Abstract
The low efficiency of feedback analysis is one of the main shortcomings in the construction of underground cavern engineering. With this in mind, a method of intelligent autofeedback and safety early-warning for underground cavern is proposed based on BP neural network and FEM. The training sample points are chosen by using uniform test design method, and the autogeneration of FEM calculation file for ABAQUS is realized by using the technique of file partition, information grouping, and orderly numbering. Then, intelligent autoinversion of mechanics parameters is realized, and the automatic connection of parameter inversion, subsequent prediction, and safety early-warning is achieved. The software of intelligent autofeedback and safety early-warning for underground cavern engineering during construction is developed. Finally, the applicability of the proposed method and the developed software is verified through an application example of underground cavern of a pumped-storage power station located in Southwest China.
Highlights
The development of civil engineering, water conservancy and hydropower, transportation engineering, and mining industry boosts continuous and fast construction of underground cavern in China
The applicability of the proposed method and the developed software is verified through an application example of underground cavern of a pumped-storage power station located in Southwest China
The applicability of the proposed method and the developed software IFWUC is verified through an application example of underground cavern of a pumped-storage power station located in Southwest China
Summary
The development of civil engineering, water conservancy and hydropower, transportation engineering, and mining industry boosts continuous and fast construction of underground cavern in China. The inversion of mechanical parameters, prediction of the stress and deformation of the surrounding rock in the subsequent construction steps, and safety early-warning are main procedures of feedback analysis. Many procedures such as selection of sample points, generation of sample FEM calculation file, FEM analysis, extraction of FEM results, generation of sample input and output files, establishment of mapping model, input of monitoring data, and output of the inversion parameters are involved. The inversion of mechanical parameters of surrounding rock, subsequent prediction, safety earlywarning, and revision of predesign are the critical procedures of feedback analysis during the construction of underground craven. The automation of FEM analysis, extraction of FEM results, generation of sample input and output files, inputting monitoring data and outputting inversion parameters, subsequent perdition, and safety early-warning are realized through programming.
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