The analysis of engineering systems must often be conducted using complex, non-hierarchic, coupled, discipline-speci c methods. When the cost of performing these individual analyses is high, it is impractical to apply many current optimization methods to this type of system to achieve improved designs. Consequently, methods are being developed which attempt to reduce the cost of designing or optimizing non-hierarchic systems. This paper details the application of an extension of the Concurrent Subspace Optimization (CSSO) approach through the use of neural network based response surface mappings. The response surface mappings are used to allow the discipline designer to account for discipline coupling and the impact of design decisions on the system at the discipline level as well as for system level design coordination. The ability of this method to identify globally optimal designs is discussed using two example system design problems. Comparisons between this algorithm and full system optimization are made with regard to computational expense associated with obtaining optimal system designs.

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg [1,2] is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.

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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

An experimental study of the flow around a cylinder with rms a single straight perturbation was conducted in a wind tunnel. With this bluff body, positioned in a uniform crossfiow, the vortex shed-S ding frequency and other flow characteristics could be manipulated, Smax The Strouhal number has been shown to be a function of the perturbation angular position, 0p, as well as the perturbation size Smi, t and Reynolds number. As much as a 50% change in Strouhal Uc number could be achieved, simply by changing 0p by 1 ~ The perturbation size compared to the local boundary layer thickness, 6, Umax was varied from approximately 1 6 to about 206. The Reynolds U~ number was varied from 10,000 to 40,000. For perturbation sizes U~c approximately 5 6 to 20 fi and Reynolds numbers of 20,000 to 40,000, x a consistent Strouhai number variation with 0 r was observed.A detailed investigation of the characteristic Strouhal number z variation has shown that varying 0p had a significant influence on the boundary layer separation and transition to turbulence. These Ax significant changes occurring in the boundary layer have been A~ shown to cause variations in the spacing between the shear layers, base pressure, drag, lift, and the longitudinal spacing between the vortices in the vortex street.