Abstract
Saline-alkali soil is typically expansible due to salt expansion. Salt expansion always affected by water migration and salt crystallization. As for the soil in frozen ground, salt expansion behavior is also influenced by the temperature and the salt-water reaction. Thus the expansion behavior of frozen saline-alkali soil is a complex and nonlinear problem, which brings damages to structures and engineering, such as subgrade and infrastructure deformations. In this paper, experiment of salt expansion behaviors is carried on, in which the soil samples are mixed with different content of water, salt. And the influence of the water and salt on the salt expansion is analyzed. To study the salt expansion characteristics, two different kinds of mathematical methods are applied, including the back propagation neural network (BPNN) and support vector machine for regression (SVR). 300 data are used for training, and 35 data are used for testing. The calculated results of BPNN and SVR are compared with the experimental data. The results indicate that SVR is superior to BPNN in prediction. And both methods indicated that water and salt influenced salt expansion strongly, which provides reference in environment engineering and chemical engineering.
