Evomimetics: the biomimetic design thinking 2.0

Abstract

The consensus is that nature is a tremendous source of ideas for innovative designs that can meet various specific functional needs, relevant to society. Designs rely on structural, constructional, process-based and behavioral traits that all result from a natural trial-and-error cycle: evolution. Being one of the pillars of biomimicry, through billion years of evolution, nature has experimented and found what works and lasts, and what does not. Evidently, this has attracted scientists, especially engineers, trying to understand working natural designs, and translate them into applicable, working synthetic designs. The 'Biomimetic Design Method' forms the underlying conceptual framework to analytically decode biologically functions and designs. However, even though the evolutionary process is considered key to all this, it is generally overlooked in this conceptual thinking. The general assumption is that particular functions in organisms result from a natural selection process that optimized the underlying design for a particular function, thereby overlooking that an organism actually represents the possibly best compromise between all its functions needed to survive, to reproduce and to produce fit offspring. Many evolutionary processes thus yield suboptimal design components that, when put together, provide an optimized organismal design that manages to perform as good as needed, within a given environment. Such evolutionary limitations thus create possible pitfalls for bio-inspired design thinking. But, when considering them as a structural part of the design thinking process ('evomimetics'), they actually create opportunities for an improved translation of biology into optimally functioning designs. Using specific examples from evolutionary biology, these processes are explained, and recommendations are formulated.

Increasing morphological disparity and decreasing optimality for jaw speed and strength during the radiation of jawed vertebrates

“…Furthermore, in this study, the VMS surface is poorly characterized by the quadratic surface required for Arnold's fitness formulae (21). Here, we develop a new rank-based method of combining functional metrics into a single fitness metric, adapted from Pareto ranking algorithms (34,77). Pareto optimality has been used as a method of morphospace optimality analysis elsewhere with very promising results, although these studies operate on large-scale assumptions about the relationship between morphospace and function (78,79).…”

Paleomimetics: A Conceptual Framework for a Biomimetic Design Inspired by Fossils and Evolutionary Processes

“…Besides the environmental context, it is important to consider that organismal design is not a result of an effective optimisation process or the best absolute solution in terms of functional efficiency; its evolution is determined by several constraints [ 18 , 32 , 33 ]. Accordingly, many organismal traits can easily invalidate the biomimetic transfer, constituting real traps for design projects (see Section 2.1.2 ).…”

From Bioinspired to Bioinformed: Benefits of Greater Engagement From Biologists

“…However, effective bioinspiration/biomimetics is more complicated than simply selecting a species and replicating the desired adaptation; it can be difficult to identify the most functionally relevant traits to abstract into a design. One solution is to study the evolution of the trait in question using comparative methods, observing whether it appears in related species exhibiting the desired function, and whether it was lost in those without (Adriaens, 2019). Such a comparative approach enables insights into how traits are associated with specific environmental conditions.…”