Drainage conditions have significant influence on the liquefaction behaviour of soil. In this study, cyclic triaxial tests were conducted on saturated Fujian standard sand under different drainage conditions. A new infiltration device was designed to simulate the different drainage conditions by controlling the permeability coefficient of the silt inside. Permeability coefficient ratio (kp) is introduced to measure the effect of different drainage conditions (k p = k i /k o, where k i is the permeability coefficient of the silt at different dry density; k o is the permeability coefficient of the saturated sand specimen). A series of cyclic triaxial tests were conducted to evaluate the response regularity of excess pore water pressure (EPWP) of saturated sand under different drainage conditions. Test results indicate that different drainage conditions have obviously effects on the EPWP generation. Based on the strain energy concept, an EPWP generation model is developed by considering the effect of drainage condition and it shows good agreement with the test observations.
Using undrained triaxial shear tests, this study investigates the mechanical properties of fine-grained materials (silty clay and sand) which are extensively used for China’s Qinghai–Tibet Railway (QTR) under different confining pressures (σ3) and freezing temperatures (T). The results show that a reduction in T causes an increase in the shear strength and elastic modulus of all the materials tested in the present study. In addition, the freezing of the silty clay has no significant effect on the type of soil behaviour (strain-hardening), whereas the freezing of the sand changes its strain-hardening behaviour to strain-softening. Supposing that the deviatoric stress–strain curves of the silty clay and sand can be divided into two segments due to a reverse bending point, it was assumed that the first segment follows a hyperbolic function. Meanwhile, the second segment is also a hyperbola, with the reverse bending point as the origin and the residual strength as the asymptote. Accordingly, a nonlinear relation constitutive model that considers σ3 and T is derived. All model parameters are identified. The reasonability of the new model was verified using the test results of the materials. A comparison of the predicted and test results shows that this model can well simulate the deviatoric stress–strain response in the failure process of the tested materials. In particular, it can reflect the residual deviatoric stress after the materials’ failure.
Drainage conditions are supposed to have significant influence on sand liquefaction behavior. An infiltration device was utilized in cyclic triaxial tests to reproduce different drainage conditions by altering dry density of the within silt. Permeability coefficient ratio (kp) was utilized for quantifying the drainage boundary effect. Cyclic triaxial tests were conducted on saturated Fujian standard sand samples. Test results were used to evaluate the liquefaction potential by using the energy approach. It can be concluded that, if kp increases slightly bigger than zero, excess pore water pressure (EPWP) will respond more fiercely, and the dissipated energy that triggers sand liquefaction will be less. By considering kp, an energy-based database was built by taking kp into consideration and different neural network (NN) models were constructed to predict liquefaction potential by energy approaches accurately under different drainage boundary conditions. It was suggested that the neuro-fuzzy (NF)-based NN model has more satisfactory performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.