Stablity Monitoring And Back Analysis Of Displacement Of Rockmasses Surrounding The Emptying Tunel In Pubugou Hydropower Project

In this paper, As Pubugou hydropower station emptying tunnel for the object of research. Through monitoring the stability of surrounding rockmasses in construction period , combined with geological conditions, analysis deformation processes of surrounding rockmasses , as well as characteristics and a variety of factors; then through artificial neural network theory and the theory of displacement back-analysis study,combining orthogonal design and FLAC numerical procedures,using the BP neural network to realize the process of displacement back analysis about initial geostress and parameters of surrounding rockmasses ,and discuss the reliability and factors of the results.Finally use the results to simulate the construction process.(1) Discuss the monitoring of hydrotic tunnel about project selection ,instrument selection and monitoring design in different stages,and introduce the monitoring of emptying tunnel in Pubugou hydropower station about construction period(2) By monitoring the stability of surrounding rock masses in construction period , combined with geological data and construction process,to analysis deformation of the surrounding rock masses relations with time,space, hole depth as well as excavation footage,and stress change of cables. Rock deformation mainly concentrated in the section at the bottom of the excavation process, surrounding rockmasses deformation mainly concentrated in the section at the bottom of the excavation process, the support of the changes in stress focused mainly on this process, construction of the first half of the course of 3-3 hole section of the dome collapse occurred mainly due to lagging support, non-standard due to blasting.(3)Mehtod based on Artificial Neural Network Analysis of the anti-displacement , and its essence is still a direct anti-displacement analysis. Ideas based on Artificial Neural Network Analysis of the anti-displacement include: the establishment of the tunnel excavation using FLAC numerical analysis model, theoretical calculation, the number of groups in different parts of the displacement. Displacement data of these samples as a training into the preparation of a good artificial neural network learning process, and then the measured data into the trained artificial neural network anti-analysis, has been pending for the parameters(4) By orthogonal test analysis to determine parameters of the sample composition, use FLAC to calculate the surrounding rockmasses deformation about different samples, displacement values as an input sample and parameters as an output sample is brought into the BP neural network,then the measured displacement values is brought into the training network,so getting the initial stress parameters ,elastic modulus and poisson's ratio of surrounding rockmasses. Initial stress to the level of stress mainly for 22.105MPa, the equivalent elastic modulus for 7.38GPa, the equivalent Poisson's ratio of 0.2663.(5) Use the results to simulate the process of construction ,analysis the surrounding rock deformation,the distribution of plastic zone of different cross-section at the bottom of the excavation,as well as restoring the process of surrounding rock masses about the entire construction period. At the bottom of the excavation process of the surrounding rock deformation mainly concentrated at the bottom of the excavation cross-section at a distance of 2D (D is diameter) rock excavation within the scope of the process; at the bottom of the distribution of the excavation cross-section than the one arising from the excavation site in the bottom of the plastic areas to small, mainly simulation did not consider support measures.