Inversion Method of In-situ Stress and Rock Damage Characteristics in Dam Site Using Neural Network and Numerical Simulation—A Case Study

Abstract

In mountain and ravine region of southwest China, several hydropower stations have been built in this area. It is the main national base for hydropower energy development, but under the influence of geological structure and surface erosion, the in-situ stress environment in this area is more complex. The main purpose of this paper is to establish the relationship between measured in-situ stress data and numerical calculation by means of neural network. Therefore, it can be used to analyze the distribution characteristics of large-scale in-situ stress and the failure of regional geological bodies under the action of in-situ stress in Xiluodu area. This paper analyzes the geological conditions and the measured data of in-situ stress in Xiluodu area. The results show that there is obvious surface weathering phenomenon in this area, the stress environment is complex. The depth has a positive impact on the level of in-situ stress, but the impact degree is different. The genetic algorithm-BP artificial neural networks (G-P) method is trained by the measured in-situ stress data. Based on the field measurement data, neural network algorithm and numerical simulation technology, the three-dimensional in-situ stress field distribution characteristics of the project area are carried out. The research shows that the scheme of combining the actual measurement, numerical analysis and neural network inversion is reliable; Depth is an important factor affecting the maximum horizontal stress value in Xiluodu area; Under the action of in-situ stress, the fissures of geological body are relatively developed, and three types of original water storage and flow spaces are formed before dam storage period; The flow and storage space of groundwater includes limestone fracture, basalt fracture and slope fracture aquifer; After the impoundment of the reservoir area, the reservoir water is transmitted downward through the vertical fissures, and finally the reservoir water forms a hydraulic connection with the groundwater. After impoundment, the hydrogeological conditions of the reservoir area would be changed.

Keywords

• In-situ stress
• numerical simulation
• neural network
• in-situ stress inversion
• geological rock mass damage
• hydraulic connection