Inversion Analysis Based on the Unloading Rock Mass of Underground Powerhouse Monitoring Achievements of Jin Ping Cascade II Hydropower Station

Abstract:

On the basis of unloading rock mass theory, we identify the excavated rock mass parameters by means of neural network training in each step, in which the subjective factors of the parameters selected process have largely been decreased. Through inducing the parameters of inversion into two -dimensional modeling, we aim to do the numerical simulation computing in various conditions. By comparison, the calculated displacement trend of the measuring points following the multi-point extensometers is basically identical with the monitoring displacement trend.

• Periodical: Advanced Materials Research (Volumes 430-432)
• Pages: 1455-1459
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.430-432.1455
• Online since: January 2012
• Authors: Jie Liu, Jian Lin Li, Lei Xiao, Shi Wei Luo, Jian Cai
• Keywords: BP Neural Network (BPNN), Parameters Inversion, Two-Dimensional Finite Element Calculation, Unloading Rock Mass Theory

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