In this paper, we present our vision for a framework to facilitate computationally-based aerospace vehicle design by improving the quality of the response surfaces that can be developed for a given cost. The response surfaces are developed using computational fluid dynamics (CFD) techniques of varying fidelity. We propose to improve the quality of a given response surface by exploiting the relationships between the response surface and the flow features that evolve in response to changes in the design parameters. The underlying technology, generalized feature mining, is employed to locate and characterize features as well as provide explanations for feature-feature and featurevehicle interactions. We briefly describe the components of our framework and outline two different strategies to improve the quality of a response surface. We also highlight ongoing efforts.