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The freezing and freeze-thaw cycles may reduce the mechanical strength of the material for a concrete faced rockfill dam (CFRD), resulting in the risk of structural damage to the dam under the design load. In order to study the influence of freezing and freeze-thaw on the stress and deformation of the CFRDs, some experimental results and theoretical analysis for the influence of freezing and freeze-thaw cycles on the mechanical parameters of concrete face slab and rockfill were introduced at first. The finite element method (FEM) was adopted for the structural analysis of a CFRD in the high altitude area of Qinghai-Tibet Plateau of China. Using the FEM analysis results, the distribution of stress and deformation of concrete face slab and dam body were obtained and a comparison was made with the analysis results when the freezing and freeze-thaw cycles were not taken into account. Some conclusions were drawn from these analysis results and the research results provide a reliable basis for the design and construction of the CFRD in the future.

Aiming at the problem of low precision and poor forecasting results of traditional statistical model and neural network model under the influence of abnormal discrete values. This paper construct a new dam displacement prediction model based on outlier-robust extreme learning machine and the characteristics of environmental factors affecting the deformation of earth-rock dam. Compared with other models, the outlier-robust extreme learning machine model is more robust, anti-noise and easy to generalize. The analysis of engineering example shows that the ORELM model has higher fitting precision and better forecasting results. It is advanced and reasonable in the prediction of earth-rock dam displacement, and it can be used as a reference for similar projects.