CONCURRENT SUBSPACE OPTIMIZATION USING DESIGN VARIABLE SHARING IN A DISTRIBUTED COMPUTING ENVIRONMENT

This paper reviews recent implementation advances and modifications in the continued development of a Concurrent Subspace Optimization (CSSO ) algorithm for Multidisciplinary Design Optimization (MDO). The CSSO- MDO algorithm implemented in this research incorporates a Coordination Procedure of System Approximation (CP-SA) for design updates. This st udy also details the use of a new discipline-based decomposition strat egy which provides for design variable sharing across discipline desig n regimes (i.e., subspaces). A graphical user interface is developed w hich provides for menu driven execution of MDO algorithms and results display; this new programming environment highlights the modularity of the CSSO algorithm. The algorithm is implemented in a distributed com puting environment using the graphical user interface, providing for t ruly concurrent discipline design. Implementation studies introduce tw o new multidisciplinary design test problems: the optimal design of a high-performance, low-cost structural system, and the preliminary sizi ng of a general aviation aircraft concept for optimal performance. Sig nificant time savings are observed when using distributed computing fo r concurrent design across disciplines. The use of design variable sha ring across disciplines does not introduce any difficulties in impleme ntation as the design update in the CSSO-MDO algorithm is generated in the CP-SA. Application of the CSSO algorithm results in a considerabl e decrease in the number of system analyses required for optimization in both test problems. More importantly, for the fully coupled aircraf t concept sizing problem, a significant reduction in the number of ind ividual contributing analyses is observed.