UNCLASSIFIED: Dist A. Approved for public release Multidisciplinary Design Optimization Under

Motivated by needs of concurrent multi-disciplinary design of a multi-purpose vehicle, a modeling and methodological approach to handling tradeoffs is presented. Each component has uncertain elements and a random performance which is in-fluenced by the performance of other components. The components may require different knowledge bases and models with different mathematical structures, time and size scales, calling for higher-level coordination. The theory of reproducing kernel Hilbert spaces provides the mathematical foundation for the approach. Performance is modeled as a random function of uncertainties that are considered as independent variables. Higher-level design decisions, the result of tradeoffs between alternative component designs, are based on information models of component performance functions. The models make use of second-order statistics of the performances and an algebra of their reduced-order representations. Multicriteria optimization methods are used to determine preferred overall designs.