Concurrent Subspace Optimization Using Design Variable Sharing in a Distributed Computing Environment

Abstract

This paper reviews recent implementation advances and modifications in the continued development of a Concurrent Subspace Op timization (CSSO) algorithm for Multidisciplinary Design Optimization (MDO) The CSSO MDO algorithm implemented in this research incor porates a Coordination Procedure of System Approximation (CP-SA) for design updates This study also details the use of a new discipline based decomposition strategy which provides for design variable sharing across discipline design regimes (i e subspaces) A graphical user interface is developed which 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 computing environment using the graphical user interface providing for truly concurrent discipline design Implementation studies introduce two new multidisciplinary design test problems the optimal design of a high performance, low cost structural system and the preliminary sizing of a general aviation aircraft concept for optimal perfor mance Significant time savings are observed when using distributed computing for concurrent design across disciplines The use of design vari able sharing across disciplines does not introduce any difficulties in implementation as the design update in the CSSO MDO algorithm is gener ated in the CP-SA Application of the CSSO algorithm results in a considerable decrease in the number of system analyses required for optimization in both test problems More importantly for the fully coupled aircraft concept sizing problem a significant reduction in the number of individual contributing analyses is observed