A COARSE-GRAINED PARALLEL VARIABLE-COMPLEXITY MULTIDISCIPLINARY OPTIMIZATION PARADIGM

Modern aerospace vehicle design requires the interaction of multiple d isciplines, traditionally processed in a sequential order, Multidiscip linary optimization (MDO), a formal methodology for the integration of these disciplines, is evolving toward methods capable of replacing th e traditional sequential methodology of aerospace vehicle design by co ncurrent algorithms, with both an overall gain in product performance and a decrease in design time. A parallel MDO paradigm using variable- complexity modeling and multipoint response surface approximations is presented here for the particular instance of the design of a high-spe ed civil transport (HSCT). This paradigm interleaves the disciplines a t one level of complexity and processes them hierarchically at another level of complexity, achieving parallelism within disciplines rather than across disciplines. A master-slave paradigm manages a coarse-grai ned parallelism of the analysis and optimization codes required by the disciplines showing reasonable speedups and efficiencies on an Intel Paragon.