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author:

Hua, H. (Hua, H..) [1] | Chen, X. (Chen, X..) [2] | Lin, H. (Lin, H..) [3]

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Scopus

Abstract:

Complex geometric features and stress features as well as their intricate relationships are the important factors causing the complexity of lightweight for large component. In order to better coordinate the stress distribution with lightweight goal, a knowledge-guided lightweight method based on geometric-stress feature correlation response is proposed. Multistage decomposition and three-steps feature express strategy is utilized to construct the geometric features relationship model firstly. By combining the influence significance for stress features with the association grade for geometric features, and reasoning under lightweight expectations, the geometric-stress correlation knowledge is extracted. Furthermore, a knowledge-guided lightweight algorithm integrated knowledge correlation response with intelligent searching is proposed. Finally, the lightweight of X-type caterpillar frame is taken as example to demonstrate the effectiveness of this method. © Published under licence by IOP Publishing Ltd.

Keyword:

Geometric-stress feature correlation; Integrated optimization; Knowledge correlation response; Knowledgeguided lightweight; Large complex component

Community:

  • [ 1 ] [Hua, H.]School of Mechanical and Automotive Engineering, FuJian University of Technology, Fuzhou, China
  • [ 2 ] [Chen, X.]School of Mechanical and Automotive Engineering, FuJian University of Technology, Fuzhou, China
  • [ 3 ] [Lin, H.]Mechanical and Electrical Engineering Practice Center, Fuzhou University, Fuzhou, China

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Source :

IOP Conference Series: Materials Science and Engineering

ISSN: 1757-8981

Year: 2019

Issue: 1

Volume: 531

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 1

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