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http://dx.doi.org/10.12989/cac.2017.19.5.527

An approach of evaluation and mechanism study on the high and steep rock slope in water conservancy project  

Yang, Meng (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University)
Su, Huaizhi (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University)
Wen, Zhiping (Department of Computer Engineering, Nanjing Institute of Technology)
Publication Information
Computers and Concrete / v.19, no.5, 2017 , pp. 527-535 More about this Journal
Abstract
In this study, an aging deformation statistical model for a unique high and steep rock slope was proposed, and the aging characteristic of the slope deformation was better reflected. The slope displacement was affected by multiple-environmental factors in multiple scales and displayed the same tendency with a rising water level. The statistical model of the high and steep rock including non-aging factors was set up based on previous analyses and the study of the deformation and residual tendency. The rule and importance of the water level factor as a non-aging unit was analyzed. A partitioned statistical model and mutation model were established for the comprehensive cumulative displacement velocity with the monitoring study under multiple factors and multiple parameters. A spatial model was also developed to reflect and predict the whole and sectional deformation character by combining aging, deformation and space coordinates. A neural network model was built to fit and predict the deformation with a high degree of precision by mastering its feature of complexity and randomness. A three-dimensional finite element model of the slope was applied to approach the structure character using numerical simulations. Further, a three-dimensional finite element model of the slope and dam was developed, and the whole deformation state was analyzed. This study is expected to provide a powerful and systematic method to analyze very high, important and dangerous slopes.
Keywords
high and steep slope; statistic model; spatial model; neural network; finite element model;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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