One of the CFD problem is Turbulent Model. This model is proposed so many, however, they cannot capture the realistic phenomena in the present.

In this research, the Delta Wing, which is recently experimented in NASA Langley Research Center, is analysed by using several turbulence models, and then the results is compared with the empirical data. In the experiment, the Second Primary Vortex which has same rotation on inboard wing of the primary vortex was captured. However, its identity cannot be clear. The objective of this analysis is to solve the second primary vortex through CFD visualization of three-dimensional vortex structure.

The result shows that the modified Spalart-Allmaras one equation model can capture the second primary vortex, and it reveals that the second primary vortex is a shear layer merging into the primary vortex occured later due to the leading-edge bluntness. Moreover, it reveals that this primary vortex classifies Open-Type Separation.

It should be performed that the cost of space launch systerm reduce, because development of space technology get more active. Therefore, USA and EU have been developing RLV (Reusable Launch Vehicle) for this legitimate requirement.

SSTO (Single Stage To Orbit) , which goes back to launch site like airplane, is the most effective system, however it is difficult to make with present technology. TSTO (Two Stage To orbit) , which has booster and orbiter stage, can give this requirement using present technology.

Body should be salvaged to reuse. Most effective way is launched fuselage flies back to launch site under own power. However, fuselage must have enough lift-to-drag ratio for this way.

In this study, wing shape of reusable booster stage is optimized using evolutionary algorithms in aerodynamics with CFD.

Consequently, the tradeoff information among four objective functions has been revealed. Moreover, data mining for the design space has been performed using Self-Organizing Map(SOM). Data mining proveds knowledge regarding the design space, which is considered an important facet of solving optimization problems.

We should optimize aerospace vehicle among many disciplines such as aerodynamics, structures, control, propulsion, and noise to discuss and apply practical problems for engineering. That is, Multidisciplinary Design Optimization is needed.

In this study, the multi-objective optimization tool will be generated for multi-field such as aerodynamics and structure dynamics. For aerodynamic evaluation, Navier-Stokes equations are solved. For structural evaluation, NASTRAN is applied to analyze strength/flutter. The objective function is the minimization of block fuel. In addition, the minimization of maximum take-off weight and drag divergence between subsonic and transonic conditions.

The result reveals that there is a tradeoff between block fuel and drag divergence, and then the knowledge in the design space is obtained by using SOM. Because its design knowledge generated the better individual compared with the initial and optimized solutions, data mining is a significant facet for the optimization problem.