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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/118885...
Part of book or chapter of book . 2006 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2017
Data sources: DBLP
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Bio-inspiration: Learning Creative Design Principia

Authors: Tomasz Arciszewski; Joanna Cornell;

Bio-inspiration: Learning Creative Design Principia

Abstract

Reusing or modifying known design concepts cannot meet new challenges facing engineering systems. However, engineers can find inspiration outside their traditional domains in order to develop novel design concepts. The key to progress and knowledge acquisition is found in inspiration from diverse domains. This paper explores abstract knowledge acquisition for use in conceptual design. This is accomplished by considering body armor in nature and that developed in Europe in the last Millennium. The research is conducted in the context of evolution patterns of the Directed Evolution Method, which is briefly described. The focus is on conceptual inspiration. Analysis results of historic and natural body armor evolution are described and two sets of acquired creative design principia from both domains are presented. These principia can be used to stimulate human development of novel design concepts. Creative design principia, combined with human creativity, may lead to revolutionarychanges, rather than merely evolutionarysteps, in the evolution of engineering systems.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Average
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