Keywords: structural design, evolutionary computation, evolutionary design, coevolutionary design, morphogenesis, generative representations, cellular automata.

This paper explores the state of the art in structural design inspired by nature and proposes an improved understanding of this emerging paradigm and its major components. The three categories of inspiration by nature introduced in the paper include visual, conceptual, and computational inspiration. The paper emphasizes the importance of computational inspiration for automated conceptual design. It is the most intriguing but still poorly understood and difficult approach, yet with the greatest potential to revolutionize design [1]. In this case, inspiration occurs on the level of computational mechanisms, which are inspired by the mechanisms governing the processes and phenomena occurring in nature.

Several key sources of computational inspiration from nature are identified and briefly described, including evolutionary computation, coevolutionary computation, cellular automata, and TRIZ [2]. They are related to three major design objectives, namely optimality, creativity, and robustness. In particular, design generation mechanisms based on cellular automata are introduced with some details. They are inspired by the processes of morphogenesis occurring in nature and have great potential to generate novel designs. In this case, the design generation mechanisms are encoded in so-called generative representations, which are also briefly described.

The paper also proposes three levels of integration of computational mechanisms inspired by nature and discusses their relationship to design objectives. At the lowest level of integration, individual mechanisms are used separately to achieve corresponding design objectives. For example, evolutionary computation is employed to optimize structural systems and generative representations (e.g., based on cellular automata) to generate novel designs. The paper calls this level `one-dimensional' design because only a single design objective is considered at a time.

At a higher integration level, two computational mechanisms inspired by nature are combined to address two design objectives. The paper provides an example of how evolutionary computation and generative representations can be integrated in morphogenic evolutionary design [3,4] and thus achieve two important design objectives: generation of novel designs concepts and their subsequent optimization. Similarly, integration of other computational mechanisms inspired by nature is suggested and their potential for structural design is described. This level of integration (called in the paper `two-dimensional' design) corresponds to the current state of the art in nature inspired design research.

Finally, at the highest integration level, the three computational mechanisms discussed in this paper are combined in an integrated nature-inspired design framework. This `three-dimensional' design constitutes a useful reference for future research in engineering design and building future design support tools. Such tools are necessary to provide guidance through the structural design process and to acquire relevant design knowledge.

The paper also proposes a unified description of structural design inspired by nature in the form of attributes and their values. This unified description is the first step in the direction of a unified structural design model, when inspiration by nature is used. When such a model is available the new structural design paradigm could be better understood, taught, and used in practice.

1

Arciszewski, T., and De Jong, K.A. (2001). "Evolutionary computation in civil engineering: research frontiers", In B.H.V. Topping (Ed.), Civil and Structural Engineering Computing: 2001, Saxe-Coburg Publications, Stirling, UK.

2

Altshuller, G. (1969). Algorithm of invention. Moscow: Moskowskij Raboczij Publishing House.

3

Kicinger, R., Arciszewski, T., and De Jong, K. A. (2004). "Morphogenic evolutionary design: cellular automata representations in topological structural design", In I.C. Parmee (Ed.), Adaptive Computing in Design and Manufacture VI. London, UK: Springer-Verlag, 25-38.

4

Kicinger, R. (2004). "Emergent Engineering Design: Design creativity and optimality inspired by nature", Ph.D. Dissertation, School of Information Technology and Engineering, George Mason University, Fairfax, VA, USA.

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