Elastic-plastic constitutive model of artificial frozen soil based on cascade-correlation artificial neural network

Elastic-plastic consistent stiffness matrix was derived based on a neural network constitutive model for frozen soil.Neural network model was trained by the triaxial test data and the traditional finite element constitutive model was replaced by the trained model.The calculated results of the same properties and moisture content of frozen soil were compared with the experimental results.It was found that this neural network constitutive model represents the nonlinear response of the material very well, can improve the numerical analysis results, and agrees very well with the measured results.The deep freezing engineering numerical simulation results show that the artificial frozen soil BP neural network constitutive model can well describe the complex stress path deformation characteristics.The numerical results and site measurement are consistent and the measured displacement error is 5.0%; The BP neural network constitutive model accurately predicts the stress field and deformation field of artificial frozen soil curtain, and provides some guidance for freezing engineering design and construction.