scholarly journals A scalable approach for ideation in biologically inspired design

2014 ◽  
Vol 29 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Dennis Vandevenne ◽  
Paul-Armand Verhaegen ◽  
Simon Dewulf ◽  
Joost R. Duflou
Keyword(s):  
Natural Language ◽  
Information Structure ◽  
Biological Information ◽  
Reference Database ◽  
Automated Classification ◽  
Biologically Inspired ◽  
Large Numbers ◽  
Growing Body ◽  
Biologically Inspired Design

AbstractThis paper presents a bioinspiration approach that is able to scalably leverage the ever-growing body of biological information in natural-language format. The ideation tool AskNature, developed by the Biomimicry 3.8 Institute, is expanded with an algorithm for automated classification of biological strategies into the Biomimicry Taxonomy, a three-level, hierarchical information structure that organizes AskNature's database. In this way, the manual work entailed by the classification of biological strategies can be alleviated. Thus, the bottleneck is removed that currently prevents the integration of large numbers of biological strategies. To demonstrate the feasibility of building a scalable bioideation system, this paper presents tests that classify biological strategies from AskNature's reference database for those Biomimicry Taxonomy classes that currently hold sufficient reference documents.

scholarly journals SEABIRD: Scalable search for systematic biologically inspired design

2015 ◽  
Vol 30 (1) ◽  
pp. 78-95 ◽  
Author(s):  
Dennis Vandevenne ◽  
Paul-Armand Verhaegen ◽  
Simon Dewulf ◽  
Joost R. Duflou
Keyword(s):  
Design Process ◽  
State Of The Art ◽  
Knowledge Bases ◽  
Biological Database ◽  
Biologically Inspired ◽  
Growing Body ◽  
Design By Analogy ◽  
Biologically Inspired Design ◽  
Scalable Search ◽  
Design Inspiration

AbstractAs more and more people are increasingly turning to nature for design inspiration, tools and methodologies are developed to support the systematic bioideation process. State-of-the-art approaches struggle with expanding their knowledge bases because of interactive work required by humans per biological strategy. As an answer to this persistent challenge, a scalable search for systematic biologically inspired design (SEABIRD) system is proposed. This system leverages experience from the product aspects in design by analogy tool that identifies candidate products for between-domain design by analogy. SEABIRD is based on two conceptual representations, product and organism aspects, extracted from, respectively, a patent and a biological database, that enable leveraging the ever growing body of natural-language biological texts in the systematic bioinspired design process by eliminating interactive work by humans during corpus expansion. SEABIRD's search is illustrated and validated with three well-known biologically inspired design cases.

A Systematic Approach to Biologically-Inspired Engineering Design

2011 ◽  
Author(s):  
Jacquelyn K. S. Nagel ◽  
Robert B. Stone
Keyword(s):  
Engineering Design ◽  
Systematic Approach ◽  
Biological Information ◽  
Biological Knowledge ◽  
Biologically Inspired ◽  
Design Methodologies ◽  
Functional Representation ◽  
Engineering Designs ◽  
Engineered Systems ◽  
Biologically Inspired Design

To facilitate systematic biologically-inspired design, a design methodology that integrates with function-based design methodologies has been formalized. The goals of this methodology are to go beyond the element of chance, reduce the amount of time and effort required for developing biologically-inspired engineering solutions, and bridge the seemingly immense disconnect between the engineering and biological domains. Using functional representation and abstraction to describe biological systems presents the natural designs in an engineering context and allows designers to make connections between biological and engineered systems. Thus, the biological information is accessible to engineering designers with varying biological knowledge, but a common understanding of engineering design methodologies. Two approaches to validation are presented. One examines current biologically-inspired products either in production or in literature to see if the systematic approach to biologically-inspired design can reproduce the existing designs. The second investigates needs-based design problems that lead to plausible biologically-inspired solutions. This work has demonstrated the feasibility of using systematic design for the discovery of innovative engineering designs without requiring expert-level knowledge, but rather broad knowledge of many fields.

Automatically Populating the Biomimicry Taxonomy for Scalable Systematic Biologically-Inspired Design

2012 ◽  
Author(s):  
Dennis Vandevenne ◽  
Paul-Armand Verhaegen ◽  
Simon Dewulf ◽  
Joost R. Duflou
Keyword(s):  
Hierarchical Classification ◽  
Biological Database ◽  
Support Vector ◽  
Biologically Inspired ◽  
Cross Domain ◽  
Large Numbers ◽  
Vector Machines ◽  
Database Size ◽  
Design By Analogy ◽  
Biologically Inspired Design

Although Biologically-Inspired Design (BID) is gaining popularity, state-of-the-art approaches for systematic BID are still limited by the required interactive work which is proportional to the applied biological database size. This interactive work, depending on the adopted methodology, might encompass model instantiation for each strategy in the biological database, classification into a predefined scheme or extensive result filtering. This contribution presents a first scalable approach to systematic BID with the potential to leverage large numbers of biological strategies. First, a focused webcrawler, based on a combination of Support Vector Machines (SVM), continuously searches for biological strategies on the Internet. The solution to this needle-in-a-haystack task is shown to produce biological strategies interesting for cross-domain Design-by-Analogy (DbA). These resources are then automatically positioned into Ask Nature’s well-known Biomimicry Taxonomy; a 3-level hierarchical classification scheme that enables designers to identify biological strategies relevant to their specific design problem. This paper details the architecture of the proposed system, and presents results indicating the feasibility of the applied approach.

Retrieving Causally Related Functions From Natural-Language Text for Biomimetic Design

2014 ◽  
Vol 136 (8) ◽  
Author(s):  
Hyunmin Cheong ◽  
L. H. Shu
Keyword(s):  
Natural Language ◽  
User Study ◽  
Keyword Search ◽  
Causal Relation ◽  
Biologically Inspired ◽  
Retrieval Method ◽  
Natural Language Text ◽  
Biological Phenomena ◽  
Biologically Inspired Design ◽  
Language Text

Identifying biological analogies is a significant challenge in biomimetic (biologically inspired) design. This paper builds on our previous work on finding biological phenomena in natural-language text. Specifically, a rule-based computational technique is used to identify biological analogies that contain causal relations. Causally related functions describe how one function is enabled by another function, and support the transfer of functional structure from analogies to design solutions. The causal-relation retrieval method uses patterns of syntactic information that represent causally related functions in individual sentences, and scored F-measures of 0.73–0.85. In a user study, novice designers found that of the total search matches, proportionally more of the matches obtained with the causal-relation retrieval method were relevant to design problems than those obtained with a single verb-keyword search. In addition, matches obtained with the causal-relation retrieval method increased the likelihood of using functional association to develop design concepts. Finally, the causal-relation retrieval method enables automatic extraction of biological analogies at the sentence level from a large amount of natural-language sources, which could support other approaches to biologically inspired design that require the identification of interesting biological phenomena.

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