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基于多场耦合方法的厚截面复合材料固化过程的多目标优化

  • Zhenyi Yuan
  • , Yingjie Xu
  • , Guigeng Yang
  • , Yu Feng
  • , Zhenchao Yang
  • , Xinxing Tong
  • , Danlong Song
  • , Dajing Gao
  • , Yan Li
  • Xi'an University of Technology

科研成果: 期刊稿件文章同行评审

6 引用 (Scopus)

摘要

In order to reduce the mechanical properties and the curing residual stress of the thick composite caused by the excessive temperature peak during the curing process, a multi-objective optimization model based on the multi-physics coupling characteristics was developed to reduce the maximum curing temperature peak and the curing time. Firstly, a three-dimensional model which incorporated three typical sub-models including thermo-chemical model, resin viscosity model and resin flow model was established to investigate the development of temperature and thickness of laminate during curing process. The results of numerical model were compared with experiment data in reference and good accordance was obtained. Then, a multi-objective optimization method was applied to optimize curing process parameters by using a radial basis function neural network model (RBF) as the surrogate model. It is shown that the curing temperature peak has a nonlinear relationship with the first and second dwell temperature, which is related to the nonlinear characteristics of the curing process. In order to reduce the temperature peak, it is necessary to increase the first dwell temperature and reduce the second dwell temperature. Meanwhile, the dwell time should also be adjusted to shorten the total curing time. Compared to standard cure profiles, the proposed optimization method can significantly reduce the curing time and temperature peak for thick composite laminates.

投稿的翻译标题Multi-objective optimization for curing process of thick composite based on multi-physics coupling method
源语言繁体中文
页(从-至)526-535
页数10
期刊Fuhe Cailiao Xuebao/Acta Materiae Compositae Sinica
38
2
DOI
出版状态已出版 - 2月 2021

关键词

  • Composite
  • Curing process
  • Multi-physics coupling
  • Optimization
  • Surrogate model

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