Beyond analogy: A model of bioinspiration for creative design. Issue 2 (18th April 2016)
- Record Type:
- Journal Article
- Title:
- Beyond analogy: A model of bioinspiration for creative design. Issue 2 (18th April 2016)
- Main Title:
- Beyond analogy: A model of bioinspiration for creative design
- Authors:
- Salgueiredo, Camila Freitas
Hatchuel, Armand - Editors:
- Hanna, Sean
Bentley, Peter - Abstract:
- Abstract: Is biologically inspired design only an analogical transfer from biology to engineering? Actually, nature does not always bring "hands-on" solutions that can be analogically applied in classic engineering. Then, what are the different operations that are involved in the bioinspiration process and what are the conditions allowing this process to produce a bioinspired design? In this paper, we model the whole design process in which bioinspiration is only one element. To build this model, we use a general design theory, concept–knowledge theory, because it allows one to capture analogy as well as all other knowledge changes that lead to the design of a bioinspired solution. We ground this model on well-described examples of biologically inspired designs available in the scientific literature. These examples include Flectofin ®, a hingeless flapping mechanism conceived for façade shading, and WhalePower technology, the introduction of bumps on the leading edge of airfoils to improve aerodynamic properties. Our modeling disentangles the analogical aspects of the biologically inspired design process, and highlights the expansions occurring in both knowledge bases, scientific (nonbiological) and biological, as well as the impact of these expansions in the generation of new concepts (concept partitioning). This model also shows that bioinspired design requires a special form of collaboration between engineers and biologists. Contrasting with the classic one-way transferAbstract: Is biologically inspired design only an analogical transfer from biology to engineering? Actually, nature does not always bring "hands-on" solutions that can be analogically applied in classic engineering. Then, what are the different operations that are involved in the bioinspiration process and what are the conditions allowing this process to produce a bioinspired design? In this paper, we model the whole design process in which bioinspiration is only one element. To build this model, we use a general design theory, concept–knowledge theory, because it allows one to capture analogy as well as all other knowledge changes that lead to the design of a bioinspired solution. We ground this model on well-described examples of biologically inspired designs available in the scientific literature. These examples include Flectofin ®, a hingeless flapping mechanism conceived for façade shading, and WhalePower technology, the introduction of bumps on the leading edge of airfoils to improve aerodynamic properties. Our modeling disentangles the analogical aspects of the biologically inspired design process, and highlights the expansions occurring in both knowledge bases, scientific (nonbiological) and biological, as well as the impact of these expansions in the generation of new concepts (concept partitioning). This model also shows that bioinspired design requires a special form of collaboration between engineers and biologists. Contrasting with the classic one-way transfer between biology and engineering that is assumed in the literature, the concept–knowledge framework shows that these collaborations must be "mutually inspirational" because both biological and engineering knowledge expansions are needed to reach a novel solution. … (more)
- Is Part Of:
- AI EDAM. Volume 30:Issue 2(2016)
- Journal:
- AI EDAM
- Issue:
- Volume 30:Issue 2(2016)
- Issue Display:
- Volume 30, Issue 2 (2016)
- Year:
- 2016
- Volume:
- 30
- Issue:
- 2
- Issue Sort Value:
- 2016-0030-0002-0000
- Page Start:
- 159
- Page End:
- 170
- Publication Date:
- 2016-04-18
- Subjects:
- Biologically Inspired Design, -- Concept–Knowledge Design Theory, -- Innovation
Engineering design -- Data processing -- Periodicals
Artificial intelligence -- Periodicals
Expert systems (Computer science) -- Periodicals
620.00420285 - Journal URLs:
- http://www.journals.cambridge.org/jid%5FAIE ↗
- DOI:
- 10.1017/S0890060416000044 ↗
- Languages:
- English
- ISSNs:
- 0890-0604
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 2205.xml