Dynamic analysis of coal stick-slip impact based on physical information neural network

Abstract

At present, physical information neural network has become a new paradigm for numerical calculation of engineering mechanics. It can solve partial differential equations by integrating the physical mechanism of neural network in the case of unlabeled sample data, and solve them quickly with low computational cost. In this paper, the calculation principle of physical information neural network(PINN) and the framework for solving the governing equation of coal stick-slip impact are expounded. By comparing the solution results with the explicit finite difference method, the effective accuracy of the solution results is verified. Taking the working face of No.12 coal seam in Jinhuagong Mine as the research background, the dynamic numerical simulation of coal stick-slip impact is carried out, and the occurrence time interval and fluctuation rule of coal stick-slip deformation process are obtained by means of numerical simulation. The numerical simulation results show that when the abutment pressure concentration coefficient is 2, the maximum value of coal stick-slip displacement(deformation) increases obviously; when the abutment pressure concentration coefficient is 3, the typical stick-slip phenomenon occurs, and the displacement changes quasi-periodically, the storage elastic energy of coal stick-slip system gradually increases, and the strength damage of coal-rock stick-slip process occurs. The dynamic friction factor has a great influence on the coal stick-slip dynamic characteristics. When the dynamic friction factor changes, the displacement field of the coal stick-slip system changes obviously.

Keywords

• physical information neural network(pinn)
• coal body stick-slip
• rock burst
• dynamic characteristics
• numerical simulation