I. INTRODUCTIONExploring the design space with the aim of finding feasible, let alone optimal solutions is not trivial. Essentially, this involves finding a solution to an inverse problem. That is, a relatively small number of (presumably) known requirements and performance characteristics need to be mapped onto a much larger number (space) of unknown design parameters, subject to constraints. The inverse problem, of course, is generic and forms parts of the study of complex systems, from ecology [1,2] to engineering design [3], where the integration of an expanding set of (validated) numerical methods and models is used to investigate scenarios and to predict outcomes.The work presented here lies within this context, with a particular emphasis on computational intelligence methods and tools for interactive design space exploration. The scope is restricted (but not limited) to conceptual computational design where a complex product, for example aircraft, ship, and so on, is described by a large number of computational models related to geometry parameterization, performance, cost, and so forth. It is assumed that the computational models are black-boxes (e.g., compiled code) which contain low-fidelity code (e.g., parametric/empirical equations) and/or surrogate models. This assumption reflects the realities of the commercial world in which the content of a model is usually a closely guarded intellectual property.There are a number of challenges associated with such complex and relatively little studied computational systems:

Presented is a novel framework for early systems architecture design. The framework defines data structures and algorithms that enable the systems architect to operate interactively and simultaneously in both the functional and logical domains. A prototype software tool, called AirCADia Architect, was implemented, which allowed the framework to be evaluated by practicing aircraft systems architects. The evaluation confirmed that, on the whole, the approach enables the architects to effectively express their creative ideas when synthesizing new architectures while still retaining control over the process.

Presented is a method for automated sizing of airframe systems, ultimately aiming to enable an efficient and interactive systems architecture evaluation process. The method takes as input the logical view of the system architecture. A source-sink approach combined with a Design Structure Matrix (DSM) sequencing algorithm is used to orchestrate the sequence of the subsystem sizing tasks. Bipartite graphs and a maximum matching algorithm are utilized to identify and construct the computational sizing workflows. A recursive algorithm, based on fundamental dimensions of additive physical quantities (e.g., weight, power, etc.) is employed to aggregate variables at the system level. The evaluation, based on representative test cases confirmed the correctness of the proposed method. The results also showed that the proposed approach overcomes certain limitations of existing methods and looks very promising as an initial systems architectural design enabler.

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Presented is an approach for interactive margin management. Existing methods enable a fixed set of allowable margin combinations to be identified, but these have limitations with regard to supporting interactive exploration of the effects of: 1) margins on other margins, 2) margins on performance and 3) margins on the probabilities of constraint satisfaction. To this purpose, the concept of a margin space is introduced. It is bi-directionally linked to the design space, to enable the designer to understand how assigning margins on certain parameters limits the allowable margins that can be assigned to other parameters. Also, a novel framework has been developed. It incorporates the margin space concept as well as enablers, including interactive visualization techniques, which can aide the designer to explore the margin and design spaces dynamically, as well as the effects of margins on the probability of constraint satisfaction and on performance. The framework was implemented into a prototype software tool, AirCADia, which was used for a qualitative evaluation by practicing designers. The evaluation, conducted as part of the EU TOICA project, demonstrated the usefulness of the approach.