An integrated micromechanical model and BP neural network for predicting elastic modulus of 3-D multi-phase and multi-layer braided composite. (April 2015)

• Record Type: Journal Article
• Authors: Xu, Yingjie; You, Tao; Du, Chenglie
• Is Part Of: Composite structures. Volume 122(2015)
• Page Start: 308
• Page End: 315
• Publication Date: 2015-04
• Subjects: 3-D multi-phase and multi-layer braided composite -- Micromechanical model -- BP neural network -- Elastic modulus; Composite construction -- Periodicals; Composites -- Périodiques; 624.18
• DOI: 10.1016/j.compstruct.2014.11.052
• Languages: English
• ISSNs: 0263-8223

Abstract

Abstract: This research is aimed to develop an integrated methodology based on micromechanical model and neural network to predict elastic modulus of 3-D multi-phase and multi-layer (MPML) braided composite. The micromechanical model including two-scale RVC modeling and strain energy model is firstly proposed. A back propagation (BP) neural network model is then developed to map the complex non-linear relationship between microstructural parameters and elastic modulus of the composite. The 3-D braided C/C-SiC composite is used as a case study. Predictions are compared with experimentally measured response to verify the developed technique. The results show that the developed methodology performs well in predicting the properties of the complex 3-D MPML braided composite.