Title:
Transforming Aerodynamic Datasets into Parametric Equations for use in Multi-disciplinary Design Optimization

dc.contributor.author Scott, Jeffery M. en_US
dc.contributor.author Olds, John R.
dc.contributor.corporatename American Institute of Aeronautics and Astronautics
dc.date.accessioned 2006-03-17T15:59:36Z
dc.date.available 2006-03-17T15:59:36Z
dc.date.issued 1998-10
dc.description 1998 Defense and Civil Space Programs Conference and Exhibit Huntsville, AL, October 28-30, 1998. en_US
dc.description.abstract This paper presents a method of transforming aerodynamic datasets generated in Aerodynamic Preliminary Analysis System (APAS) into parametric equations which may subsequently be used in a multidisciplinary design optimization (MDO) environment for analyzing aerospace vehicles. APAS is an analysis code which allows the user to create a simple geometric model of a vehicle and then calculate the aerodynamic force coefficients of lift, drag, and pitching moment over a wide range of flight conditions. As such, APAS is a very useful tool for conceptual level vehicle designs since it allows the force coefficients for a given design to be calculated relatively quickly and easily. However, APAS suffers from an outdated user interface and, because it is tedious to generate a new dataset during each design iteration, it is quite difficult to integrate into an MDO framework. Hence the desire for a method of transforming the APAS output into a more usable form. The approach taken and described in this paper involves the use of regression analysis techniques and response surface methodology to accomplish the data transformation with two goals in mind. The first goal was to develop a parametric model for calculating the aerodynamic coefficients for a single unique geometry. The second goal was to extend this model to capture the effects of changes in vehicle geometry. This paper presents the results and gives the model developed for analyzing a sample vehicle for both cases.
dc.description.abstract This paper presents a method of transforming aerodynamic datasets generated in Aerodynamic Preliminary Analysis System (APAS) into parametric equations which may subsequently be used in a multidisciplinary design optimization (MDO) environment for analyzing aerospace vehicles. APAS is an analysis code which allows the user to create a simple geometric model of a vehicle and then calculate the aerodynamic force coefficients of lift, drag, and pitching moment over a wide range of flight conditions. As such, APAS is a very useful tool for conceptual level vehicle designs since it allows the force coefficients for a given design to be calculated relatively quickly and easily. However, APAS suffers from an outdated user interface and, because it is tedious to generate a new dataset during each design iteration, it is quite difficult to integrate into an MDO framework. Hence the desire for a method of transforming the APAS output into a more usable form. The approach taken and described in this paper involves the use of regression analysis techniques and response surface methodology to accomplish the data transformation with two goals in mind. The first goal was to develop a parametric model for calculating the aerodynamic coefficients for a single unique geometry. The second goal was to extend this model to capture the effects of changes in vehicle geometry. This paper presents the results and gives the model developed for analyzing a sample vehicle for both cases.
dc.format.extent 262773 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/8421
dc.language.iso en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original American Institute of Aeronautics and Astronautics (AIAA)
dc.relation.ispartofseries SSDL ; AIAA 98-5208 en_US
dc.subject Aerodynamic coefficients
dc.subject Multidisciplinary design optimization
dc.subject Regression analysis
dc.subject Parametric modeling
dc.subject Geometric models
dc.title Transforming Aerodynamic Datasets into Parametric Equations for use in Multi-disciplinary Design Optimization en_US
dc.type Text
dc.type.genre Paper
dspace.entity.type Publication
local.contributor.corporatename Space Systems Design Laboratory (SSDL)
local.contributor.corporatename Daniel Guggenheim School of Aerospace Engineering
local.contributor.corporatename Daniel Guggenheim School of Aerospace Engineering
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relation.isOrgUnitOfPublication a348b767-ea7e-4789-af1f-1f1d5925fb65
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