JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI ›› 2010, Vol. 27 ›› Issue (7): 31-35.

• HEALTHY CHANGJIANG RIVER • Previous Articles     Next Articles

A Constitutive Model of Reinforced Clay Based on RBF Neural Network

SHI Xiu-song, WANG Lu-jun, CHENG Zhan-lin   

  1. Key Laboratory of Geotechnical Mechanics and Engineering of The Ministry of Water Resources,  Yangtze River Scientific Research Institute, Wuhan 430010 , China
  • Online:2010-07-01 Published:2012-08-21

Abstract: Indoor, triaxial tests were carried out to obtain the stress-strain relationship of reinforced clay. A RBF neural network constitutive model of reinforced clay was established based on test data. The authors used it to simulate the constitutive model of reinforced soil under different reinforced layers. Compared with the experimental value, the result shows that, the RBF neural network has a good approach to the constitutive relationship of reinforced clay and a strong generalization ability. It can reflect well the number of reinforced material layers and the stress path.

Key words: triaxial test, constitutive model , RBF neural network , reinforced clay

CLC Number: