Zoned safety monitoring model for uplift pressures of concrete dams

Abstract

Uplift pressure beneath concrete dams is related to several intrinsic factors such as geological structure, qualities of grouting and drainage engineering, and so forth. Thus, the fluctuation law and the amplitude of the uplift pressure vary along the dam axis. Based on observation data, the data mining method can be used to divide the piezometers beneath concrete dams into several zones, with similar fluctuation laws in measurement, to better identify the spatial distribution mechanism of the foundation uplift pressure. Then, zoned regression models can be established to mine the essential causes of the abnormal zone. In this paper, data mining algorithms such as time series piecewise representation, similarity measure and cluster analysis are combined to propose the zoning method for piezometers. On this basis, the variable coefficient panel data model is employed to establish regression models of various zones of piezometers. The Xixi Reservoir Dam is taken as a case study. According to the supplementary geological survey result, the credibility of the proposed method is verified. Further discussion shows that the causes of the sudden increases of the abnormal zone under the unfavorable condition include the development of local rock fissures, the aging of the grouting curtain. The observation data after the curtain reinforcement shows that uplift pressures in the abnormal zone are getting normal. The proposed method can also be easily applied to the zoned safety monitoring of arch dam deformation, reservoir slope stability, lateral bypass seepage, and so forth.