Evaluation of the Change in Undrained Shear Strength in Cohesive Soils due to Principal Stress Rotation Using an Artificial Neural Network

Undrained shear strength had a major principal stress value in the σ1 horizontal, which was about 0.70 of the value of that of the vertical σ1, as previously observed in the literature [4,5,6,7,8]. [...]when determining the bearing capacity of the subsoil, changes resulting from this phenomenon should be taken into account. [...]other methods to evaluate the change in undrained shear strength are used. [...]the process of sample shearing was carried out in the stress path, involving an increase in deviator stress, q, and a constant value of total mean stress, p. During the entire shearing process of the soil samples, values of parameter b and angle α were kept constant. The predictive quality of the neural regression model was evaluated on the basis of error analysis, and calculated independently for the following subsets: learning, L , testing, T , and validation, V . Neural networks were optimized for the number of neurons in the hidden layer, the activation function in the neurons of the hidden and output layers, and the learning method.