Prediction of multidimensional deformation behavior based on observed values

In this study, a method is developed for predicting the future deformation of soft ground, based on measured data. Because it is difficult to predict the deformation behavior of soft ground on the basis of laboratory consolidation test results only, in situ observations are generally made. An inverse analysis is effective for identifying the in situ parameters of the ground and for predicting future deformation based on those parameters. In the method proposed, the induced anisotropy (transverse isotropy) of the ground is introduced to solve the problem of predicting lateral displacement, and a simplified hyperbolic model is introduced to simulate nonlinear shear behavior. Furthermore, the change in volume compressibility of the material and the decrease in permeability caused by consolidation are considered simultaneously through the use of a statistical model for the soil parameters. This statistical model, which takes the nonlinearity of the parameters into account, is called the stochastic nonlinear model (SNM). To verify the usefulness of the proposed method, the results of two-dimensional deformation tests are analyzed.