Research on Function Based Method for Bio-Inspiration Knowledge Modeling and Transformation

Biological inspirations are good design mimicry resources. This paper proposes a function based approach for modeling and transformation of bio-inspiration design knowledge. A general functional modeling method for biological domain and engineering domain design knowledge is introduced. Functional s...

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Published inShanghai jiao tong da xue xue bao Vol. 19; no. 2; pp. 190 - 198
Main Author 谷朝臣 胡洁 彭颖红
Format Journal Article
LanguageEnglish
Published Heidelberg Shanghai Jiaotong University Press 01.04.2014
Subjects
Architecture
Biological
Computer Science
Electrical Engineering
Engineering
Inspiration
Life Sciences
Materials Science
Mathematical models
Mimicry
Similarity
Topology
Transformations
Transformations (mathematics)
TH 122
knowledge transfer
functional reasoning
bio-inspired design
ontology
functional modeling
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Summary:Biological inspirations are good design mimicry resources. This paper proposes a function based approach for modeling and transformation of bio-inspiration design knowledge. A general functional modeling method for biological domain and engineering domain design knowledge is introduced. Functional similarity based bio-inspiration transformation between biological domain and engineering domain is proposed. The biological function topology transfer and analog solution recomposition are also discussed in this paper.
Bibliography:Biological inspirations are good design mimicry resources. This paper proposes a function based approach for modeling and transformation of bio-inspiration design knowledge. A general functional modeling method for biological domain and engineering domain design knowledge is introduced. Functional similarity based bio-inspiration transformation between biological domain and engineering domain is proposed. The biological function topology transfer and analog solution recomposition are also discussed in this paper.
bio-inspired design, functional modeling, ontology, functional reasoning, knowledge transfer
GU Chao-chen , HU Jie, PENG Ying-hong（Institute of Electromechanical Design and Knowledge Based Engineering, School of Mechanical Engineering Shanghai Jiaotong University, Shanghai 200240, China）
31-1943/U
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SourceType-Scholarly Journals-1
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ISSN:1007-1172
1995-8188
DOI:10.1007/s12204-014-1489-3