Advanced search
1 file | 334.07 KB Add to list

Evomimetics : the biomimetic design thinking 2.0

Author
Organization
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.
Keywords
Biomimicry, biomimetics, design, evolution, conceptual, constraints, optimization, adaptation, EVOLUTION, SELECTION, GENES, INSPIRATION, PERFORMANCE, INTEGRATION, MODULARITY

Downloads

  • 11927.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 334.07 KB

Citation

Please use this url to cite or link to this publication:

MLA
Adriaens, Dominique. “Evomimetics : The Biomimetic Design Thinking 2.0.” BIOINSPIRATION, BIOMIMETICS, AND BIOREPLICATION IX, edited by Raúl J Martín-Palma et al., vol. 10965, 2019.
APA
Adriaens, D. (2019). Evomimetics : the biomimetic design thinking 2.0. In R. J. Martín-Palma, M. Knez, & A. Lakhtakia (Eds.), BIOINSPIRATION, BIOMIMETICS, AND BIOREPLICATION IX (Vol. 10965). Denver, CO, USA.
Chicago author-date
Adriaens, Dominique. 2019. “Evomimetics : The Biomimetic Design Thinking 2.0.” In BIOINSPIRATION, BIOMIMETICS, AND BIOREPLICATION IX, edited by Raúl J Martín-Palma, Mato Knez, and Akhlesh Lakhtakia. Vol. 10965.
Chicago author-date (all authors)
Adriaens, Dominique. 2019. “Evomimetics : The Biomimetic Design Thinking 2.0.” In BIOINSPIRATION, BIOMIMETICS, AND BIOREPLICATION IX, ed by. Raúl J Martín-Palma, Mato Knez, and Akhlesh Lakhtakia. Vol. 10965.
Vancouver
1.
Adriaens D. Evomimetics : the biomimetic design thinking 2.0. In: Martín-Palma RJ, Knez M, Lakhtakia A, editors. BIOINSPIRATION, BIOMIMETICS, AND BIOREPLICATION IX. 2019.
IEEE
[1]
D. Adriaens, “Evomimetics : the biomimetic design thinking 2.0,” in BIOINSPIRATION, BIOMIMETICS, AND BIOREPLICATION IX, Denver, CO, USA, 2019, vol. 10965.
@inproceedings{8608401,
  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.},
  articleno    = {1096509},
  author       = {Adriaens, Dominique},
  booktitle    = {BIOINSPIRATION, BIOMIMETICS, AND BIOREPLICATION IX},
  editor       = {Martín-Palma, Raúl J and Knez, Mato and Lakhtakia, Akhlesh},
  isbn         = {9781510625853},
  issn         = {0277-786X},
  keywords     = {Biomimicry,biomimetics,design,evolution,conceptual,constraints,optimization,adaptation,EVOLUTION,SELECTION,GENES,INSPIRATION,PERFORMANCE,INTEGRATION,MODULARITY},
  language     = {eng},
  location     = {Denver, CO, USA},
  title        = {Evomimetics : the biomimetic design thinking 2.0},
  url          = {http://dx.doi.org/10.1117/12.2514049},
  volume       = {10965},
  year         = {2019},
}

Altmetric
View in Altmetric
Web of Science
Times cited: