Brittleness plays an important role in the brittle failure process of rocks, and is also one of the important mechanical properties of rocks and a key indicator in rock engineering such as hydraulic fracturing, tunnelling machine borehole drilling and rockburst prediction. Therefore, aiming at the applicability of the brittleness index, this paper summarizes and analyzes the existing brittleness indices based on different experimental methods. Through analysis, it is found that many of the existing methods have their limitations. On the other hand, the brittleness evaluation method based on the stress sstrain curve makes it easier to obtain key parameters and quantify them. Therefore, this paper also adopts this practically widely used method. It proposes a brittleness index based on the post-peak stress drop rate of the rock stress-strain curve and the difficulty of brittle failure, verifies by the traditional triaxial surrounding rock pressure test the accuracy and superiority of B L and further explores the differences between the brittleness indices B 8 , B 11 , B 12 and B L. Finally, the brittleness index B L and B 13 are further contrasted by the existing experimental data.

Based on the analysis of the shortcomings of the grey wolf optimization algorithm, an improved grey wolf optimization algorithm (SGWO) is proposed. The algorithm uses the convergence factor based on S-function change to balance the global search and local search ability of the algorithm. At the same time, the proportion weight based on Euclidean distance of step size and the individual optimal position of the particle swarm optimization algorithm are introduced to update the grey wolf position, thus speeding up the convergence speed of the algorithm to 8. The simulation results of three classical test functions show that the SGWO algorithm has higher accuracy and better stability.Introduction

Abstract. Guano flashover belongs to a form of pollution flashover, whose process is complex. Bird droppings shows liquid and has a certain viscosity and high conductivity, especially the conductive rate of some wading bird droppings reaches 6000~8000μs/cm. This article expounds the guano flashover generally can be divided into the following four conditions, and analyzes the reason causing the guano flashover, examples and proposes the corresponding solution measures.

Transformer in the operation process, iron core, winding and steel structure to produce loss. These losses will produce heat, leading to the transformer temperature rise, the aging of insulation materials to accelerate, the transformer's service life is shortened. In order to ensure that the temperature of each component of the transformer is not more than the limit value, the service life of the transformer is prolonged, and the temperature measuring device must be installed. The temperature measuring device is used to monitor the temperature and temperature change of the transformer. The existing temperature measuring device has the problem of bad sealing, and the water enters the temperature measuring device through the temperature measuring hole. In winter, the water is converted into ice, and the thermometer is easily cracked, leading to the failure of the function of the temperature measuring device. An effective method is described in this paper to avoid the thermometer being ruptured. Because the performance and density of anti freezing agent is better than that of transformer oil, special anti freeze agent is used to replace transformer oil in the temperature measuring hole. So, completely solve the problem of the thermometer damage accident.