Permeability characteristics of bedrock fissures under disturbance conditions based on neural network

Abstract

During different periods of rock fracture engineering, the surrounding rock is subject to intermittent and periodic vibration disturbances of different degrees. This disturbance has a great influence on the permeability characteristics of bedrock fissures. The permeability characteristics of bedrock fissure permeability are the most important hydrogeological element of underground water-containing medium, and determining the stratum permeability is an important link to evaluate the hydrogeological conditions of the mining area. Therefore, this paper studies the permeability characteristics of bedrock fissures based on the disturbance of neural network. First, use the basic structure of the neural network to understand the method applied to the study of permeability characteristics of bedrock cracks; secondly, put forward the rock permeability model driven by coal mining to help the subsequent experimental design of various relevant factors after the bedrock cracks Finally, the stress intensity factor method at the tip of the fracture is used to calculate the permeability of the bedrock fracture. The experimental data shows that the infiltration rate tested in the first minute of the experiment is 5.5 * 10−4 cm/s, which is equivalent to 12 times the stable infiltration rate. At 50 min after the start of the test, the infiltration rate dropped to 4.6 * 10−4 cm/s, which was close to the stable infiltration rate. The experimental results show that under the disturbance condition of neural network, the infiltration rate of bedrock fissures is accelerated and the permeability is increased.