A Coarse-Grained Parallel Variable-Complexity Multidisciplinary Optimization Paradigm

Abstract

Modem aerospace vehicle design requires the interac tion of multiple disciplines, traditionally processed in a sequential order. Multidisciplinary optimization (MDO), a formal methodology for the integration of these disci plines, is evolving toward methods capable of replacing the traditional sequential methodology of aerospace vehi cle design by concurrent 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 approxima tions is presented here for the particular instance of the design of a high-speed civil transport (HSCT). This para digm interleaves the disciplines at 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-grained parallelism of the analysis and optimization codes required by the disciplines showing reasonable speedups and efficiencies on an Intel Paragon.