Composition, Management, and Exploration of Computational Studies at Early Design Stage

Abstract

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:

A Set-based Approach for Coordination of Multi-level Collaborative Design Studies

“…In this section, the proposed method is evaluated through a realistic (but not real) aircraft sizing test-case which is specified in Section V.A. The coordination process is then demonstrated in Section V.B, using an in-house software, AirCADia [16], [24]. In Section V.C, the proposed method is compared with point-based coordination and feedback from practicing designers is summarized in section V.D.…”

“…In previous research [16], several enablers for SBD, including the interactive iso-contour and parallel coordinate plot were developed. The former can be used for constraint analysis, where a multi-dimensional design space is projected into 2D slices).…”

Margin Allocation and Tradeoff in Complex Systems Design and Optimization

“…To perform the evaluation, the methods and enablers proposed in Section III were implemented into an existing in-house model-based design tool, called AirCADia [21]. This software tool contains inbuilt enablers for performing optimization, design space exploration, as well as deterministic and robust design studies.…”

Set-Based Approach to Passenger Aircraft Family Design

“…Figure 3.15 also shows the tools that can be employed for down-selection through constraint satisfaction. A constraint analysis method based on iso-contours is proposed for the down-selection of aircraft family set [125]. The method divides the multi-dimensional design space into multiple 2D projections or slices (contour plots) which show the contour line (also called isoline) of the constraints for two design variables along which the constraint has a constant value [126].…”

“…A more detailed description of the classes and the joining algorithm can be found in references [127] and [128]. The tool uses the object oriented, components-based approach and can be used to build complex aircraft configurations.…”