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The practical application of optimization methods to non-hierarchic, coupled, multidisciplinary systems has been hampered by the costs associated with the use of complex discipline-speci c analysis procedures. When the cost of performing these individual analyses is high, it is impractical to apply many current optimization methods to most practical systems in order to identify improved designs. This paper details an extended formulation and application of the Concurrent Subspace Optimization (CSSO) approach to this class of system design problems. In this application neural network based response surface mappings are used to allow the discipline designer to account for discipline coupling as well as for system level design coordination. The application is the design of a \hovercraft" and includes external con guration, structures, performance and propulsion disciplines.

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