dimitri N.
local.contributor.corporatename Daniel Guggenheim School of Aerospace Engineering
local.contributor.corporatename Aerospace Systems Design Laboratory (ASDL)
local.contributor.corporatename College of Engineering
local.relation.ispartofseries Doctor of Philosophy with a Major in Aerospace Engineering
relation.isAdvisorOfPublication d355c865-c3df-4bfe-8328-24541ea04f62
relation.isOrgUnitOfPublication a348b767-ea7e-4789-af1f-1f1d5925fb65
relation.isOrgUnitOfPublication a8736075-ffb0-4c28-aa40-2160181ead8c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
relation.isSeriesOfPublication f6a932db-1cde-43b5-bcab-bf573da55ed6
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