Steel and Composite Structures

  • 제47권5호
  • /
  • Pages.601-613
  • /
  • 2023
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  • 1229-9367(pISSN)
  • /
  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Finite element computer simulation of twinning caused by plastic deformation of sheet metal

  • Fuyuan Dong (School of Materials Science and Engineering, North Minzu University) ;
  • Wang Xu (School of Materials Science and Engineering, North Minzu University) ;
  • Zhengnan Wu (School of Materials Science and Engineering, North Minzu University) ;
  • Junfeng Hou (School of Materials Science and Engineering, North Minzu University)
  • 투고 : 2021.12.11
  • 심사 : 2023.04.19
  • 발행 : 2023.06.10
⟨ 이전 논문 다음 논문 ⟩

초록

Numerous methods have been proposed in predicting formability of sheet metals based on microstructural and macro-scale properties of sheets. However, there are limited number of papers on the optimization problem to increase formability of sheet metals. In the present study, we aim to use novel optimization algorithms in neural networks to maximize the formability of sheet metals based on tensile curve and texture of aluminum sheet metals. In this regard, experimental and numerical evaluations of effects of texture and tensile properties are conducted. The texture effects evaluation is performed using Taylor homogenization method. The data obtained from these evaluations are gathered and utilized to train and validate an artificial neural network (ANN) with different optimization methods. Several optimization method including grey wolf algorithm (GWA), chimp optimization algorithm (ChOA) and whale optimization algorithm (WOA) are engaged in the optimization problems. The results demonstrated that in aluminum alloys the most preferable texture is cube texture for the most formable sheets. On the other hand, slight differences in the tensile behavior of the aluminum sheets in other similar conditions impose no significant decreases in the forming limit diagram under stretch loading conditions.

키워드

과제정보

This work was supported by the Natural Science Foundation of China (51901002), Western Young Scholars Program (XAB2021YW12), Project (TJGC2020142) supported by Ningxia Youth Talents Supporting Program Young Top Notch Talents Supporting Program.

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