Summary
Many pieces of evidence have confirmed that the seepage in fine‐grained soils can deviate from traditional Darcy's law that contributes to the consolidation theory. In this paper, a numerical model, referred to as consolidation with non‐Darcian flow 2 (CNDF2), is developed for the 1D large strain consolidation of a saturated porous medium with the non‐Darcian flow. The algorithm accounts for vertical strain, general constitutive relationships, the relative velocity of the fluid and solid phases, variable compressibility and permeability relation during consolidation, time‐dependent loading, and unload/reload effects. Compared with the CS2 model proposed in previous studies, some parts of the CNDF2 model are modified in order to adapt to the non‐Darcian flow, especially the equivalent series hydraulic conductivity and fluid flow. The verification examples of the CNDF2 model demonstrate excellent accuracy for both small strain and large strain consolidation. According to the applicable conditions of non‐Darcian flow law, the CNDF2 model is most suitable for the fine‐grained soil. The development of CNDF2 is first presented, followed by examples to analyze the influences of the non‐Darcian flow on the consolidation behavior.
This paper presents an artificial neural network (ANN)-based response surface method that can be used to predict the failure probability of c- slopes with spatially variable soil. In this method, the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model; the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties; and finally, an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables. The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability. As a result, the obtained approximate function can be used as an alternative to the specific analysis process in c- slope reliability analyses.
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