Using Response Surface Metamodels to Optimize the Aerodynamic Performance of a High Speed Standoff Missile within a Multi-Disciplinary Environment

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AIAA-2002-5855.pdf (457.64 KB)
Author(s)
Won, Henry W.
Levine, Simon B.
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Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
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http://hdl.handle.net/1853/6293
Abstract
This report summarizes the feasibility of implementing a metamodel, consisting of Response Surface Equations (RSE), in a High Speed Standoff Missile (HSSM) multi-disciplinary mission analysis. The metamodel, which is a representation of a physics based engineering tool, is used to optimize the missile aerodynamic performance for any given mission. Each mission is defined as a function of the mission parameters. The optimization schemes use flight condition information and missile requirements from the upstream mission analysis, and find the optimum missile geometry parameters for that mission. The geometry parameters are then returned to the system analysis to complete the mission evaluation under optimal aerodynamic performance. The optimization scheme allows the variation of the missile geometry without increasing the number of runs in a parametric design study, such as a Design of Experiments (DOE). Results are achieved for two modules, namely the fuselage aerodynamics and the tail fin aerodynamics. Metamodel optimization schemes were created and implemented into the modules. The transformed modules were tested to observe the behavior and accuracy of the schemes. Comparison is made between the optimal geometries found with and without the use of the metamodel. The comparison shows that the metamodel optimization returns similar results, and does so in a significantly shorter amount of time. In addition, the aerodynamic design spaces are analyzed in conjunction with the optimization behavior to predict possible problems in the optimization process. The use of the metamodel is shown to alleviate optimization problems such as multi-modal design spaces. The results indicate the usefulness and promise for the proposed metamodel optimization scheme for use in a large scale preliminary design analysis.
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2002-10
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1905 bytes
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